{ "title": "The AI at Work Fact Book", "edition": "2026 edition", "publisher": "EVY", "url": "https://evy.so/facts/", "license": { "name": "CC BY 4.0", "url": "https://creativecommons.org/licenses/by/4.0/", "credit": "The AI at Work Fact Book by EVY (evy.so/facts)" }, "last_checked": "2026-10-14", "method": "Every range comes from primary sources that were opened and read. Figures that circulate but could not be traced to a primary source are listed under numbers_you_may_have_seen and are never used in a range.", "chapters": [ { "n": 1, "title": "Where the Week Goes", "url": "https://evy.so/facts/where-the-week-goes/", "poster": "https://evy.so/facts/where-the-week-goes/sheet/", "facts": [ "F-01", "F-02", "F-03", "F-04", "F-05", "F-06", "F-07" ] }, { "n": 2, "title": "What AI Saves", "url": "https://evy.so/facts/what-ai-saves/", "poster": "https://evy.so/facts/what-ai-saves/sheet/", "facts": [ "F-08", "F-09", "F-10", "F-11", "F-12", "F-13" ] }, { "n": 3, "title": "Who Uses AI at Work", "url": "https://evy.so/facts/who-uses-ai-at-work/", "poster": "https://evy.so/facts/who-uses-ai-at-work/sheet/", "facts": [ "F-14", "F-15", "F-16", "F-17", "F-18", "F-19", "F-20" ] }, { "n": 4, "title": "What Teams Trust", "url": "https://evy.so/facts/what-teams-trust/", "poster": "https://evy.so/facts/what-teams-trust/sheet/", "facts": [ "F-21", "F-22", "F-23", "F-24", "F-25", "F-26", "F-27" ] }, { "n": 5, "title": "Small Teams", "url": "https://evy.so/facts/small-teams/", "poster": "https://evy.so/facts/small-teams/sheet/", "facts": [ "F-28", "F-29", "F-30", "F-31", "F-32", "F-33" ] }, { "n": 6, "title": "Europe", "url": "https://evy.so/facts/europe/", "poster": "https://evy.so/facts/europe/sheet/", "facts": [ "F-34", "F-35", "F-36", "F-37", "F-38", "F-39", "F-40" ] } ], "facts": [ { "id": "F-01", "url": "https://evy.so/facts/time-spent-searching-for-information/", "chapter": "Where the Week Goes", "question": "How much of the work week do knowledge workers spend searching for information?", "answer": "The most-cited studies put it at 19 to 25 percent of the work week, or about 9 to 10 hours. Across all five studies the estimates run from about 5 to 15 hours a week, because each one defines searching a little differently.", "range": { "low": 19, "high": 25, "unit": "% of the work week", "display": "19–25% of the work week, about 9 to 10 hours" }, "spread": { "low": 5, "high": 15, "unit": "hours a week" }, "confidence": "medium", "confidence_reason": "Three independent studies agree on 19 to 25 percent, but all five are self-reported surveys, and two vendor surveys sit well below and above that cluster.", "last_checked": "2026-10-13", "how_to_read": "All five figures are people's own estimates; none comes from time tracking. They also count different things: McKinsey includes tracking down colleagues, Qatalog counts only searching inside work apps, and Atlassian gives no definition. McKinsey re-used IDC's 2009 survey, so its number is a 2009 measurement published in 2012. Three of the five creators sell search or work-hub software. Hours assume a 5-day week; McKinsey's share uses the 46.5-hour week its respondents reported.", "sources": [ { "creator": "McKinsey Global Institute, using IDC survey data", "title": "The social economy: Unlocking value and productivity through social technologies", "year": 2012, "sample": "Managers and professionals in IDC's 2009 survey; sample size not stated", "method": "Re-analysis of IDC's self-reported time-use survey", "figure": "19% of the week (8.8 of 46.5 hours)", "url": "https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-social-economy", "archive_url": "https://web.archive.org/web/20260710105837/https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-social-economy", "quote": "19 percent of working hours trying to track down information needed to complete tasks" }, { "creator": "Atlassian Teamwork Lab", "title": "The State of Teams 2025", "year": 2025, "sample": "12,000 knowledge workers and 200 Fortune 1000 executives in the US, UK, Australia, India, Germany and France", "method": "Online survey, self-reported", "figure": "25% of the workweek", "url": "https://www.atlassian.com/blog/state-of-teams-2025", "quote": "Executives and teams alike spend a quarter of the workweek searching for information" }, { "creator": "Glean, survey by The Harris Poll", "title": "Hybrid Workplace Habits & Hangups", "year": 2022, "sample": "1,043 employed US adults", "method": "Online survey, December 2021, self-reported. Glean sells enterprise search.", "figure": "At least 2 hours a day, or 25% of the workweek, looking for documents, information or people", "url": "https://www.businesswire.com/news/home/20220208005510/en/Hybrid-Workplace-Habits-Hangups-Report-Frustrated-Employees-Spend-a-Quarter-of-Workweek-Searching-for-Information-Needed-to-Do-Their-Jobs", "archive_url": "https://web.archive.org/web/20260615090357/https://www.businesswire.com/news/home/20220208005510/en/Hybrid-Workplace-Habits-Hangups-Report-Frustrated-Employees-Spend-a-Quarter-of-Workweek-Searching-for-Information-Needed-to-Do-Their-Jobs", "quote": "spend, on average, at least two hours a day" }, { "creator": "Qatalog with Cornell University's Ellis Idea Lab", "title": "Workgeist Report '21", "year": 2021, "sample": "Three surveys of about 1,000 remote-working professionals each, US and UK", "method": "Online surveys, March 2021, self-reported. Counts only searching inside work apps. Qatalog sells a work hub.", "figure": "59 minutes a day finding information trapped in apps and tools", "url": "https://qatalog.com/", "archive_url": "https://web.archive.org/web/20210624191022/https://assets.qatalog.com/language.work/qatalog-2021-workgeist-report.pdf", "quote": "up to 5 hours a week, just trying to find what we need" }, { "creator": "Coveo, survey by Arlington Research", "title": "EX Relevance Report 2025: The Search for Relevance", "year": 2025, "sample": "4,000 people who use a computer for work at companies with 5,000 or more staff, US and UK", "method": "Online survey, self-reported. Coveo sells AI search.", "figure": "3 hours a day searching for information (3.6 hours in the 2022 edition)", "url": "https://www.coveo.com/en/company/news-releases/2025/coveo-ex-relevance-report", "quote": "an average of three hours daily searching for information" } ], "related_findings": [ { "question": "How many hours a day do people spend looking for information?", "answer": "About 1.8 to 2 hours a day in the main cluster: McKinsey's 8.8 hours a week over 5 days, and Glean's at least 2 hours a day. The full spread runs from about 1 hour a day (Qatalog, inside work apps only) to 3 hours a day (Coveo).", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "McKinsey: 19.8% of the week is spent searching for information.", "what_the_source_says": "The report says 19 percent, and \"nearly 20 percent\" in its summary. The figure 19.8% does not appear in it." }, { "claim": "IDC: knowledge workers spend 15 to 35% of their time searching, or 2.5 hours a day.", "what_the_source_says": "The 2.5 hours was a working assumption IDC used to model costs in 2001. The 15 to 35% rolls up older studies that are not named, so neither figure traces back to a measurement." }, { "claim": "Gartner: professionals spend 47% of their time searching for information.", "what_the_source_says": "Gartner's 2023 survey found that 47% of digital workers struggle to find the information they need. It counts people and gives no figure for time." }, { "claim": "Microsoft: 62% of time goes to searching for information.", "what_the_source_says": "In Microsoft's 2023 Work Trend Index, 62% of people say they struggle with too much time spent searching. It is a share of people and gives no figure for time." } ], "citation": "EVY (2026). How much of the work week do knowledge workers spend searching for information? The AI at Work Fact Book, F-01. https://evy.so/facts/time-spent-searching-for-information/ (last checked October 13, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-02", "url": "https://evy.so/facts/time-on-work-about-work/", "chapter": "Where the Week Goes", "question": "How much of the work day goes to coordinating work rather than doing it?", "answer": "Between 53 and 61 percent, or roughly three of every five working hours. Four independent creators (Asana, McKinsey with IDC data, Microsoft and Workfront) land in that band, though each draws the line around coordination a little differently.", "range": { "low": 53, "high": 61, "unit": "% of working time", "display": "53–61% of working time, from 4 independent creators" }, "confidence": "high", "confidence_reason": "Four independent creators using surveys, adjusted survey data and app usage data converge on 53 to 61 percent. Definitions differ, and three of the four are self-reported or vendor-built.", "last_checked": "2026-10-13", "how_to_read": "Each study draws the line differently. Asana counts self-reported work about work, which includes searching, switching apps and chasing status. McKinsey counts everything outside role-specific tasks, including email. Microsoft compares time in communication apps with time in creation apps, so it only sees work done inside Microsoft 365. Workfront asks how much of the day goes to the job people were hired for. Asana's six editions come from one creator, so they count once toward agreement, and the 2024 change of label and panel means the series is not one clean trend.", "sources": [ { "creator": "Asana, survey by Sapio Research", "title": "Anatomy of Work Index 2019", "year": 2019, "sample": "10,223 knowledge workers in Australia, New Zealand, Germany, Japan, the UK and the US", "method": "Online survey, August to September 2019, self-reported. Asana sells work management software.", "figure": "60% work about work, 27% skilled work, 13% strategic work", "url": "https://resources.asana.com/rs/784-XZD-582/images/Anatomy-of-Work-Index.pdf", "quote": "The average knowledge worker devotes 60% of their time to work about work" }, { "creator": "Asana, survey by Sapio Research", "title": "Anatomy of Work Index 2021", "year": 2021, "sample": "13,123 knowledge workers in seven countries", "method": "Online survey, October 2020, self-reported", "figure": "60% work about work (France 66%)", "url": "https://asana.com/resources/anatomy-of-work-index", "archive_url": "https://web.archive.org/web/20210301155022/https://resources.asana.com/rs/784-XZD-582/images/PDF-FY21-Global-EN-Anatomy%20of%20Work%20Report.pdf", "quote": "knowledge workers continue to spend 60% of their day on work about work" }, { "creator": "Asana, survey by GWI", "title": "Anatomy of Work Index 2022", "year": 2022, "sample": "10,624 knowledge workers in seven countries", "method": "Online survey, October 2021, self-reported", "figure": "58% work about work, 33% skilled work, 9% strategic work", "url": "https://www.businesswire.com/news/home/20220405005399/en/Asana-Anatomy-of-Work-Index-2022-Work-About-Work-Hampering-Organizational-Agility", "archive_url": "https://web.archive.org/web/20260411014513/https://www.businesswire.com/news/home/20220405005399/en/Asana-Anatomy-of-Work-Index-2022-Work-About-Work-Hampering-Organizational-Agility", "quote": "individuals are dedicating 33% of their day to skilled work" }, { "creator": "Asana, survey by GWI", "title": "Anatomy of Work Global Index 2023", "year": 2023, "sample": "9,615 knowledge workers in the US, UK, Australia, France, Germany and Japan", "method": "Online survey, November 2022, self-reported", "figure": "58% work about work", "url": "https://investors.asana.com/news-releases/news-release-details/asana-anatomy-work-global-index-2023-smart-collaboration-and", "archive_url": "https://web.archive.org/web/20260407093353/https://investors.asana.com/news-releases/news-release-details/asana-anatomy-work-global-index-2023-smart-collaboration-and" }, { "creator": "Asana Work Innovation Lab", "title": "State of Work Innovation 2024", "year": 2024, "sample": "13,066 knowledge workers in the US, UK, Germany, France, Japan and Australia", "method": "Online surveys, February to August 2024, self-reported. New label (busywork) and new survey panels.", "figure": "53% of time on busywork", "url": "https://asana.com/resources/state-of-work-innovation", "quote": "more than half (53%) of workers' time is swallowed up by busywork" }, { "creator": "Asana Work Innovation Lab", "title": "State of AI at Work 2025", "year": 2025, "sample": "9,236 knowledge workers in the US, UK, Germany, Japan and Australia", "method": "Online surveys, February to August 2025, self-reported", "figure": "55% of time on busywork", "url": "https://asana.com/resources/state-of-ai-work", "quote": "Knowledge workers spend 55% of their time on busywork" }, { "creator": "McKinsey Global Institute, using IDC survey data", "title": "The social economy: Unlocking value and productivity through social technologies", "year": 2012, "sample": "Managers and professionals in IDC's 2009 survey; sample size not stated", "method": "Re-analysis of IDC's self-reported time-use survey", "figure": "61% of the week outside role-specific work: 28% email, 19% searching, 14% internal communication", "url": "https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-social-economy", "archive_url": "https://web.archive.org/web/20260710105837/https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-social-economy" }, { "creator": "Microsoft", "title": "2024 Work Trend Index Annual Report", "year": 2024, "sample": "Anonymized usage data from commercial Microsoft 365 customers, 28 days to March 2024, outside the EU", "method": "App usage data, observed. Measures time inside Microsoft 365 apps only.", "figure": "60% of time in emails, chats and meetings; 40% in creation apps such as Word and PowerPoint", "url": "https://assets-c4akfrf5b4d3f4b7.z01.azurefd.net/assets/2024/05/Microsoft_2024_Work_Trend_Index_Annual_Report_663b79bdc8f91.pdf", "quote": "users spend 60% of their time on emails, chats, and meetings" }, { "creator": "Workfront, survey by Regina Corso Consulting", "title": "2019 US State of Work", "year": 2018, "sample": "2,010 US office workers at companies with 500 or more staff", "method": "Online survey, June 2018, self-reported. Workfront sells work management software.", "figure": "40% of the workday on primary tasks, so 60% on everything else", "url": "https://business.adobe.com/products/workfront.html", "archive_url": "https://web.archive.org/web/20190907022647/https://www.workfront.com/sites/default/files/files/2019-01/2019%20US%20State%20of%20Work.pdf", "quote": "U.S. workers say they spend only 40% of their workday on their primary tasks" } ], "related_findings": [ { "question": "Is work about work going down?", "answer": "Slightly, in Asana's series: 60% (2019), 60% (2021), 58% (2022), 58% (2023), then 53% (2024) and 55% (2025). From 2024 Asana relabeled it busywork and changed survey panels, so the last two years are not directly comparable. In 2019, respondents guessed they spent only 35% of their time on it.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Asana 2024: 54% (or 60%) of time goes to work about work.", "what_the_source_says": "Asana's 2024 report says 53% of time goes to busywork. The 54% in that report is the share of workers using AI at least monthly, and 60% comes from the 2019 and 2021 editions." }, { "claim": "Asana's 60% quoted as this year's figure.", "what_the_source_says": "60% is from the 2019 and 2021 editions. The latest figures are 53% (2024) and 55% (2025), under the new label busywork." } ], "citation": "EVY (2026). How much of the work day goes to coordinating work rather than doing it? The AI at Work Fact Book, F-02. https://evy.so/facts/time-on-work-about-work/ (last checked October 13, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-03", "url": "https://evy.so/facts/time-in-meetings/", "chapter": "Where the Week Goes", "question": "How many hours a week do people spend in meetings, and how much of it is wasted?", "answer": "Studies range from about 3 to 18 hours a week for the average office worker, and managers report about 22. Workers judge roughly a third to two thirds of their meeting time unnecessary or unproductive.", "range": { "low": 3, "high": 18, "unit": "hours a week in meetings", "display": "3–18 h a week in meetings for the average worker; managers about 22 h" }, "confidence": "medium", "confidence_reason": "Six primary studies measure hours, and they differ by a factor of six because they count different meetings, people and methods. Every figure on wasted time is self-reported.", "last_checked": "2026-10-13", "how_to_read": "The studies count different meetings and different people. ActivTrak only sees time in online tools on work computers, so it is a floor. Microsoft publishes only its heaviest quarter of Teams users. Otter.ai's 18 hours comes from a senior, long-hours group with a median 50-hour week, and likely includes calls and one-to-ones. Seniority matters most: managers of 4 or more people report 22.2 hours against 13.7 for everyone else. Doodle, Otter.ai and Atlassian sell scheduling, transcription or collaboration tools.", "sources": [ { "creator": "Doodle", "title": "The Doodle State of Meetings Report 2019", "year": 2019, "sample": "About 6,500 professionals in the UK, Germany and the US, plus data on 19 million meetings scheduled in Doodle", "method": "Survey with Nielsen plus scheduling data, 2018. Doodle sells meeting scheduling.", "figure": "3 hours a week in meetings, 2 of them considered pointless", "url": "https://assets.ctfassets.net/p24lh3qexxeo/axrPjsBSD1bLp2HYEqoij/d2f08c2aaf5a6ed80ee53b5ad7631494/Meeting_Report_2019.pdf", "quote": "The average professional spends three hours a week in meetings" }, { "creator": "ActivTrak Productivity Lab", "title": "Productivity Benchmarks Report 2025", "year": 2025, "sample": "218,900 employees at 777 companies using ActivTrak", "method": "Observed time in online meeting and chat tools on monitored work computers, 2022 to 2024. Leaves out in-person meetings and calls away from the computer.", "figure": "About 38 minutes a day in digital collaboration tools (derived from the report's sector comparison)", "url": "https://www.activtrak.com/blog/productivity-benchmarks/", "quote": "Collaboration time (49 mins) is 11 mins longer than average" }, { "creator": "David Deming, Katrine Løken, Alexander Willén and Yaling Xu", "title": "Meetings (NBER Working Paper 35706)", "year": 2026, "sample": "About 9,000 workers in Norway, linked to employer records", "method": "Survey in 2025, self-reported hours in bands", "figure": "Meetings take 12% of work hours, 4.7 hours a week", "url": "https://www.nber.org/papers/w35706", "quote": "consuming an average of 12 percent of work hours" }, { "creator": "Atlassian Teamwork Lab", "title": "The State of Teams 2022", "year": 2022, "sample": "1,710 knowledge workers in the US and Australia", "method": "Online survey, July 2022, self-reported", "figure": "About 5 hours a week for office-only teams, about 8 hours for hybrid and distributed teams", "url": "https://www.atlassian.com/blog/state-of-teams-2022", "quote": "office-only workers have roughly five hours of meetings in an average week" }, { "creator": "Microsoft", "title": "Will AI Fix Work? (2023 Work Trend Index)", "year": 2023, "sample": "Anonymized Microsoft 365 usage data, commercial customers", "method": "Observed Teams meeting time. Reports only the heaviest quarter of meeting users.", "figure": "7.5 hours a week for the heaviest 25% of Teams meeting users", "url": "https://www.microsoft.com/en-us/worklab/work-trend-index/will-ai-fix-work", "quote": "the heaviest meeting users (top 25%) spend 7.5 hours a week in meetings" }, { "creator": "Otter.ai with Steven G. Rogelberg (UNC Charlotte)", "title": "The Cost of Unnecessary Meeting Attendance", "year": 2022, "sample": "632 employees in 20+ industries, median 50-hour week", "method": "Voluntary online survey, summer 2022, self-reported. Otter.ai sells meeting transcription.", "figure": "18 hours a week in 17.7 meetings; non-managers 13.7 hours, managers of 4 or more people 22.2 hours", "url": "https://public.otter.ai/reports/The_Cost_of_Unnecessary_Meeting_Attendance.pdf", "quote": "On average, employees have 17.7 meetings (totaling 18 hours) per week." } ], "related_findings": [ { "question": "How much meeting time do workers consider wasted?", "answer": "Roughly 30 to 67 percent of it, by workers' own judgment. In the Otter.ai study, employees said they could skip about 30% of their meetings (5.7 of 18 hours). Doodle's respondents called 2 of their 3 weekly meeting hours pointless. Asana's 2024 survey puts unproductive meetings at 5 hours a week, double the 2019 level. Widely shared figures such as 71% of senior managers calling meetings unproductive (HBR, 2017) measure opinion about meetings and give no share of time.", "sources": [ { "creator": "Asana Work Innovation Lab", "title": "State of Work Innovation 2024", "year": 2024, "sample": "13,066 knowledge workers in six countries", "method": "Online surveys, February to August 2024, self-reported", "figure": "5 hours a week in unproductive meetings, double the August 2019 level; 9 hours in France and Germany", "url": "https://asana.com/resources/state-of-work-innovation", "quote": "doubled to 5 hours per week since August 2019" }, { "creator": "Leslie A. Perlow, Constance Noonan Hadley and Eunice Eun", "title": "Stop the Meeting Madness (Harvard Business Review)", "year": 2017, "sample": "182 senior managers across industries", "method": "Authors' survey of opinions", "figure": "71% said meetings are unproductive and inefficient; 65% said meetings keep them from their own work", "url": "https://hbr.org/2017/07/stop-the-meeting-madness", "quote": "71 percent said meetings are unproductive and inefficient" } ] }, { "question": "How much time goes to status meetings?", "answer": "About 4 hours a week for people who attend them, but only one study measures it, so treat this as indicative. In a 2016 Harris Poll survey for Clarizen, US workers who attend status meetings spend 4.1 hours a week in project status meetings and 3.9 hours in general ones, and those who prepare for them spend another 3.8 hours. Each average covers a different group (56 to 62 percent of respondents). In a 2015 Wrike survey, 46% said most or all of their meetings were just status updates. No study we found measures time spent writing or reading written status updates.", "confidence": "low", "sources": [ { "creator": "Clarizen, survey by The Harris Poll", "title": "Clarizen survey on status meetings", "year": 2016, "sample": "1,120 employed US adults (plus UK and Australia samples)", "method": "Online survey, January 2016, self-reported. Clarizen sells work management software.", "figure": "4.1 hours a week in project status meetings (61% attend), 3.9 hours in general status meetings (62%), 3.8 hours preparing (56%)", "url": "https://www.firmenpresse.de/pressrelease449502/clarizen-survey-says-employees-in-the-u-s-waste-up-to-30-percent-of-work-week-on-status-meetings.html", "quote": "spending 4.1 hours each week in these meetings" }, { "creator": "Wrike", "title": "2015 Work Management Survey", "year": 2015, "sample": "More than 1,400 office workers", "method": "Wrike's own survey, cited on its company blog. Wrike sells work management software.", "figure": "46% said most or all of their meetings were focused on status updates", "url": "https://www.wrike.com/blog/accurate-real-time-insights-with-one-click/", "quote": "most or all of their meetings were focused on just status updates" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Executives spend nearly 23 hours a week in meetings, up from under 10 in the 1960s.", "what_the_source_says": "Repeated from article to article without an original study we could find. Otter.ai and Steven Rogelberg's 2022 survey found 22.2 hours for managers of 4 or more people, which is close." }, { "claim": "Atlassian: 3 in 4 meetings are ineffective (\"72% of the time\").", "what_the_source_says": "The 72% averages six ratings, each the share of respondents who call meetings ineffective for one purpose, such as brainstorming. It does not count meetings." }, { "claim": "Clarizen: workers spend 11.8 hours a week, up to 30% of the week, on status meetings.", "what_the_source_says": "11.8 adds three averages that each cover a different group of respondents. The parts are 4.1, 3.9 and 3.8 hours, for people who attend or prepare for status meetings." }, { "claim": "The average employee spends 6 hours a week in scheduled meetings (MIT Sloan Management Review, 2007).", "what_the_source_says": "The article calls this a conservative estimate from the literature and names no underlying study." } ], "citation": "EVY (2026). How many hours a week do people spend in meetings, and how much of it is wasted? The AI at Work Fact Book, F-03. https://evy.so/facts/time-in-meetings/ (last checked October 13, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-04", "url": "https://evy.so/facts/time-to-resume-after-interruption/", "chapter": "Where the Week Goes", "question": "How long does it take to get back to a task after an interruption?", "answer": "Field studies that watched people at work found it takes about 20 to 26 minutes to return to an interrupted task, usually after handling about two other things first. The often quoted \"23 minutes\" comes from this research and counts that whole detour.", "range": { "low": 20, "high": 26, "unit": "minutes until back on the interrupted task", "display": "20–26 min until back on the interrupted task, observed in the field" }, "confidence": "medium", "confidence_reason": "Two independent research groups observed workers in the field and land at about 20 to 26 minutes. Both studies are from 2005 to 2007, the samples are small, and the groups define getting back slightly differently.", "last_checked": "2026-10-13", "how_to_read": "Three different things get called the cost of an interruption: how often attention breaks, how long until people are back on the task, and stress or mistakes measured in the lab. This range covers the second only. It is the elapsed time to return, which includes dealing with the interruption and doing other work first. The Iqbal and Horvitz range is our sum of the two phases they report. All three studies observed mostly US office workers.", "sources": [ { "creator": "Gloria Mark, Victor M. Gonzalez and Justin Harris, UC Irvine", "title": "No task left behind? Examining the nature of fragmented work (ACM CHI 2005)", "year": 2005, "sample": "24 information workers in two teams, over 700 hours of observation", "method": "Researchers shadowed each person for 3 days with second-by-second timing. Peer-reviewed.", "figure": "25 minutes 26 seconds to resume interrupted work, after an average of 2.26 other tasks", "url": "https://ics.uci.edu/~gmark/CHI2005.pdf", "quote": "it took an average length of time of 25 min. 26 sec" }, { "creator": "Gallup Business Journal", "title": "Too Many Interruptions at Work? (interview with Gloria Mark)", "year": 2006, "sample": "36 managers, analysts, developers, engineers and project leaders, shadowed 3 days each", "method": "The researcher's own account of her shadowing study, in an interview", "figure": "23 minutes 15 seconds to resume interrupted work, with about two tasks in between", "url": "https://news.gallup.com/businessjournal/23146/too-many-interruptions-work.aspx", "quote": "it was resumed, on average, in 23 minutes and 15 seconds" }, { "creator": "Shamsi T. Iqbal and Eric Horvitz, Microsoft Research", "title": "Disruption and recovery of computing tasks: field study, analysis, and directions (ACM CHI 2007)", "year": 2007, "sample": "27 computer users logged for two weeks", "method": "Logging software for windows, apps, email and chat alerts, plus interviews. Peer-reviewed.", "figure": "About 10 minutes on the diversion after an email or chat alert, then 10 to 15 minutes more to return to the task", "url": "https://erichorvitz.com/CHI_2007_Iqbal_Horvitz.pdf", "quote": "spent on average nearly 10 minutes on switches caused by alerts" } ], "related_findings": [ { "question": "How often are knowledge workers interrupted?", "answer": "Every few minutes. Microsoft's 2025 usage data counts a meeting, email or chat ping every 2 minutes during core hours for its busiest fifth of users, or 275 a day. In Gloria Mark's shadowing study, people spent about 3 minutes on a task before switching, and interrupted themselves about 44% of the time. A 2016 logging study found a median of 40 seconds on one screen before switching (mean 47 seconds).", "sources": [ { "creator": "Microsoft", "title": "Breaking down the infinite workday (2025 Work Trend Index)", "year": 2025, "sample": "Anonymized Microsoft 365 usage data, 28 days to February 2025, outside the EU; top 20% of users by ping volume", "method": "App usage data, observed. Counts incoming pings, which do not always break focus.", "figure": "Interrupted every 2 minutes during core work hours, 275 times a day", "url": "https://www.microsoft.com/en-us/worklab/work-trend-index/breaking-down-infinite-workday", "quote": "interrupted every 2 minutes by a meeting, email, or notification" }, { "creator": "Gloria Mark, Shamsi Iqbal, Mary Czerwinski, Paul Johns and Akane Sano", "title": "Neurotics Can't Focus: An in situ Study of Online Multitasking in the Workplace (ACM CHI 2016)", "year": 2016, "sample": "40 information workers at one US technology company", "method": "Window-logging software over two work weeks. Peer-reviewed.", "figure": "Median 40 seconds of focus on one screen; mean 47 seconds", "url": "https://ics.uci.edu/~gmark/Home_page/Publications_files/CHI%2016%20Multitasking%20and%20Focus.pdf", "quote": "The median duration of online screen focus was 40 seconds." } ] } ], "numbers_you_may_have_seen": [ { "claim": "It takes 23 minutes to refocus after an interruption.", "what_the_source_says": "The 23 minutes 15 seconds (Gloria Mark, in a 2006 Gallup interview) is the time until people returned to the interrupted work, after about two other tasks. It says nothing about how long concentration takes to come back." }, { "claim": "The 23 minutes comes from Mark, Gudith and Klocke, \"The Cost of Interrupted Work\" (2008).", "what_the_source_says": "That paper is a lab experiment on email tasks. Interrupted people finished faster but with more stress, and the paper contains no 23-minute figure." }, { "claim": "Workers are interrupted 275 times a day (Microsoft).", "what_the_source_says": "Microsoft's count covers its busiest 20% of users by ping volume and runs over 24 hours. It does not describe the typical worker." }, { "claim": "Attention spans fell from 150 seconds in 2004 to 47 seconds today.", "what_the_source_says": "The 47 seconds is in Mark and colleagues' 2016 paper. The earlier values come from talks and essays; we did not open the underlying papers, so only the 2016 figure is used here." } ], "citation": "EVY (2026). How long does it take to get back to a task after an interruption? The AI at Work Fact Book, F-04. https://evy.so/facts/time-to-resume-after-interruption/ (last checked October 13, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-05", "url": "https://evy.so/facts/time-on-email-and-chat/", "chapter": "Where the Week Goes", "question": "How much of the work week do knowledge workers spend on email and chat?", "answer": "Email alone takes 13 to 28 percent of the work week, depending on how it is measured. Microsoft's usage data adds Teams chat at 19 percent of measured time in its apps.", "range": { "low": 13, "high": 28, "unit": "% of the work week on email", "display": "13–28% of the work week on email alone" }, "confidence": "medium", "confidence_reason": "Five primary studies, but they split into two groups (about 13 to 15 percent and about 26 to 29 percent) because they use different denominators and definitions of email time.", "last_checked": "2026-10-13", "how_to_read": "The studies fall into two groups. Workfront's self-reports and Microsoft's app data land at 13 to 15 percent; McKinsey's model, Adobe's self-reports and Microsoft Research's logs land at 26 to 29 percent. The denominators differ: the whole week, time inside Microsoft apps, or an assumed 40-hour week. Adobe's and Microsoft Research's percentages are our conversion at 40 hours, so they read high for people who work longer weeks. Microsoft Research counts whole email sessions, which is broader than Microsoft's count of deliberate actions.", "sources": [ { "creator": "Workfront, survey by Regina Corso Consulting", "title": "State of Work 2020", "year": 2019, "sample": "3,750 employees at companies with 500 or more staff in the US, UK, Germany and the Netherlands", "method": "Online survey, July 2019; people split their week into categories adding up to 100%", "figure": "Email takes 15% of the week (US, UK), 14% (Netherlands), 13% (Germany)", "url": "https://business.adobe.com/products/workfront.html", "archive_url": "https://web.archive.org/web/20201003135606/https://www.workfront.com/sites/default/files/resource/file_pdf/2019-09/sow-report-2020.pdf", "quote": "Best guess for what percentage of your work week is taken up by each" }, { "creator": "Microsoft", "title": "Will AI Fix Work? (2023 Work Trend Index)", "year": 2023, "sample": "Microsoft 365 usage data from commercial customers, 28 days to March 2023", "method": "App usage data, observed. Share of time inside Microsoft 365 apps, which is not the whole week.", "figure": "Email 15%, Teams chat 19% and Teams meetings 23% of measured time", "url": "https://www.microsoft.com/en-us/worklab/work-trend-index/will-ai-fix-work", "quote": "15% in email, forming 57% of the time spent communicating" }, { "creator": "Adobe", "title": "Adobe Email Usage Study 2019", "year": 2019, "sample": "About 1,000 office workers per country in the US, UK, Germany, France, Australia, India and Japan", "method": "Online survey, July to August 2019, self-reported minutes checking work email", "figure": "209 minutes per weekday on work email in the US (Germany 173, UK 207, France 216)", "url": "https://www.slideshare.net/slideshow/2019-adobe-email-report/179705093", "archive_url": "https://web.archive.org/web/20250129020143/https://www.slideshare.net/slideshow/2019-adobe-email-report/179705093", "quote": "number of minutes you spend each weekday checking your email" }, { "creator": "Dillon, Jaffe, Immorlica and Stanton (Microsoft Research and Harvard Business School)", "title": "Shifting Work Patterns with Generative AI (NBER Working Paper 33795)", "year": 2025, "sample": "7,137 knowledge workers at 66 firms", "method": "Field experiment using Microsoft 365 usage data, 2023 to 2024; this is the baseline before the AI tool", "figure": "11.7 hours a week reading and responding to email", "url": "https://arxiv.org/abs/2504.11436", "quote": "the average worker spent 11.7 hours per week reading and responding to emails" }, { "creator": "McKinsey Global Institute, using IDC survey data", "title": "The social economy: Unlocking value and productivity through social technologies", "year": 2012, "sample": "Managers and professionals in IDC's 2009 survey; sample size not stated", "method": "Modeled estimate from McKinsey and IDC data", "figure": "28% of work time reading, writing or answering email", "url": "https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-social-economy", "archive_url": "https://web.archive.org/web/20260710105837/https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-social-economy", "quote": "This includes 28 percent of work time reading, writing, or responding to e-mail" } ], "related_findings": [ { "question": "How much time goes to chat at work?", "answer": "One source measures it. In Microsoft's 2023 usage data, Teams chat takes 19% of measured time in Microsoft 365 apps, against 15% for email and 23% for Teams meetings. Email and chat together are 34% of that measured time. The heaviest quarter of email users spend 8.8 hours a week on email.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Adobe: people spend 5 hours a day on email.", "what_the_source_says": "That adds work email (209 minutes a weekday, US) to personal email (143 minutes). Work email alone is about 3.5 hours a day, self-reported." }, { "claim": "McKinsey: email takes 13 hours a week.", "what_the_source_says": "The report gives 28 percent of work time. We could not find the 13-hour conversion in the report itself." }, { "claim": "Slack: 25% of workers spend too much time on email.", "what_the_source_says": "This is an opinion on whether email takes too much time. It gives no hours." } ], "citation": "EVY (2026). How much of the work week do knowledge workers spend on email and chat? The AI at Work Fact Book, F-05. https://evy.so/facts/time-on-email-and-chat/ (last checked October 13, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-06", "url": "https://evy.so/facts/time-lost-switching-apps/", "chapter": "Where the Week Goes", "question": "How much time do people lose switching between apps at work?", "answer": "About 3 to 4 hours a week goes to getting back on track after switching apps. Logging software (just under 4 hours) and self-reports (36 minutes a day) agree within about an hour.", "range": { "low": 3, "high": 4, "unit": "hours a week lost after switching apps", "display": "3–4 h a week lost getting back on track after switching apps" }, "confidence": "medium", "confidence_reason": "Two independent studies, one logged and one self-reported, agree within about an hour. Counts of switches per day differ by a factor of 50 between sources, so they are kept out of the range.", "last_checked": "2026-10-13", "how_to_read": "The HBR figure comes from logging software at three Fortune 500 companies, mostly in operations-style teams, so it may run high for other roles. Qatalog's is self-reported; 36 minutes a day is about 3 hours over a 5-day week. Counts of switches and counts of apps measure different things, so they are shown separately below and kept out of the range.", "sources": [ { "creator": "Rohan Narayana Murty, Sandeep Dadlani and Rajath B. Das (Soroco)", "title": "How Much Time and Energy Do We Waste Toggling Between Applications? (Harvard Business Review)", "year": 2022, "sample": "137 users in 20 teams at three Fortune 500 companies", "method": "Logging software for up to five weeks, observed. Soroco sells work-pattern software.", "figure": "About 1,200 toggles a day; just under 4 hours a week reorienting, about 9% of time at work", "url": "https://hbr.org/2022/08/how-much-time-and-energy-do-we-waste-toggling-between-applications", "quote": "just under four hours a week reorienting themselves after toggling" }, { "creator": "Qatalog with Cornell University's Ellis Idea Lab", "title": "Workgeist Report '21", "year": 2021, "sample": "Three surveys of about 1,000 remote workers each, US and UK", "method": "Online surveys, March 2021, self-reported. Qatalog sells a work hub.", "figure": "36 minutes a day switching between apps; 9.5 minutes to get back into a good workflow", "url": "https://qatalog.com/", "archive_url": "https://web.archive.org/web/20210624191022/https://assets.qatalog.com/language.work/qatalog-2021-workgeist-report.pdf", "quote": "taking 9 and a half minutes on average to get back into a good workflow" } ], "related_findings": [ { "question": "How many times a day do people switch between apps?", "answer": "It depends on who counts. People report about 25 switches a day between 10 apps (Asana, 2021). Logging software records far more: 391 to 661 window switches a day (Mark and colleagues, 2014) and about 1,200 toggles between apps and websites (Harvard Business Review, 2022). Self-reported counts are likely too low.", "sources": [ { "creator": "Asana, survey by Sapio Research", "title": "Anatomy of Work Index 2021", "year": 2021, "sample": "13,123 knowledge workers in seven countries", "method": "Online survey, October 2020, self-reported", "figure": "10 apps and 25 switches between them a day (US: 13 apps, 30 switches)", "url": "https://asana.com/resources/anatomy-of-work-index", "archive_url": "https://web.archive.org/web/20210301155022/https://resources.asana.com/rs/784-XZD-582/images/PDF-FY21-Global-EN-Anatomy%20of%20Work%20Report.pdf", "quote": "on average people switch between 10 apps 25 times per day" }, { "creator": "Gloria Mark, Shamsi Iqbal, Mary Czerwinski and Paul Johns", "title": "Bored Mondays and Focused Afternoons (ACM CHI 2014)", "year": 2014, "sample": "32 information workers at one US company, 5 days each", "method": "Logging software plus experience sampling, observed. Peer-reviewed.", "figure": "661 window switches a day on Mondays, 391 on Fridays", "url": "https://dl.acm.org/doi/abs/10.1145/2556288.2557204", "archive_url": "https://web.archive.org/web/20240705042331/https://dl.acm.org/doi/abs/10.1145/2556288.2557204" } ] }, { "question": "How many apps does a knowledge worker use in a day?", "answer": "About 9 to 10, self-reported: 10 in Asana's 2021 survey and 9 in 2022, with 13 in the US. Companies deploy far more: Okta's customers average 101 apps each, and 74 in Europe, the Middle East and Africa.", "sources": [ { "creator": "Asana, survey by GWI", "title": "Anatomy of Work Index 2022", "year": 2022, "sample": "10,624 knowledge workers in seven countries", "method": "Online survey, October 2021, self-reported", "figure": "9 apps a day, down from 10", "url": "https://www.businesswire.com/news/home/20220405005399/en/Asana-Anatomy-of-Work-Index-2022-Work-About-Work-Hampering-Organizational-Agility", "archive_url": "https://web.archive.org/web/20260411014513/https://www.businesswire.com/news/home/20220405005399/en/Asana-Anatomy-of-Work-Index-2022-Work-About-Work-Hampering-Organizational-Agility", "quote": "workers are using slightly fewer apps per day (9) than last year (10)" }, { "creator": "Okta", "title": "Businesses at Work 2025", "year": 2025, "sample": "Anonymized data from thousands of Okta customers", "method": "Apps connected per company in Okta's network, 2024 data. A company-level count.", "figure": "101 apps per company on average; 74 in Europe, the Middle East and Africa", "url": "https://www.okta.com/blog/2025/03/businesses-at-work-2025", "quote": "The average number of apps each company uses reached 101 this year" } ] } ], "numbers_you_may_have_seen": [ { "claim": "It takes 23 minutes 15 seconds to refocus after switching apps.", "what_the_source_says": "That figure comes from research on interruptions, and it measures the time until people return to interrupted work. See F-04." }, { "claim": "The average person toggles more than 3,600 times a day.", "what_the_source_says": "We found no study behind it. The largest logged count we found is about 1,200 toggles a day (HBR, 2022)." }, { "claim": "Slack: workers switch between 10 or more apps a day and lose nearly 100 minutes.", "what_the_source_says": "It appears on a Slack product page citing unnamed research. We could not find the study." } ], "citation": "EVY (2026). How much time do people lose switching between apps at work? The AI at Work Fact Book, F-06. https://evy.so/facts/time-lost-switching-apps/ (last checked October 13, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-07", "url": "https://evy.so/facts/time-spent-duplicating-work/", "chapter": "Where the Week Goes", "question": "How much time do people spend redoing work that already exists?", "answer": "Workers report losing about 4.6 to 5.7 hours a week to duplicated work, or 10 to 14 percent of a 40-hour week. Every figure is self-reported, and two of the three come from the same publisher.", "range": { "low": 4.6, "high": 5.7, "unit": "hours a week on duplicated work", "display": "4.6–5.7 h a week on duplicated work, 10 to 14% of a 40-hour week" }, "confidence": "medium", "confidence_reason": "Three reports agree closely, but two come from Asana with the same method, so there are only two independent creators, and every figure is self-reported in a vendor survey.", "last_checked": "2026-10-13", "how_to_read": "All three figures are people's own estimates in surveys run for vendors, mostly from 2018 to 2020. Panopto's average comes from a lopsided spread: 21% report zero hours and 14% report 10 or more. Asana's 2021 hours are our conversion: 236 hours a year is 4.5 hours a week, and 13% of a 40-hour week is 5.2. No newer independent measure was found.", "sources": [ { "creator": "Asana, survey by Sapio Research", "title": "Anatomy of Work Index 2019", "year": 2019, "sample": "10,223 knowledge workers in Australia, New Zealand, Germany, Japan, the UK and the US", "method": "Online survey, August to September 2019, self-reported. Asana sells work management software.", "figure": "4 hours 38 minutes a week duplicating work, more than 10% of the week", "url": "https://resources.asana.com/rs/784-XZD-582/images/Anatomy-of-Work-Index.pdf", "quote": "waste more than 10% of their time duplicating efforts" }, { "creator": "Asana, survey by Sapio Research", "title": "Anatomy of Work Index 2021", "year": 2021, "sample": "13,123 knowledge workers in seven countries", "method": "Online survey, October 2020, self-reported", "figure": "13% of time on work that has already been done, 236 hours a year", "url": "https://asana.com/resources/anatomy-of-work-index", "archive_url": "https://web.archive.org/web/20210301155022/https://resources.asana.com/rs/784-XZD-582/images/PDF-FY21-Global-EN-Anatomy%20of%20Work%20Report.pdf", "quote": "Teams are spending 13% of their time on work that's already been completed" }, { "creator": "Panopto", "title": "Workplace Knowledge and Productivity Report", "year": 2018, "sample": "1,001 US employees with at least 5 years of work experience", "method": "Online survey, self-reported. Panopto sells video knowledge-sharing software.", "figure": "5.68 hours a week reinventing the wheel and duplicating others' work", "url": "https://assets.panopto.com/asset/fd3223fa-08dd-46ba-94ad-80d29a787d12/Social-Learning-Workplace-Knowledge-Panopto-White-Paper.pdf", "quote": "nearly 6 hours each week \"reinventing the wheel\" and duplicating other people's work" } ], "related_findings": [ { "question": "Which countries lose the most time to duplicated work?", "answer": "In Asana's 2019 survey, Germany reported the most at 5 hours 9 minutes a week, followed by Australia and New Zealand (5 h 7 min), the UK (5 h 5 min) and the US (4 h 55 min). Japan reported the least at 2 hours 56 minutes.", "sources": [] }, { "question": "How common is duplicated work across teams?", "answer": "Half of knowledge workers (50%) have worked on a project and only later found out that another team was doing the same thing, according to Atlassian's 2024 survey of 5,000 knowledge workers.", "sources": [ { "creator": "Atlassian Teamwork Lab", "title": "The State of Teams 2024", "year": 2024, "sample": "5,000 knowledge workers and 100 Fortune 500 executives", "method": "Online survey. Measures how many people have experienced it, with no hours.", "figure": "50% have worked on a project another team was also doing", "url": "https://www.atlassian.com/blog/state-of-teams-2024", "quote": "only later found out that another team was working on the same thing" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Panopto: workers lose 5.3 hours a week waiting for information or recreating existing knowledge.", "what_the_source_says": "In the report, 5.31 hours is time spent waiting for colleagues' knowledge. Duplicating work is a separate 5.68 hours, and the report says the two overlap and cannot be added." }, { "claim": "Asana: 209 hours a year on duplicated work, 103 hours in unnecessary meetings, 352 hours talking about work.", "what_the_source_says": "These blog figures mix editions. 209 hours is the 2019 duplication figure (2021 says 236), and we found the 352 hours in neither the 2019 nor the 2021 report." }, { "claim": "IDC: reworking information takes 15% of knowledge workers' time.", "what_the_source_says": "The 15% is an assumption inside a cost model of a hypothetical 1,000-person company (Feldman, KMWorld, 2004). No one measured it." } ], "citation": "EVY (2026). How much time do people spend redoing work that already exists? The AI at Work Fact Book, F-07. https://evy.so/facts/time-spent-duplicating-work/ (last checked October 13, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-08", "url": "https://evy.so/facts/time-saved-by-ai-at-work/", "chapter": "What AI Saves", "question": "How much time does AI save knowledge workers?", "answer": "Workers who use generative AI say it saves them about 3 to 5.4 percent of their work hours, roughly 1 to 2 hours of a 40-hour week. The one large trial that measured time found users spent 1.4 to 2 fewer hours a week on email, with no measurable change in time in meetings or writing documents.", "range": { "low": 3, "high": 5.4, "unit": "% of work hours saved, self-reported by AI users", "display": "3–5.4% of work hours, by the estimate of people who use AI (about 1 to 2 hours a week)" }, "spread": { "low": 1.2, "high": 8.75, "unit": "hours a week" }, "confidence": "medium", "confidence_reason": "Three independent creators with different surveys (a US national panel, a Danish survey linked to government records, and the UK civil service) agree on the range. All of them are self-reports, and the only large measured trial covers email time only.", "last_checked": "2026-10-14", "how_to_read": "Every figure here is a worker's own estimate of how much longer the work would have taken without AI. The surveys turn answers into numbers differently and ask different people, from national panels to a vendor's own customers. Figures for AI users run three to four times higher than figures across all workers, because in any given week most workers do not use AI. Hours assume a 40-hour week. Microsoft, Atlassian and Workday sell AI products.", "sources": [ { "creator": "Alexander Bick (St. Louis Fed), Adam Blandin (Vanderbilt) and David Deming (Harvard)", "title": "The Rapid Adoption of Generative AI (NBER Working Paper 32966)", "year": 2025, "sample": "More than 10,000 US adults aged 18 to 64 in the Real-Time Population Survey; time question asked in November 2024", "method": "Nationally representative online survey. Asks how many extra hours last week's work would have taken without AI.", "figure": "5.4% of work hours among people who used generative AI for work, about 2.2 hours of a 40-hour week; 1.4% across all workers", "url": "https://www.nber.org/papers/w32966", "quote": "We estimate a mean time savings of 5.4 percent among all genAI work users," }, { "creator": "Anders Humlum (Chicago Booth) and Emilie Vestergaard (University of Copenhagen), with Statistics Denmark", "title": "Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI (NBER Working Paper 33777)", "year": 2026, "sample": "About 25,000 workers at about 7,000 workplaces in 11 occupations exposed to AI chatbots", "method": "Surveys linked to Danish payroll records. Time saved is self-reported in bands; earnings and paid hours come from the records. First circulated as \"Large Language Models, Small Labor Market Effects\".", "figure": "About 3% of work hours for people who use AI chatbots (0.7% for teachers up to 6.1% for marketing staff); no change in earnings or paid hours in the records", "url": "https://www.nber.org/papers/w33777", "quote": "On average, adopters in our sample report savings of about 3% of their work hours." }, { "creator": "UK Government Digital Service", "title": "Microsoft 365 Copilot Experiment: Cross-Government Findings Report", "year": 2025, "sample": "7,115 survey responses from a trial with 20,000 civil servants", "method": "End-of-trial survey, October to December 2024, with answers in time bands averaged at their midpoints. No control group for the time question.", "figure": "26 minutes a day saved on average; 17% noticed no clear time saving", "url": "https://assets.publishing.service.gov.uk/media/683db42bd23a62e5d32680d0/M365_Copilot_Experiment_Findings_Report.pdf", "quote": "Trial participants saved an average of 26 minutes a day when using M365 Copilot." }, { "creator": "Microsoft WorkLab", "title": "AI Data Drop: The 11 by 11 Tipping Point", "year": 2024, "sample": "1,300 Microsoft 365 Copilot users, including Microsoft employees, after at least three weeks of use", "method": "Self-reported daily time saved, in answer bands. Microsoft sells Copilot.", "figure": "14 minutes a day saved on average; 30 minutes for the most efficient users", "url": "https://www.microsoft.com/en-us/worklab/ai-data-drop-the-11-by-11-tipping-point", "quote": "the average person saved 14 minutes a day, or nearly five hours each month" }, { "creator": "Atlassian Teamwork Lab", "title": "AI Collaboration Report", "year": 2024, "sample": "About 5,000 knowledge workers in Australia, the US, India, Germany and France", "method": "Online survey, self-estimated time saved, grouped by how advanced people's AI use is. Atlassian sells AI-enabled software.", "figure": "53 minutes a day for simple AI users, 105 minutes for the most advanced", "url": "https://www.atlassian.com/blog/ai-at-work/ai-collaboration-report", "quote": "We asked people to estimate the amount of time that AI saves them" }, { "creator": "Workday, survey by Hanover Research", "title": "Beyond Productivity: Measuring the Real Value of AI", "year": 2026, "sample": "3,200 full-time employees who use AI, at organizations with $100 million or more in revenue", "method": "Online survey, November 2025, self-reported. Read in Workday's press release; the full report is gated. Workday sells AI products.", "figure": "85% say they save 1 to 7 hours a week, and that nearly 40% of the savings is lost to rework", "url": "https://newsroom.workday.com/2026-01-14-New-Workday-Research-Companies-Are-Leaving-AI-Gains-on-the-Table", "quote": "85% of employees report saving one to seven hours per week using AI" } ], "related_findings": [ { "question": "How much of all work hours does AI save across the economy?", "answer": "1.4 to 2.2 percent of all US work hours, counting the many workers who do not use AI. The share rose from 1.41% in late 2024 to 2.17% in the second quarter of 2026, as the share of employed adults who used AI for work in a given week grew from 28% to 39%. Both figures are self-reported, from the St. Louis Fed's survey series.", "sources": [ { "creator": "Federal Reserve Bank of St. Louis, data series by Bick, Blandin and Deming", "title": "Does generative AI save time at work? (FRED Blog, series RPSGENAITSALL)", "year": 2026, "sample": "Employed US adults aged 18 to 64, quarterly survey waves", "method": "Same self-reported question as the NBER paper, with non-users counted as zero", "figure": "1.41% of all US work hours saved (Q4 2024) rising to 2.17% (Q2 2026)", "url": "https://fred.stlouisfed.org/blog/2026/08/does-generative-ai-save-time-at-work/", "quote": "the share of work hours saved thanks to AI assistance grew from 1.6% to 2.2%." } ] }, { "question": "What does measured data show about time saved?", "answer": "In a randomized trial of Microsoft 365 Copilot with 7,137 workers at 66 firms, people who used it spent about 2 fewer hours a week on email (1.4 hours averaged over everyone offered the tool), out of about 11.7. Time in Teams meetings and in Word did not change measurably, and they replied to as many email threads and finished as many documents. In Denmark, payroll records show no change in paid hours or earnings, which fits saved time going into other work.", "confidence": "low", "sources": [ { "creator": "Dillon, Jaffe and Immorlica (Microsoft Research) and Stanton (Harvard Business School)", "title": "Shifting Work Patterns with Generative AI (NBER Working Paper 33795)", "year": 2025, "sample": "7,137 knowledge workers at 66 large firms", "method": "Randomized field experiment, 2023 to 2024, timed with Microsoft 365 usage data. Most authors work at Microsoft.", "figure": "1.4 fewer hours a week on email for everyone offered Copilot (12%), about 2 fewer for those who used it (17%); no significant change in meeting or document time", "url": "https://www.nber.org/papers/w33795", "quote": "who used this tool spent two fewer hours on email each week" } ] }, { "question": "Are people's own estimates of AI time savings accurate?", "answer": "Often not, and they miss in both directions. In a Microsoft lab test, people guessed AI saved them 36 minutes when the measured saving was 12. In METR's 2025 trial, experienced developers felt 20% faster with AI but took 19% longer. In a 2022 GitHub Copilot test, developers guessed a 35% gain when the measured one was 55.8%.", "sources": [ { "creator": "Microsoft Research", "title": "Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity (MSR-TR-2023-43)", "year": 2023, "sample": "Several lab studies and an early-access survey", "method": "Lab tasks timed and compared with participants' own estimates. Tasks were chosen because AI was likely to help.", "figure": "Participants guessed 36 minutes saved; the measured saving was 12 minutes", "url": "https://www.microsoft.com/en-us/research/wp-content/uploads/2023/12/AI-and-Productivity-Report-First-Edition.pdf", "quote": "They guessed 36 minutes on average, when actual time savings were 12 minutes" }, { "creator": "Joel Becker, Nate Rush, Beth Barnes and David Rein (METR)", "title": "Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity", "year": 2025, "sample": "16 experienced open-source developers, 246 tasks", "method": "Randomized trial at the task level, compared with developers' own estimates afterwards", "figure": "Tasks took 19% longer with AI; developers believed they were 20% faster", "url": "https://arxiv.org/abs/2507.09089", "quote": "we find that allowing AI actually increases completion time by 19%" }, { "creator": "Sida Peng (Microsoft Research), Eirini Kalliamvakou and Peter Cihon (GitHub), Mert Demirer (MIT Sloan)", "title": "The Impact of AI on Developer Productivity: Evidence from GitHub Copilot", "year": 2023, "sample": "95 freelance developers recruited on Upwork", "method": "Controlled experiment, 2022, with an exit survey", "figure": "Developers estimated a 35% gain; the measured time saving was 55.8%", "url": "https://arxiv.org/abs/2302.06590", "quote": "participants in both treated and control groups estimated a 35% increase in productivity" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Generative AI saves 5.4% of all work hours.", "what_the_source_says": "5.4% is the average among people who used AI for work. Across all workers it was 1.4% in November 2024 and 2.2% by mid-2026." }, { "claim": "Danish study: AI's measured time savings are only 2.8%.", "what_the_source_says": "The 2.8% (about 3% in the 2026 revision) is what workers report in a survey. What the authors measure in payroll records is earnings and paid hours, where they find no change." }, { "claim": "Thomson Reuters: AI saves professionals 5 hours a week.", "what_the_source_says": "This is a forecast. Respondents predicted AI would save them 5 hours a week within the next year (4 hours in the 2024 edition)." }, { "claim": "Microsoft: Copilot saves 11 minutes a day.", "what_the_source_says": "In Microsoft's survey, 11 minutes a day is the point at which users start to feel value. The average reported saving was 14 minutes." }, { "claim": "Microsoft Work Trend Index 2024: AI saves workers time, 90% say.", "what_the_source_says": "90% agree AI helps them save time. The report gives no amount of time saved." }, { "claim": "Slack: daily AI users are 64% more productive.", "what_the_source_says": "Slack's 2025 survey found daily users 64% more likely to rate their productivity \"very good\". It is a gap in self-ratings, with no time or output measured." } ], "citation": "EVY (2026). How much time does AI save knowledge workers? The AI at Work Fact Book, F-08. https://evy.so/facts/time-saved-by-ai-at-work/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-09", "url": "https://evy.so/facts/ai-writing-speed-and-quality/", "chapter": "What AI Saves", "question": "How much faster do people finish writing tasks with AI, and is the work better?", "answer": "In controlled experiments, professionals using ChatGPT or GPT-4 finished defined writing and consulting tasks 25 to 40 percent faster, and graders rated the work 18 to 34 percent better. In a six-month field trial of everyday work, time spent writing documents did not change measurably.", "range": { "low": 25, "high": 40, "unit": "% less time on a defined writing or consulting task", "display": "25–40% less time on a defined writing or consulting task, with quality up 18 to 34%" }, "confidence": "medium", "confidence_reason": "Two independent teams with different designs agree on direction and roughly on size. Both time one-off tasks chosen to suit the AI, and the one long-run field trial finds no measurable change in document time.", "last_checked": "2026-10-14", "how_to_read": "Both experiments time one well-defined task, chosen to suit the AI, in a single session. Noy and Zhang's task took people without AI about 27 minutes; the BCG tasks were longer, multi-part consulting exercises. Quality was graded on different scales (1 to 7 and 1 to 10). The six-month field trial found no change in time in Word, though its authors say too few people used Word regularly to detect small effects.", "sources": [ { "creator": "Shakked Noy and Whitney Zhang (MIT)", "title": "Experimental evidence on the productivity effects of generative artificial intelligence (Science)", "year": 2023, "sample": "453 college-educated professionals: marketers, grant writers, consultants, data analysts, HR professionals and managers", "method": "Preregistered online randomized experiment on a 20 to 30 minute writing task, graded blind by people in the same occupation. Minute figures from the authors' MIT working paper.", "figure": "40% less time and 18% higher quality; in the working paper, 27 minutes without ChatGPT and 17 with it", "url": "https://www.science.org/doi/10.1126/science.adh2586", "quote": "The average time taken decreased by 40% and output quality rose by 18%." }, { "creator": "Fabrizio Dell'Acqua, Ethan Mollick, Karim R. Lakhani and colleagues (Harvard Business School, Wharton, MIT, Warwick, Boston Consulting Group)", "title": "Navigating the Jagged Technological Frontier (Organization Science)", "year": 2026, "sample": "758 BCG consultants, about 7% of its individual-contributor consultants", "method": "Preregistered randomized experiment on 18 realistic consulting tasks, graded by humans", "figure": "25.1% faster on average (22.5% and 27.6% in the two AI groups), 12.2% more tasks done, quality up 29.9% to 33.9%", "url": "https://doi.org/10.1287/orsc.2025.21838", "quote": "completing 12.2% more tasks and completing them 25.1% more quickly on average" }, { "creator": "Dillon, Jaffe and Immorlica (Microsoft Research) and Stanton (Harvard Business School)", "title": "Shifting Work Patterns with Generative AI (NBER Working Paper 33795)", "year": 2025, "sample": "7,137 knowledge workers at 66 large firms", "method": "Randomized field experiment over six months, timed with Microsoft 365 usage data", "figure": "No significant change in time spent writing in Word, and the same number of documents completed", "url": "https://www.nber.org/papers/w33795", "quote": "no significant average changes in total time spent in video meetings or writing documents" } ], "related_findings": [ { "question": "Is writing done with AI better?", "answer": "Graders rated it higher in both experiments: 18% higher in Noy and Zhang's study, graded blind by professionals in the same occupation, and 29.9% to 33.9% higher in the BCG study, graded by humans (about half that when GPT-4 did the grading). In Noy and Zhang's study, 68% of people with ChatGPT handed in its first draft without editing it.", "sources": [] }, { "question": "What happens on tasks the AI handles badly?", "answer": "The gain can turn into a loss. On a business problem chosen so that GPT-4 would give a plausible wrong answer, BCG consultants without AI were right 84.5% of the time, against 60% and 70.6% in the two AI groups, even though the AI groups spent less time on it. F-13 covers this in more detail.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "ChatGPT makes workers 40% more productive (Noy and Zhang).", "what_the_source_says": "The study found 40% less time and 18% higher quality, on one 20 to 30 minute writing task. A 40% cut in time is a different number from a 40% rise in output." }, { "claim": "AI raised BCG consultants' quality by more than 40%.", "what_the_source_says": "That comes from the 2023 working paper. The peer-reviewed 2026 version reports human-graded gains of 29.9% to 33.9%." }, { "claim": "Consultants using AI were 19% less likely to be correct.", "what_the_source_says": "The paper's tables give 84.5% correct without AI and 60% and 70.6% with it: a drop of 14 to 25 percentage points, 19 on average, on one task chosen to sit outside the AI's abilities." } ], "citation": "EVY (2026). How much faster do people finish writing tasks with AI, and is the work better? The AI at Work Fact Book, F-09. https://evy.so/facts/ai-writing-speed-and-quality/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-10", "url": "https://evy.so/facts/ai-customer-support-productivity/", "chapter": "What AI Saves", "question": "How much more do customer support agents get done with AI?", "answer": "In the largest real-world study, chat agents at a Fortune 500 software firm resolved 14 to 15 percent more issues per hour with an AI assistant, and the least skilled gained 30 to 36 percent. A larger randomized trial at Alibaba found much smaller speed gains, with chats 1 to 8 percent faster.", "range": { "low": 14, "high": 15, "unit": "% more issues resolved per hour", "display": "14–15% more issues resolved per hour, in one firm's study" }, "spread": { "low": 1.1, "high": 15.2, "unit": "% faster or more output" }, "confidence": "low", "confidence_reason": "The 14 to 15 percent comes from a single study at a single firm, in two versions of the same paper. The only other large field experiment, at Alibaba, measures different things and finds much smaller speed gains.", "last_checked": "2026-10-14", "how_to_read": "The two studies measure different things. The software firm's figure counts issues resolved per hour, which captures both faster chats and handling several chats at once, with 2020 to 2021 data and a GPT-3-era tool. The Alibaba trial measures the length of single chats over four weeks, among new agents only, with an assistant that helps only at the start of each chat. They agree on who gains most and disagree on how much overall.", "sources": [ { "creator": "Erik Brynjolfsson (Stanford), Danielle Li and Lindsey Raymond (MIT)", "title": "Generative AI at Work (Quarterly Journal of Economics)", "year": 2025, "sample": "5,172 chat support agents at one Fortune 500 software firm, mostly in the Philippines, 3 million chats", "method": "Staggered rollout of a GPT-3-based reply assistant, 2020 to 2021, compared before and after with the firm's own records. The 2023 NBER version gives 13.8%.", "figure": "15.2% more issues resolved per hour; handle time down 8.5%; customer satisfaction unchanged", "url": "https://doi.org/10.1093/qje/qjae044", "quote": "increases worker productivity, as measured by issues resolved per hour, by 15% on average" }, { "creator": "Xiao Ni, Yiwei Wang, Tianjun Feng, Lauren Xiaoyuan Lu, Yitong Wang and Congyi Zhou (Fudan, Zhejiang University, Dartmouth Tuck, Alibaba Group)", "title": "Generative AI in Action: Field Experimental Evidence from Alibaba's Customer Service Operations", "year": 2026, "sample": "5,940 new agents with under a year of tenure, about 2.56 million chats on Taobao, China", "method": "Four-week randomized trial run by Alibaba, January to February 2024. The assistant drafts a diagnosis and solution at the start of each chat. One author works at Alibaba.", "figure": "Issues identified 8.2% faster and chats 1.1% shorter; dissatisfaction down 3.4%", "url": "https://arxiv.org/abs/2603.29888", "quote": "reduced issue identification time and chat duration by 8.2% and 1.1%, respectively" } ], "related_findings": [ { "question": "Which support agents gain the most from AI?", "answer": "The weakest. At the software firm, less skilled and less experienced agents gained 30% and the lowest-skilled fifth 36%, while the most skilled saw no significant change and their quality slipped slightly. At Alibaba, customer ratings for the lowest-performing fifth of agents rose 0.81 points on a 5-point scale and fell 0.28 points for the top fifth. F-12 compares this pattern across studies.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "AI makes support agents 14% more productive, and novices 34% more.", "what_the_source_says": "Those are the 2023 working-paper figures. The peer-reviewed 2025 version says 15% on average, 30% for less skilled and less experienced agents, and 36% for the lowest-skilled fifth." }, { "claim": "Klarna's AI assistant does the work of 700 agents.", "what_the_source_says": "Klarna's 2024 press release describes a chatbot answering chats on its own. It gives no method and says nothing about how productive human agents are with AI." } ], "citation": "EVY (2026). How much more do customer support agents get done with AI? The AI at Work Fact Book, F-10. https://evy.so/facts/ai-customer-support-productivity/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-11", "url": "https://evy.so/facts/ai-coding-speed/", "chapter": "What AI Saves", "question": "How much faster do developers code with AI assistants?", "answer": "Randomized trials inside companies find gains of about 21 to 26 percent. Across all studies the results run from 19 percent slower, for experienced developers in their own mature codebases, to 56 percent faster on one simple lab task, so the evidence conflicts.", "range": { "low": 21, "high": 26, "unit": "% faster, or more tasks done, in company trials", "display": "21–26% faster, or more tasks done, in randomized trials inside companies" }, "spread": { "low": -19, "high": 56, "unit": "% faster (negative means slower)" }, "confidence": "medium", "confidence_reason": "Five randomized studies from four independent groups agree that the effect depends on the task and the developer. The two company estimates are close but have wide margins of error and measure different things, and the studies disagree on the sign for experienced developers in familiar codebases.", "last_checked": "2026-10-14", "how_to_read": "The studies measure different things. Peng and colleagues and Google time one assigned task; the three-company trials count pull requests finished per week over months; METR times real tasks that experienced developers picked in code they know well. The developers differ, from freelancers to senior open-source maintainers, and so do the tools, from 2022 autocomplete to early-2025 Cursor with Claude. Google and Microsoft evaluated their own tools.", "sources": [ { "creator": "Sida Peng (Microsoft Research), Eirini Kalliamvakou and Peter Cihon (GitHub), Mert Demirer (MIT Sloan)", "title": "The Impact of AI on Developer Productivity: Evidence from GitHub Copilot", "year": 2023, "sample": "95 freelance developers recruited on Upwork, mostly in India and Pakistan", "method": "Controlled experiment, 2022, on one task: writing a basic HTTP server in JavaScript", "figure": "55.8% less time (71 minutes against 161); 95% confidence interval 21% to 89%", "url": "https://arxiv.org/abs/2302.06590", "quote": "the treated group completed the task 55.8% faster (95% confidence interval: 21-89%)" }, { "creator": "Kevin Zheyuan Cui, Mert Demirer, Sonia Jaffe, Leon Musolff, Sida Peng and Tobias Salz (Princeton, MIT, Microsoft, Wharton)", "title": "The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers", "year": 2025, "sample": "4,867 developers at Microsoft, Accenture and a Fortune 100 electronics maker", "method": "Three randomized experiments run by the companies over 2 to 8 months, pooled. Counts output; does not time tasks.", "figure": "26.08% more completed pull requests a week for developers who used GitHub Copilot (standard error 10.3%)", "url": "https://economics.mit.edu/sites/default/files/inline-files/draft_copilot_experiments.pdf", "quote": "our analysis reveals a 26.08% increase (SE: 10.3%) in completed tasks among" }, { "creator": "Elise Paradis, Satish Chandra and colleagues (Google)", "title": "How much does AI impact development speed? An enterprise-based randomized controlled trial", "year": 2024, "sample": "96 full-time Google software engineers", "method": "Randomized trial on one enterprise task in Google's own tools, 2024. Google evaluated its own tools.", "figure": "About 21% less time (21% to 26% across models); 96 minutes with AI against 114 without", "url": "https://arxiv.org/abs/2410.12944", "quote": "this main effect was robust to covariates, making developers between 21% and 26% faster." }, { "creator": "Joel Becker, Nate Rush, Beth Barnes and David Rein (METR)", "title": "Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity", "year": 2025, "sample": "16 experienced developers, 246 real tasks in mature open-source projects they had worked on for about 5 years", "method": "Randomized at the task level, February to June 2025, mostly Cursor with Claude 3.5 and 3.7 Sonnet", "figure": "19% more time per task with AI (95% confidence interval +2% to +39%)", "url": "https://arxiv.org/abs/2507.09089", "quote": "we find that allowing AI actually increases completion time by 19%" }, { "creator": "METR", "title": "We are Changing our Developer Productivity Experiment Design", "year": 2026, "sample": "57 developers (10 from the first study, 47 new), more than 800 tasks", "method": "Same design from August 2025. Many developers declined tasks without AI, so METR calls the estimates unreliable.", "figure": "18% less time for returning developers and 4% less for new ones; both margins of error include zero", "url": "https://metr.org/blog/2026-02-24-uplift-update/", "quote": "Among newly-recruited developers the estimated speedup is -4%" } ], "related_findings": [ { "question": "Which developers gain the most from AI?", "answer": "Newer and more junior ones, in the three-company trials: developers with short tenure raised output 27% to 39%, against 8% to 13% for long-tenured colleagues, and junior developers 21% to 40% against 7% to 16% for senior ones. These splits are not statistically significant on their own. F-12 compares the pattern across studies.", "sources": [] }, { "question": "Do newer AI coding agents make developers faster?", "answer": "There is no clean measurement yet. METR's late-2025 rerun, with 57 developers, estimated 4% to 18% less time with AI, but both estimates sit within the margin of error. Many developers declined to do tasks without AI, which METR says biases the data.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Developers code 55% faster with GitHub Copilot.", "what_the_source_says": "This comes from one simple, self-contained lab task done by freelancers in 2022. METR's paper notes the task is unlike most software work." }, { "claim": "AI makes developers 19% slower.", "what_the_source_says": "METR studied 16 experienced developers in large, mature codebases with early-2025 tools. METR says the result does not show that AI slows down most developers, and its 2026 rerun leans toward a speedup." }, { "claim": "Copilot makes developers 26% more productive.", "what_the_source_says": "The 26% is the rise in pull requests completed per week for developers who used the tool, with a standard error of 10 points. It counts output, and measures neither time per task nor code quality." } ], "citation": "EVY (2026). How much faster do developers code with AI assistants? The AI at Work Fact Book, F-11. https://evy.so/facts/ai-coding-speed/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-12", "url": "https://evy.so/facts/ai-helps-less-experienced-workers-more/", "chapter": "What AI Saves", "question": "Does AI help less-experienced workers more than experienced ones?", "answer": "Mostly yes, on well-defined tasks: the newest or weakest workers gained about 27 to 46 percent in support, consulting and software studies, against 0 to 17 percent for the strongest. On open-ended business decisions the pattern reversed: in Kenya, strong entrepreneurs gained from an AI adviser while weak ones did nearly 10 percent worse.", "range": { "low": 27, "high": 46, "unit": "% gain for the newest or lowest-skilled workers", "display": "27–46% gain for the newest or weakest workers; the strongest gain 0 to 17%" }, "confidence": "medium", "confidence_reason": "Five independent teams in different settings find bigger gains for weaker or newer workers. Each measures a different outcome, the software gaps are not statistically significant, and a randomized trial on open-ended business decisions finds the reverse.", "last_checked": "2026-10-14", "how_to_read": "Studies split workers in different ways, by earlier performance or by tenure, and only the support and software studies speak directly to experience. Outcomes differ: issues resolved per hour, graded quality, pull requests and customer ratings. The BCG 43% and 17% compare consultants with their own earlier work and appear in the 2023 working paper; the published 2026 version keeps the finding without printing the numbers. Noy and Zhang and Alibaba show the same narrowing without a comparable percentage, so they are in the table only.", "sources": [ { "creator": "Erik Brynjolfsson (Stanford), Danielle Li and Lindsey Raymond (MIT)", "title": "Generative AI at Work (Quarterly Journal of Economics)", "year": 2025, "sample": "5,172 customer support agents at one Fortune 500 software firm", "method": "Staggered rollout, compared before and after, split by earlier skill and by tenure. The tenure figure is from the 2023 NBER version.", "figure": "Less skilled and less experienced agents +30%; lowest-skilled fifth +36%; agents with under a month of tenure about +46%; no significant change for the most skilled", "url": "https://doi.org/10.1093/qje/qjae044", "quote": "Less skilled and less experienced workers improve significantly across all productivity measures" }, { "creator": "Fabrizio Dell'Acqua, Ethan Mollick, Karim R. Lakhani and colleagues, with Boston Consulting Group", "title": "Navigating the Jagged Technological Frontier (HBS Working Paper 24-013)", "year": 2023, "sample": "758 BCG consultants", "method": "Preregistered randomized experiment. Gains compare AI users with their own earlier scores on a baseline task.", "figure": "Consultants below the median improved 43%, those above 17%", "url": "https://www.hbs.edu/faculty/Pages/item.aspx?num=64700", "archive_url": "https://web.archive.org/web/20240102034642/https://www.hbs.edu/ris/Publication%20Files/24-013_d9b45b68-9e74-42d6-a1c6-c72fb70c7282.pdf", "quote": "those below the average performance threshold increasing by 43% and those above increasing by 17%" }, { "creator": "Kevin Zheyuan Cui, Mert Demirer, Sonia Jaffe, Leon Musolff, Sida Peng and Tobias Salz", "title": "The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers (Management Science)", "year": 2026, "sample": "4,867 developers at Microsoft, Accenture and a Fortune 100 electronics maker", "method": "Three randomized company experiments, split by tenure and job level. The splits are not statistically significant.", "figure": "Short-tenure developers +27% to 39% completed tasks; long-tenure +8% to 13%", "url": "https://doi.org/10.1287/mnsc.2025.00535", "quote": "less experienced developers had higher adoption rates and greater productivity gains." }, { "creator": "Shakked Noy and Whitney Zhang (MIT)", "title": "Experimental evidence on the productivity effects of generative artificial intelligence (Science)", "year": 2023, "sample": "453 college-educated professionals", "method": "Preregistered online randomized experiment on writing tasks", "figure": "The gap between stronger and weaker writers halved: low scorers improved in grade and speed, high scorers kept their grade and got faster", "url": "https://www.science.org/doi/10.1126/science.adh2586", "quote": "ChatGPT compresses the productivity distribution by benefiting low-ability workers more." }, { "creator": "Xiao Ni, Yiwei Wang, Tianjun Feng, Lauren Xiaoyuan Lu, Yitong Wang and Congyi Zhou", "title": "Generative AI in Action: Field Experimental Evidence from Alibaba's Customer Service Operations", "year": 2026, "sample": "5,940 new customer service agents, about 2.56 million chats", "method": "Four-week randomized trial run by Alibaba, split by earlier customer ratings", "figure": "Ratings for the lowest-performing fifth rose 0.81 points on a 5-point scale and fell 0.28 for the top fifth", "url": "https://arxiv.org/abs/2603.29888", "quote": "Lower-performing agents benefit the most, indicating that gen AI can narrow performance gaps." } ], "related_findings": [ { "question": "When does AI help strong performers more than weak ones?", "answer": "On open-ended decisions, where people must judge which advice fits. In a five-month trial with 640 entrepreneurs in Kenya who got a GPT-4 business mentor on WhatsApp, low performers' revenue fell about 9% while high performers' rose about 18%, a gain the authors treat as tentative. They trace the gap to weaker owners acting on generic advice such as price cuts.", "sources": [ { "creator": "Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning", "title": "The Uneven Impact of Generative AI on Entrepreneurial Performance: Evidence from a Field Experiment in Kenya (HBS Working Paper 24-042)", "year": 2026, "sample": "640 entrepreneurs in Kenya, five months", "method": "Randomized field experiment: a GPT-4 mentor on WhatsApp or a standard business guide", "figure": "No average effect; low performers about 9% lower revenue, high performers about 18% higher (p = 0.07)", "url": "https://www.hbs.edu/ris/Publication%20Files/24-042_567db548-5b24-4182-b703-9d5ef1328043.pdf", "archive_url": "https://web.archive.org/web/20261009165007/https://www.hbs.edu/ris/Publication%20Files/24-042_567db548-5b24-4182-b703-9d5ef1328043.pdf", "quote": "low performers did nearly 10% worse due to the AI assistant" } ] } ], "numbers_you_may_have_seen": [ { "claim": "AI mostly helps top scientists (Toner-Rodgers, MIT, 2024).", "what_the_source_says": "MIT said in May 2025 that it has no confidence in the paper's data and asked for it to be withdrawn." }, { "claim": "Below-average BCG consultants improved 43% more than the control group.", "what_the_source_says": "The 43% and 17% compare consultants using AI with their own scores on an earlier task without AI." }, { "claim": "Novice support agents gained 34% with AI.", "what_the_source_says": "That is the 2023 working-paper figure. The peer-reviewed 2025 version says 30% for less skilled and less experienced agents and 36% for the lowest-skilled fifth." }, { "claim": "AI levels the playing field for every worker.", "what_the_source_says": "It holds in studies of well-defined tasks. In the Kenyan trial on open-ended business decisions, AI widened the gap." } ], "citation": "EVY (2026). Does AI help less-experienced workers more than experienced ones? The AI at Work Fact Book, F-12. https://evy.so/facts/ai-helps-less-experienced-workers-more/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-13", "url": "https://evy.so/facts/when-ai-makes-work-worse/", "chapter": "What AI Saves", "question": "When does AI make work slower or worse?", "answer": "On tasks the AI handles poorly, controlled studies find results 14 to 25 percent worse: consultants using GPT-4 gave fewer correct answers, and experienced developers took 19 percent longer. No study measures how often this happens across all AI-assisted work.", "range": { "low": 14, "high": 25, "unit": "percentage points fewer correct answers, or % more time, on tasks AI handles poorly", "display": "14–25% worse on tasks the AI handles poorly (points fewer correct answers, or percent more time)" }, "confidence": "medium", "confidence_reason": "Three independent creators with different designs each found a penalty in this band on some tasks. Each measures a different outcome, one study has only 3 people per group, and none answers how often it happens across all work.", "last_checked": "2026-10-14", "how_to_read": "Three kinds of worse get mixed up: wrong answers, slower work, and extra effort to check and fix output. This range covers the first two, from controlled studies, on tasks where AI was weak or people trusted it too much. Units differ: the BCG figure is percentage points of correct answers, the others percent more time. The same studies show gains on other tasks, and the UK observation had only 3 people per group.", "sources": [ { "creator": "Fabrizio Dell'Acqua, Ethan Mollick, Karim R. Lakhani and colleagues, with Boston Consulting Group", "title": "Navigating the Jagged Technological Frontier (Organization Science)", "year": 2026, "sample": "758 BCG consultants; the outside-the-frontier task was run with a subset", "method": "Preregistered randomized experiment. One business case was chosen so GPT-4 would give a plausible but wrong answer.", "figure": "84.5% correct without AI, 70.6% and 60% with AI: 13.9 and 24.5 points fewer correct answers, while spending less time", "url": "https://doi.org/10.1287/orsc.2025.21838" }, { "creator": "Joel Becker, Nate Rush, Beth Barnes and David Rein (METR)", "title": "Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity", "year": 2025, "sample": "16 experienced developers, 246 tasks in mature open-source projects", "method": "Randomized at the task level, February to June 2025, with screen recordings", "figure": "19% more time per task with AI; developers accepted under 44% of AI suggestions and spent more time prompting, waiting and reviewing", "url": "https://arxiv.org/abs/2507.09089", "quote": "we find that allowing AI actually increases completion time by 19%" }, { "creator": "UK Department for Business and Trade", "title": "The Evaluation of the M365 Copilot Pilot in the Department for Business and Trade", "year": 2025, "sample": "11 civil servants observed, 3 per group on the Excel task", "method": "Timed and blind-graded fictional tasks with matched colleagues as controls, late 2024. The authors warn the samples are very small.", "figure": "Excel analysis took 25:01 with Copilot against 20:33 without, with lower accuracy (1.5 against 2.7 out of 5)", "url": "https://assets.publishing.service.gov.uk/media/68adbe409e1cebdd2c96a19d/dbt-microsoft-365-copilot-evaluation.pdf", "quote": "M365 Copilot users completed Excel data analysis more slowly and to a worse quality" } ], "related_findings": [ { "question": "How much of the time AI saves goes into fixing its output?", "answer": "Nearly 40 percent, by AI users' own account in one vendor survey: Workday's November 2025 survey of 3,200 AI users at large firms. Only 14% said they consistently get clearly positive results. In a 2024 Upwork survey, 77% of employees who use AI said it had added to their workload in some way, and 39% spend more time reviewing AI output.", "confidence": "low", "sources": [ { "creator": "Workday, survey by Hanover Research", "title": "Beyond Productivity: Measuring the Real Value of AI", "year": 2026, "sample": "3,200 full-time employees who use AI, at organizations with $100 million or more in revenue", "method": "Online survey, November 2025, self-reported. Read in Workday's press release; the full report is gated. Workday sells AI products.", "figure": "Nearly 40% of AI time savings lost to rework; 14% consistently get clear net-positive results", "url": "https://newsroom.workday.com/2026-01-14-New-Workday-Research-Companies-Are-Leaving-AI-Gains-on-the-Table", "quote": "Nearly 40% of AI time savings are lost to rework" }, { "creator": "Upwork Research Institute with Workplace Intelligence", "title": "From Burnout to Balance: AI-Enhanced Work Models", "year": 2024, "sample": "2,500 respondents in the US, UK, Australia and Canada, including 625 full-time employees", "method": "Online survey, April to May 2024, self-reported. Read in Upwork's press release. Upwork sells freelance talent.", "figure": "77% of employees who use AI say it added to their workload; 39% spend more time reviewing AI content", "url": "https://investors.upwork.com/news-releases/news-release-details/upwork-study-finds-employee-workloads-rising-despite-increased-c", "quote": "77% of employees using AI say these tools have added to their workload" } ] }, { "question": "Does AI make software delivery less stable?", "answer": "Google's DORA surveys link wider AI adoption to less stable software delivery, in both 2024 and 2025. In 2025 the link to throughput turned positive while the stability link held. These are statistical associations from surveys of technology professionals and do not show cause.", "sources": [ { "creator": "Google Cloud DORA", "title": "2025 DORA Report: State of AI-assisted Software Development", "year": 2025, "sample": "Nearly 5,000 technology professionals", "method": "Annual survey with statistical modeling. Read in Google Cloud's announcement posts for 2024 and 2025.", "figure": "AI adoption linked to lower software delivery stability; 30% report little or no trust in AI-generated code", "url": "https://cloud.google.com/blog/products/ai-machine-learning/announcing-the-2025-dora-report", "quote": "AI adoption does continue to have a negative relationship with software delivery stability" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Upwork: 77% of workers say AI has decreased their productivity.", "what_the_source_says": "The survey says 77% of employees who use AI said it added to their workload, in a group of 625 full-time employees. It does not measure productivity." }, { "claim": "Workday: workers lose 40% of their time fixing AI.", "what_the_source_says": "The survey says nearly 40% of the time AI saves is lost to rework. As a share of the whole work week it is far smaller." }, { "claim": "AI makes consultants 19% worse (Dell'Acqua et al.).", "what_the_source_says": "The drop applies to one task chosen to sit outside GPT-4's abilities. On 18 other tasks the same consultants did better with AI." }, { "claim": "DORA: every 25% increase in AI adoption cuts delivery throughput by 1.5% and stability by 7.2%.", "what_the_source_says": "These are survey associations and do not show cause. In 2025 the throughput link turned positive; only the stability link held." } ], "citation": "EVY (2026). When does AI make work slower or worse? The AI at Work Fact Book, F-13. https://evy.so/facts/when-ai-makes-work-worse/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-14", "url": "https://evy.so/facts/share-of-workers-using-ai/", "chapter": "Who Uses AI at Work", "question": "What share of workers use generative AI at work?", "answer": "About 40 to 50 percent of US workers now use generative AI for their job, depending on how the question is asked. Daily use is much smaller: about 14 to 15 percent of all workers, or a quarter to a third of the people who use it.", "range": { "low": 40, "high": 50, "unit": "% of US workers who use generative AI for their job", "display": "40–50% of US workers use generative AI for their job (2026); studies range from 38 to 52%" }, "spread": { "low": 38, "high": 52, "unit": "% of US workers" }, "confidence": "high", "confidence_reason": "Three independent US surveys with different samples and wording land in the same range in the first half of 2026, and all three show the same rising trend. The width of the range comes from how each one defines use.", "last_checked": "2026-10-14", "how_to_read": "The surveys ask different questions. The St. Louis Fed survey asks about generative AI for your job and about last week; Gallup asks about any AI and counts people who use it a few times a year; Pew asks whether people ever use chatbots for work tasks, and in a stricter question how much of their work is done with AI. All are self-reported. Gallup and the St. Louis Fed survey both find daily use at about 14 to 15% of workers.", "sources": [ { "creator": "Alexander Bick (St. Louis Fed), Adam Blandin (Vanderbilt) and David Deming (Harvard); data published by the Federal Reserve Bank of St. Louis", "title": "Real-Time Population Survey: Generative AI Adoption Tracker (FRED series RPSGENAIUSAGESHARELWWORK)", "year": 2026, "sample": "Nationally representative online survey of US adults aged 18 to 64, May 2026 wave", "method": "Self-reported. Asks whether people use generative AI for their job, and on which workdays last week.", "figure": "45.2% use generative AI for their job; 39.2% used it for work last week (28.2% in August 2024); 13.7% every workday last week", "url": "https://fred.stlouisfed.org/series/RPSGENAIUSAGESHARELWWORK", "quote": "Did you use Generative AI for your job LAST WEEK?" }, { "creator": "Gallup", "title": "Organizational AI Adoption Jumps Six Points (Q2 2026 workforce study)", "year": 2026, "sample": "22,573 US employees, 6 to 20 May 2026", "method": "Probability-based Gallup Panel web survey. Asks about AI in general, by frequency.", "figure": "52% use AI at work a few times a year or more, 30% a few times a week or more, 15% daily", "url": "https://www.gallup.com/workplace/712736/organizational-adoption-jumps-six-points.aspx", "quote": "As of May 2026, 15% of U.S. employees use AI daily in their role," }, { "creator": "Pew Research Center", "title": "Americans and AI 2026: Chatbots, Smart Devices and Views on Impact", "year": 2026, "sample": "5,119 US adults, 17 to 23 February 2026", "method": "American Trends Panel, probability-based. Asks whether people ever use AI chatbots for tasks at work.", "figure": "38% of employed adults use AI chatbots for tasks at work", "url": "https://www.pewresearch.org/internet/2026/06/17/americans-and-ai-2026-chatbots-smart-devices-and-views-on-impact/", "quote": "38% of employed adults report using chatbots for tasks at work." }, { "creator": "Pew Research Center", "title": "About 1 in 5 U.S. workers now use AI in their job, up since last year", "year": 2025, "sample": "5,010 US workers, 2 to 8 September 2025", "method": "Asks how much of a worker's own job is done with AI. A stricter question, so it sits below the others.", "figure": "21% say at least some of their work is done with AI, up from 16% in October 2024", "url": "https://www.pewresearch.org/short-reads/2025/10/06/about-1-in-5-us-workers-now-use-ai-in-their-job-up-since-last-year/", "quote": "21% of U.S. workers say at least some of their work is done with AI" } ], "related_findings": [ { "question": "How often do workers who use AI use it?", "answer": "A quarter to a third of them use it every workday, and a little over half use it at least weekly. In May 2026, 15% of all US employees used AI daily and 30% a few times a week or more (Gallup); 13.7% used generative AI every workday of the previous week (St. Louis Fed survey). On days they use it, about a third of US users spend an hour or more with it. The among-user shares are our division of the published figures.", "sources": [ { "creator": "Alexander Bick, Adam Blandin and David Deming", "title": "The Rapid Adoption of Generative AI (NBER Working Paper 32966)", "year": 2025, "sample": "1,918 employed generative AI users, August and November 2024", "method": "Self-reported days of use last week and minutes per day of use", "figure": "34% of work users used it every workday last week; on days used, 32% spent an hour or more", "url": "https://www.nber.org/papers/w32966", "quote": "34 percent used it every workday in the previous week," }, { "creator": "Anders Humlum (Chicago Booth) and Emilie Vestergaard (University of Copenhagen), with Statistics Denmark", "title": "Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI (NBER Working Paper 33777)", "year": 2026, "sample": "About 25,000 workers in 11 AI-exposed occupations, late 2024", "method": "Survey linked to Danish government records", "figure": "16% of workers use AI chatbots daily and 35% weekly; daily use is 7% where employers do nothing and 28% where they encourage use and provide tools and training", "url": "https://www.nber.org/papers/w33777", "quote": "have used AI chatbots at work at least once, and 7% use them daily" } ] }, { "question": "What share of workers in the EU use generative AI for work?", "answer": "21.8% of employed people in the EU used generative AI tools for work in the three months before the 2025 survey, according to Eurostat. The often quoted 15% is the share of everyone aged 16 to 74, including people who are not working.", "sources": [ { "creator": "Eurostat", "title": "Individuals: use of generative AI tools (dataset isoc_ai_iaiu)", "year": 2026, "sample": "EU household ICT survey, all 27 member states, 2025", "method": "Official statistics; self-reported use in the previous 3 months, by purpose", "figure": "21.8% of employed people used generative AI for work; 15.4% of all people aged 16 to 74", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_ai_iaiu/default/table", "quote": "Use of generative AI tools: for professional (work) purposes" } ] } ], "numbers_you_may_have_seen": [ { "claim": "75% of workers use AI at work (Microsoft).", "what_the_source_says": "Microsoft's 2024 survey covered desk-based knowledge workers in an online panel across 31 markets. It does not describe the whole workforce." }, { "claim": "Half of US workers use AI at work (Gallup).", "what_the_source_says": "Gallup's 52% counts people who use AI a few times a year or more. 30% use it a few times a week and 15% daily." }, { "claim": "16% of US workers use AI (Pew).", "what_the_source_says": "That is October 2024, on Pew's strictest question. The same question gave 21% in September 2025." }, { "claim": "15% of Europeans use AI for work (Eurostat).", "what_the_source_says": "That share counts everyone aged 16 to 74, revised to 15.4%. Among employed people it is 21.8%." }, { "claim": "Half of workers use AI daily.", "what_the_source_says": "We found no source for it. Daily use is 14 to 15% of US workers." } ], "citation": "EVY (2026). What share of workers use generative AI at work? The AI at Work Fact Book, F-14. https://evy.so/facts/share-of-workers-using-ai/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-15", "url": "https://evy.so/facts/what-workers-use-ai-for/", "chapter": "Who Uses AI at Work", "question": "What do people use AI for at work?", "answer": "Mostly for writing and finding information: about half of AI-using workers use it for writing or editing, and about half for research or search. Coding is a minority use outside tech, named by 13 to 27 percent of AI users in surveys.", "range": { "low": 40, "high": 52, "unit": "% of AI-using workers who use it for writing or editing, or share of work ChatGPT messages that are writing", "display": "40–52% of AI users use it for writing or editing, the most common use" }, "confidence": "high", "confidence_reason": "Three US surveys and two usage-log studies, using different methods, agree that writing and finding information are the top work uses of general AI chatbots. Claude's logs lean toward coding, which reflects its user base and is shown separately.", "last_checked": "2026-10-14", "how_to_read": "Surveys ask workers what they use AI for, and the answers depend on the list offered and on whether the question asks about any use or the most helpful use. Usage logs classify real conversations, but each covers one product, counts messages instead of people, mixes work and personal use, and comes from the vendor. On general chatbots both kinds agree: writing and finding information lead. About two thirds of ChatGPT writing requests ask it to change text the user wrote.", "sources": [ { "creator": "Gallup", "title": "Organizational AI Adoption Jumps Six Points (Q2 2026 workforce study)", "year": 2026, "sample": "US employees who use AI, from 22,573 surveyed in May 2026", "method": "Self-reported uses, several answers allowed", "figure": "Writing and editing 51%, search or research 49%, general help or problem-solving 39%, data analysis 18%, coding 16%", "url": "https://www.gallup.com/workplace/712736/organizational-adoption-jumps-six-points.aspx", "quote": "the most common uses of AI are writing and editing (51%), search or research (49%)" }, { "creator": "Pew Research Center", "title": "U.S. Workers Are More Worried Than Hopeful About Future AI Use in the Workplace", "year": 2025, "sample": "Workers who have used AI chatbots at work, from 5,273 employed US adults, October 2024", "method": "Self-reported uses ever, several answers allowed", "figure": "Research or finding information 57%, editing written content 52%, drafting 47%, summarizing 40%, analyzing data or writing code 27%", "url": "https://www.pewresearch.org/social-trends/2025/02/25/workers-experience-with-ai-chatbots-in-their-jobs/", "quote": "Most common uses for AI chatbots at work are doing research and editing written content" }, { "creator": "Alexander Bick, Adam Blandin and David Deming", "title": "The Rapid Adoption of Generative AI (NBER Working Paper 32966)", "year": 2025, "sample": "4,698 employed generative AI users, August and November 2024", "method": "Users ranked the tasks AI helped with most last week (top two)", "figure": "Writing 39.5%, administrative tasks 25.6%, translating or summarizing 22.7%, searching for facts 18.0%, coding 12.9%", "url": "https://www.nber.org/papers/w32966", "quote": "The highest ranked tasks at work were writing (39.5 percent), administrative tasks" }, { "creator": "Aaron Chatterji, David Deming and colleagues (OpenAI, Duke, Harvard)", "title": "How People Use ChatGPT (NBER Working Paper 34255)", "year": 2025, "sample": "Random samples of consumer ChatGPT messages, May 2024 to June 2025; business plans excluded", "method": "Automated classification of messages. Counts messages, not people. Authors include OpenAI staff.", "figure": "Writing is 40% of work-related messages; 27% of all consumer messages were work-related in June 2025; programming is 4.2% of all messages", "url": "https://www.nber.org/papers/w34255", "quote": "Writing is the most common use case at work, accounting for 40% of work-related messages" }, { "creator": "Kiran Tomlinson, Sonia Jaffe, Will Wang, Scott Counts and Siddharth Suri (Microsoft Research)", "title": "Working with AI: Measuring the Applicability of Generative AI to Occupations", "year": 2025, "sample": "About 200,000 anonymized US Bing Copilot conversations, January to September 2024", "method": "Conversations matched to work activities by an AI classifier. Authors are Microsoft employees.", "figure": "Most common user goals: learning, communicating, explaining and writing", "url": "https://arxiv.org/abs/2507.07935", "quote": "the most common and successful AI-assisted work activities involve information work" } ], "related_findings": [ { "question": "Why do some studies say a third of AI use is coding?", "answer": "That comes from Claude's usage logs, where tasks tied to computer and mathematical jobs were 35% of Claude.ai conversations in February 2026, because Claude's users lean toward software work. In ChatGPT, programming is 4.2% of messages, and in worker surveys 13 to 27% of AI users name coding. In November 2025, Claude.ai chats were 52% augmentation (learning, iterating, checking) and 45% automation, while API traffic was about three quarters automation.", "sources": [ { "creator": "Anthropic", "title": "Anthropic Economic Index reports (January and March 2026)", "year": 2026, "sample": "1 million sampled conversations each from Claude.ai and the API, February 2026; a one-week sample in November 2025", "method": "Privacy-preserving classification of conversations, mapped to occupational tasks. Anthropic sells Claude.", "figure": "Computer and mathematical tasks 35% of Claude.ai conversations (February 2026); Claude.ai 52% augmentation and 45% automation (November 2025)", "url": "https://www.anthropic.com/research/anthropic-economic-index-january-2026-report", "quote": "The share of conversations classified as augmented jumped 5pp to 52%" } ] }, { "question": "Is most chatbot use for work?", "answer": "No. In June 2025, 73% of consumer ChatGPT messages were not about work, up from 53% a year earlier. Business and enterprise plans were not in that sample, so work use is understated. On Claude.ai, 46% of conversations were work in November 2025.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Most ChatGPT use is for work.", "what_the_source_says": "73% of consumer ChatGPT messages were not about work in June 2025." }, { "claim": "A third or more of AI use is coding.", "what_the_source_says": "True for Claude only. Programming is 4.2% of ChatGPT messages, and 13 to 27% of AI-using workers name coding in surveys." }, { "claim": "57% of AI use is augmentation, 43% automation (Anthropic).", "what_the_source_says": "That described Claude.ai in January 2025. By November 2025 it was 52% augmentation and 45% automation on Claude.ai, and API traffic was about three quarters automation." }, { "claim": "Therapy and companionship is the top use of generative AI.", "what_the_source_says": "OpenAI's study of ChatGPT messages found relationships and personal reflection at 1.9% of messages." } ], "citation": "EVY (2026). What do people use AI for at work? The AI at Work Fact Book, F-15. https://evy.so/facts/what-workers-use-ai-for/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-16", "url": "https://evy.so/facts/ai-use-by-occupation-and-industry/", "chapter": "Who Uses AI at Work", "question": "Which occupations and industries use AI the most?", "answer": "Tech workers, by a wide margin: about 8 in 10 US workers in computer jobs or the tech industry use AI for work, against about 2 in 10 in hands-on service jobs. The same order shows up in the EU, among EU firms and in AI companies' usage logs.", "range": { "low": 78, "high": 85, "unit": "% of US workers in the top group who use AI for work (2026)", "display": "78–85% of US tech workers use AI for work; hands-on service jobs about 15 to 25%" }, "confidence": "high", "confidence_reason": "Two US worker surveys, official EU statistics on people and on firms, Danish survey data and Anthropic's logs all put computer and information work on top and manual and in-person service work at the bottom. Small occupation groups have margins of error of 5 to 13 points, so the middle of the ranking is less certain than its ends.", "last_checked": "2026-10-14", "how_to_read": "Each chart row is the top group in one source. The US surveys and Eurostat's people survey give the share of workers in each job or industry who use AI; Eurostat's firm survey counts businesses; the Danish study covers 11 exposed jobs in late 2023. Industry labels differ (Gallup's technology against the official information industry). US rates run higher than EU rates partly because the surveys and time windows differ. Education stands out: many US education workers use AI, but few use it daily (9 to 13%).", "sources": [ { "creator": "Alexander Bick, Adam Blandin and David Deming; Federal Reserve Bank of St. Louis", "title": "Generative AI Adoption Tracker: adoption rate for work by occupation and industry (FRED)", "year": 2026, "sample": "Real-Time Population Survey, May 2026 wave; small groups have large margins of error", "method": "Self-reported use of generative AI for one's job, by occupation (22 groups) and industry", "figure": "Computer and mathematical 77.6%, management 71.9%, business and finance 60.3%, education 56.3%, office support 36.9%, personal care 20.8%, protective service 15.6%. By industry: information 82.2%, professional services 69.5%, public administration 23.4%", "url": "https://fred.stlouisfed.org/series/RPSGENAIUSAGESHAREOCC3", "quote": "Generative Artificial Intelligence, Adoption Rate for Work: Computer and Mathematical Occupations" }, { "creator": "Gallup", "title": "Indicator: Artificial Intelligence, AI use trends by industry", "year": 2026, "sample": "22,573 US employees, May 2026", "method": "Self-reported frequency of AI use, by 10 industries", "figure": "Technology 85% use AI (42% daily); finance 71%; professional services 68%; healthcare 48%; manufacturing 47%; retail 40%", "url": "https://www.gallup.com/699797/indicator-artificial-intelligence.aspx", "quote": "As of May 2026, daily AI use varies widely by industry." }, { "creator": "Eurostat", "title": "Individuals: use of generative AI tools (dataset isoc_ai_iaiu)", "year": 2026, "sample": "EU household ICT survey, 27 member states, 2025", "method": "Official statistics; use for work in the previous 3 months, by occupation group", "figure": "ICT professionals 58.3%, other professionals 20.0%, manual occupations 5.3%; all employed 21.8%", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_ai_iaiu/default/table", "quote": "Use of generative AI tools: for professional (work) purposes" }, { "creator": "Eurostat", "title": "Use of artificial intelligence in enterprises", "year": 2025, "sample": "157,000 EU enterprises with 10 or more employees, early 2025", "method": "Official statistics; share of firms (not workers) using at least one AI technology", "figure": "Information and communication 62.52% of firms; professional and technical services 40.43%; construction 10.79%; all firms 19.95%", "url": "https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Use_of_artificial_intelligence_in_enterprises", "quote": "the information and communication sector (with 62.52%) and professional, scientific and technical service activities" }, { "creator": "Anders Humlum and Emilie Vestergaard", "title": "The Adoption of ChatGPT (IZA Discussion Paper 16992)", "year": 2024, "sample": "Workers in 11 AI-exposed occupations in Denmark, November 2023 to January 2024", "method": "Survey with Statistics Denmark. Ever used ChatGPT, any purpose; an early wave.", "figure": "79% of software developers had used ChatGPT, against 34% of financial advisors", "url": "https://www.iza.org/publications/dp/16992", "quote": "adoption rates ranging from 79% for software developers to 34% for financial advisors" } ], "related_findings": [ { "question": "Which jobs do AI conversations come from?", "answer": "Mostly tech, in Claude's logs: tasks tied to computer and mathematical jobs were 35% of Claude.ai conversations in February 2026, against about 4% of US employment. In ChatGPT, 57% of messages from users in computer jobs are about work, against 40% for non-professional jobs. Both measure where usage is concentrated, not how many workers in a job use AI.", "sources": [ { "creator": "Anthropic", "title": "Anthropic Economic Index: Learning Curves (March 2026)", "year": 2026, "sample": "1 million sampled Claude.ai conversations, February 2026", "method": "Conversations mapped to the occupation a task belongs to. Anthropic sells Claude.", "figure": "Computer and mathematical tasks 35% of Claude.ai conversations", "url": "https://www.anthropic.com/research/economic-index-march-2026-report", "quote": "Computer and Mathematical occupations accounting for 35% of conversations on Claude.ai" }, { "creator": "Aaron Chatterji, David Deming and colleagues (OpenAI, Duke, Harvard)", "title": "How People Use ChatGPT (NBER Working Paper 34255)", "year": 2025, "sample": "Consumer ChatGPT users with known occupations, aggregated", "method": "Share of each occupation's messages that are about work", "figure": "57% of messages are work-related for computer-related jobs, 40% for non-professional jobs", "url": "https://www.nber.org/papers/w34255", "quote": "the unadjusted work shares are 57% for computer-related occupations" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Programmers are 37% of AI users (Anthropic).", "what_the_source_says": "37.2% was the share of Claude.ai conversations about computer and mathematical tasks in early 2025. It counts conversations on one product, and was 35% in February 2026." }, { "claim": "Microsoft's list of jobs most at risk from AI shows who uses AI.", "what_the_source_says": "The study scores how much Copilot conversations touch each job's activities, without knowing users' jobs. Its authors warn against reading it as job loss, and it does not measure who uses AI." }, { "claim": "79% of software developers use ChatGPT at work.", "what_the_source_says": "The 79% is ever use of ChatGPT for any purpose among Danish software developers in late 2023." } ], "citation": "EVY (2026). Which occupations and industries use AI the most? The AI at Work Fact Book, F-16. https://evy.so/facts/ai-use-by-occupation-and-industry/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-17", "url": "https://evy.so/facts/ai-use-by-age-education-income/", "chapter": "Who Uses AI at Work", "question": "Who uses AI at work more, by age, education and income?", "answer": "College graduates use AI at work 12 to 24 percentage points more than workers without a degree, and workers 50 and older trail younger colleagues by 4 to 20 points in the US. The income gap is the widest: across 47 countries, 83 percent of high-income employees use AI at work against 34 percent of low-income employees.", "range": { "low": 12, "high": 24, "unit": "percentage-point gap in AI use at work, college graduates against workers without a degree", "display": "12–24 pts more AI use at work among college graduates than among workers without a degree" }, "confidence": "high", "confidence_reason": "Four independent creators with different methods agree on the direction and roughly the size of the education gap. The exact size depends on how use is defined, and the income gap rests mainly on one survey.", "last_checked": "2026-10-14", "how_to_read": "The sources define use differently: Pew's main question asks whether some of your work is done with AI (strict), the St. Louis Fed survey asks whether you ever used generative AI for work, and the KPMG study counts any use, even every few months, across 47 countries. Stricter measures give smaller gaps. In the US the age gap is mostly between workers under 50 and those 50 and older. Part of the education gap is about jobs: it shrinks by about a third when comparing people in the same occupation.", "sources": [ { "creator": "Pew Research Center", "title": "About 1 in 5 U.S. workers now use AI in their job, up since last year", "year": 2025, "sample": "5,010 US workers, September 2025", "method": "Strict question: at least some of one's work is done with AI", "figure": "Bachelor's degree or more 28%, some college or less 16%", "url": "https://www.pewresearch.org/short-reads/2025/10/06/about-1-in-5-us-workers-now-use-ai-in-their-job-up-since-last-year/" }, { "creator": "Alexander Bick (St. Louis Fed), Adam Blandin (Vanderbilt) and David Deming (Harvard)", "title": "The Rapid Adoption of Generative AI (St. Louis Fed Working Paper 2024-027F, revised October 2025)", "year": 2025, "sample": "6,935 employed US adults aged 18 to 64, August and November 2024", "method": "Nationally representative online survey; ever used generative AI for work", "figure": "Less than college 23.7%, bachelor's 41.1%, graduate degree 47.5%; ages 50 to 64 at 22.6% against about 35% for younger workers", "url": "https://doi.org/10.20955/wp.2024.027", "quote": "use genAI at roughly twice the rate of non-college educated workers" }, { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Online survey; any intentional AI use at work, even every few months. Income tiers are set within each country.", "figure": "University educated 68% against 44% without; ages 18 to 34 at 72% against 40% at 55+; high income 83% against low income 34%", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "Employees who are younger, AI trained, university-educated, higher-income earners and managers are more likely" }, { "creator": "Pew Research Center", "title": "34% of U.S. adults have used ChatGPT, about double the share in 2023", "year": 2025, "sample": "Employed adults in a survey of 5,123 US adults, February to March 2025", "method": "Ever used ChatGPT specifically for work", "figure": "Ages 18 to 29 at 38% against 18% at 50+; postgraduates 45% against 17% with high school or less", "url": "https://www.pewresearch.org/short-reads/2025/06/25/34-of-us-adults-have-used-chatgpt-about-double-the-share-in-2023/", "quote": "38% of employed adults ages 18 to 29 say they have used ChatGPT" }, { "creator": "Anders Humlum (Chicago Booth) and Emilie Vestergaard (University of Copenhagen)", "title": "The unequal adoption of ChatGPT exacerbates existing inequalities among workers (PNAS)", "year": 2025, "sample": "About 18,000 workers in 11 AI-exposed occupations in Denmark, late 2023", "method": "Survey linked to government records; comparisons within each occupation", "figure": "Each extra year of age lowers the chance of having used ChatGPT for work by 0.7 points; higher earners use it more", "url": "https://www.pnas.org/doi/10.1073/pnas.2414972121", "quote": "we find younger and less experienced workers are more likely to use ChatGPT" } ], "related_findings": [ { "question": "Do older workers use AI less?", "answer": "Yes. In the US, workers 50 and older trail younger colleagues by 4 to 20 points depending on the measure: 13% against 17% on Pew's strict question (October 2024), 22.6% against about 35% in the St. Louis Fed survey (2024), and 18% against 38% for ChatGPT among the youngest (Pew, 2025). Across 47 countries the gap is 32 points (72% of ages 18 to 34 against 40% at 55 and older).", "sources": [] }, { "question": "Do higher earners and managers use AI more?", "answer": "Yes. Across 47 countries, 83% of high-income employees use AI at work against 34% of low-income employees, and 77% of managers against 34% of manual workers (KPMG and University of Melbourne). In the US, use rises with earnings up to about the top fifth, then falls slightly (St. Louis Fed survey). Gallup found leaders twice as likely as individual contributors to use AI frequently (33% against 16%, 2025).", "sources": [ { "creator": "Gallup", "title": "AI Use at Work Has Nearly Doubled in Two Years", "year": 2025, "sample": "US employees, Gallup Panel, May 2025", "method": "Self-reported frequency of AI use, by job level and job type", "figure": "Frequent AI use: leaders 33%, individual contributors 16%; white-collar 27%, production and front-line 9%", "url": "https://www.gallup.com/workplace/691643/work-nearly-doubled-two-years.aspx", "quote": "They are twice as likely as individual contributors (16%) to say they use AI" } ] } ], "numbers_you_may_have_seen": [ { "claim": "40% of college graduates use AI at work against 20% of others (St. Louis Fed).", "what_the_source_says": "That was the February 2025 draft. After reweighting, the October 2025 revision reports 41.1% (bachelor's) and 47.5% (graduate) against 23.7%." }, { "claim": "83% of high-income US workers use AI.", "what_the_source_says": "The 83% pools 47 countries, sets income tiers within each country, and counts use every few months." }, { "claim": "85% of Gen Z use AI at work, against 73% of Boomers (Microsoft).", "what_the_source_says": "Those are the shares of AI users in each generation who bring their own AI tools. They say nothing about how many people use AI." } ], "citation": "EVY (2026). Who uses AI at work more, by age, education and income? The AI at Work Fact Book, F-17. https://evy.so/facts/ai-use-by-age-education-income/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-18", "url": "https://evy.so/facts/gender-gap-in-ai-use/", "chapter": "Who Uses AI at Work", "question": "Is there a gender gap in AI use at work, and how large is it?", "answer": "Most studies find men use generative AI more than women, by about 5 to 16 percentage points, which makes men about 16 to 22 percent more likely to use it. The gap shrinks by a quarter to a third among people in the same job, and stays open.", "range": { "low": 5.4, "high": 16, "unit": "percentage points, men's AI use minus women's", "display": "5–16 pts more men than women use generative AI; men are 16 to 22% more likely" }, "confidence": "medium", "confidence_reason": "A US national survey, a Danish survey linked to government records and a review of 58 sources all find men ahead. Two large surveys report no meaningful gap on their measures, and the size varies with who is asked and how use is defined.", "last_checked": "2026-10-14", "how_to_read": "The review pools work and personal use, students and workers, so its levels are not workforce rates; its value is the direction and the trend, with the gap narrowing to about 16% since early 2025. The US survey is the cleanest whole-workforce figure (6 points, late 2024). The Danish study is the cleanest comparison within the same job, but covers ChatGPT only, early on. Pew's strict question shows no gap, which suggests the gap is smaller for regular, job-embedded use than for any use.", "sources": [ { "creator": "Katelyn Cranney (Stanford), Solène Delecourt (Berkeley Haas) and Rembrand Koning (Harvard Business School)", "title": "Global Evidence on Gender Gaps and Generative AI Over Time (HBS Working Paper 25-023, May 2026)", "year": 2026, "sample": "76 sources from more than 100 countries, 2023 to early 2026; 318,924 people in the pooled estimate", "method": "Systematic review, weighted by sample size. Mixes work and personal use, students and workers; many sources are convenience samples.", "figure": "47.8% of men against 39.3% of women use AI (men 22% more likely); in 2025 to 2026 data, 39.8% against 34.4% (5.4 points, men 16% more likely); men ahead in 56 of 58 sources", "url": "https://www.hbs.edu/ris/Publication%20Files/25-023_be8fb517-3dd5-40aa-97f9-4e42e1c8e6ff.pdf", "quote": "we estimate an AI adoption rate of 47.8% for men versus 39.3% for women" }, { "creator": "Alexander Bick, Adam Blandin and David Deming", "title": "The Rapid Adoption of Generative AI (St. Louis Fed Working Paper 2024-027F, revised October 2025)", "year": 2025, "sample": "6,935 employed US adults aged 18 to 64, August and November 2024", "method": "Nationally representative survey; ever used generative AI for work", "figure": "Men 35.0%, women 29.0%; with occupation controls the gap in last-week use falls from 7.0 to 4.8 points, and to 1.8 points once employer encouragement is added", "url": "https://doi.org/10.20955/wp.2024.027", "quote": "The top panel shows genAI adoption is 6 percentage points higher for men." }, { "creator": "Anders Humlum (Chicago Booth) and Emilie Vestergaard (University of Copenhagen)", "title": "The unequal adoption of ChatGPT exacerbates existing inequalities among workers (PNAS)", "year": 2025, "sample": "17,907 workers in 11 AI-exposed occupations in Denmark, late 2023", "method": "Survey linked to government records; ChatGPT only, ever used for work", "figure": "Women 15.9 points less likely than men in the same occupation; 11.8 points among coworkers in the same workplace with the same tasks", "url": "https://www.pnas.org/doi/10.1073/pnas.2414972121", "quote": "Women are 16 percentage points less likely to have used the tool for work." }, { "creator": "Pew Research Center", "title": "U.S. Workers Are More Worried Than Hopeful About Future AI Use in the Workplace", "year": 2025, "sample": "5,273 employed US adults, October 2024", "method": "Strict question: at least some of one's work is done with AI", "figure": "Men are 53% of AI users and 53% of non-users: no gap on this measure", "url": "https://www.pewresearch.org/social-trends/2025/02/25/u-s-workers-are-more-worried-than-hopeful-about-future-ai-use-in-the-workplace/", "quote": "AI users are younger and more educated compared with other workers" }, { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries", "method": "Reports only group differences above an effect-size cut-off, so a small gap may exist below it", "figure": "No gender difference reported in AI use at work", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "there are no gender differences in AI use or attitudes toward AI at work" } ], "related_findings": [ { "question": "Does the gender gap close among people in the same job?", "answer": "It shrinks and stays open. In Denmark the gap falls from 15.9 to 11.8 points among coworkers in the same workplace doing the same tasks. In the US it falls from 7.0 to 4.8 points with occupation controls, and to 1.8 points (only weakly significant) once employer encouragement is added, which the authors say may not be a cause. Danish women more often said they needed training; men more often cited employer restrictions.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Women are 20% (or 25%) less likely than men to use generative AI.", "what_the_source_says": "From 2024 drafts of the Harvard review, which reported 22% lower odds, a different quantity from 22% lower probability. The May 2026 version says men are 22% more likely overall and about 16% since early 2025." }, { "claim": "Women are 16 points less likely to use AI at work.", "what_the_source_says": "That is Denmark, ChatGPT only, in 11 exposed jobs, late 2023. US whole-workforce data from late 2024 show 6 points." }, { "claim": "There is no gender gap in AI use at work (KPMG).", "what_the_source_says": "The study reports only gaps above an effect-size cut-off and publishes no rates by gender. It rules out a large gap, not a small one." }, { "claim": "Only 44% of ChatGPT users are women.", "what_the_source_says": "It is the female share of US visits to chatgpt.com, with gender inferred from web traffic. It gives no usage rate for men or women." } ], "citation": "EVY (2026). Is there a gender gap in AI use at work, and how large is it? The AI at Work Fact Book, F-18. https://evy.so/facts/gender-gap-in-ai-use/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-19", "url": "https://evy.so/facts/bring-your-own-ai/", "chapter": "Who Uses AI at Work", "question": "How many workers use AI tools their employer did not provide, and how many hide it?", "answer": "Half to three quarters of workers who use AI use at least some tools their employer did not provide, and most of them also use approved tools. About half are reluctant to tell their manager or have avoided revealing their AI use.", "range": { "low": 50, "high": 78, "unit": "% of AI-using workers who use some AI tools their employer did not provide", "display": "50–78% of AI-using workers use at least some tools their employer did not provide (2024)" }, "confidence": "medium", "confidence_reason": "Three independent surveys with different questions land in the same band. All are online panels, two run by software vendors, and they ask different things: whether tools are employer-provided, which routes people use, or whether tools are company-issued.", "last_checked": "2026-10-14", "how_to_read": "Using a tool the employer did not provide is different from breaking a rule: only about 6% of workers report an outright ban, so most outside-tool use is not against an explicit rule. Many people use both: in the KPMG study, 70% use free public tools and 42% use employer tools. Microsoft's 78% is a share of AI users, which is about 58% of all knowledge workers. Microsoft and Software AG sell software that addresses this. Chapter 4 covers the risk side: use against policy and company data in public tools.", "sources": [ { "creator": "Microsoft and LinkedIn, survey by Edelman Data & Intelligence", "title": "2024 Work Trend Index Annual Report: AI at Work Is Here. Now Comes the Hard Part", "year": 2024, "sample": "31,000 knowledge workers in 31 markets, February to March 2024", "method": "Online survey. Asked whether the AI tools people use at work are provided by their organization. Microsoft sells AI tools for work.", "figure": "78% of AI users bring their own AI tools (US 63%, UK 75%, Germany 71%); 80% at small and medium-sized companies", "url": "https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part", "quote": "78% of AI users are bringing their own AI tools to work (BYOAI)" }, { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Online survey; AI-using employees picked every way they access AI tools", "figure": "Free public tools 70%, employer-provided tools 42%, paid public tools 18%; 61% have avoided revealing their AI use", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf" }, { "creator": "Software AG, survey by TEAM LEWIS", "title": "Half of all employees are Shadow AI users, new study finds", "year": 2024, "sample": "6,000 knowledge workers in the US, UK and Germany, September 2024", "method": "Online panel survey. Shadow AI means tools the company did not issue, including tolerated ones. Software AG sells integration software.", "figure": "Half of employees use AI tools the company did not issue; 46% would keep using personal tools even if banned", "url": "https://newscenter.softwareag.com/en/news-stories/press-releases/2024/1022-half-of-all-employees-use-shadow-ai.html", "archive_url": "https://web.archive.org/web/20251105024925/https://newscenter.softwareag.com/en/news-stories/press-releases/2024/1022-half-of-all-employees-use-shadow-ai.html", "quote": "half of all employees are using Shadow AI (i.e. non-company issued AI tools)" } ], "related_findings": [ { "question": "How many workers hide their AI use from their employer?", "answer": "About half, depending on the question. 48% of desk workers would be uncomfortable telling their manager they used AI for common tasks (Slack, 2024, asked of users and non-users). 52% of AI users are reluctant to admit using it for their most important tasks (Microsoft, 2024). 61% of AI-using employees have avoided revealing their use at least once, and about 42% do so sometimes or more (KPMG and University of Melbourne).", "sources": [ { "creator": "Slack Workforce Lab (Salesforce)", "title": "The Fall 2024 Workforce Index", "year": 2024, "sample": "17,372 desk workers in 15 countries, August 2024", "method": "Online survey; a hypothetical question asked of everyone, users and non-users", "figure": "48% would be uncomfortable admitting to their manager that they used AI for common tasks; top reason: it feels like cheating", "url": "https://slack.com/blog/news/the-fall-2024-workforce-index-shows-executives-and-employees-investing-in-ai-but-uncertainty-holding-back-adoption", "quote": "of all desk workers said they would be uncomfortable admitting to their manager" } ] }, { "question": "Do people use AI at work even when their employer offers nothing?", "answer": "Yes. In Denmark, about 40% of workers in exposed jobs had used AI chatbots at work in workplaces that neither encourage it nor provide tools or training, and 7% use them daily. In the US, 6.8% of firms report workers using AI with no firm-level AI use, which is 29% of all firms with any AI use.", "sources": [ { "creator": "Anders Humlum and Emilie Vestergaard, with Statistics Denmark", "title": "Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI (NBER Working Paper 33777)", "year": 2026, "sample": "About 25,000 workers in 11 AI-exposed occupations, late 2024", "method": "Survey linked to Danish government records", "figure": "About 40% have used AI chatbots at work where employers neither encourage nor equip them; 6% report a ban", "url": "https://www.nber.org/papers/w33777", "quote": "Even in workplaces that neither encourage use nor provide enterprise tools or training" }, { "creator": "US Census Bureau Center for Economic Studies", "title": "The Microstructure of AI Diffusion (CES Working Paper 26-25)", "year": 2026, "sample": "Business Trends and Outlook Survey AI supplement, November 2025 to January 2026", "method": "Firm-reported, one respondent per business", "figure": "6.8% of US firms report worker AI use with no firm-level AI use", "url": "https://www2.census.gov/library/working-papers/2026/adrm/ces/CES-WP-26-25.pdf", "quote": "worker task use sometimes occurs without formal firm-level adoption" } ] } ], "numbers_you_may_have_seen": [ { "claim": "78% of workers bring their own AI to work.", "what_the_source_says": "The 78% is of knowledge workers who use AI, about 58% of all knowledge workers, and 63% of AI users in the US. It counts tools the employer did not provide, which is different from banned tools." }, { "claim": "Half of all employees use unauthorized AI (Software AG).", "what_the_source_says": "The survey defines shadow AI as tools the company did not issue, which includes tools it allows, among knowledge workers in three countries." }, { "claim": "48% of workers hide their AI use from their boss (Slack).", "what_the_source_says": "Slack asked whether people would be uncomfortable admitting AI use. It is reluctance to tell, asked of non-users too, and did not ask about actual hiding." }, { "claim": "57% of employees hide their AI use (KPMG).", "what_the_source_says": "It combines two behaviors and counts anyone who did either even rarely. Doing it sometimes or more is 39 to 42%." } ], "citation": "EVY (2026). How many workers use AI tools their employer did not provide, and how many hide it? The AI at Work Fact Book, F-19. https://evy.so/facts/bring-your-own-ai/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-20", "url": "https://evy.so/facts/employers-providing-ai-tools/", "chapter": "Who Uses AI at Work", "question": "How many employers provide AI tools, guidance or training to staff?", "answer": "About half of workers say their employer has brought in AI tools, 42 to 49 percent in 2024 to 2026, but only 25 to 40 percent report a clear AI plan or policy. Counted by firms instead of workers, adoption is lower: 20 percent of EU firms and 24 percent of US businesses use AI, because most firms are small.", "range": { "low": 42, "high": 49, "unit": "% of workers who say their employer has brought in AI tools", "display": "42–49% of workers say their employer has brought in AI tools; 25 to 40% report a clear plan or policy" }, "confidence": "medium", "confidence_reason": "Two independent creators with different methods agree in the 40s, but one counts all employees and the other AI users, and about one in five US employees do not know what their employer has done. Firm counts from two official statistics agencies are reliable on their own terms and are shown separately.", "last_checked": "2026-10-14", "how_to_read": "Worker-reported figures count employees, so large employers weigh more, and they depend on what workers know. Firm-reported figures count businesses, most of which are small, so they come out much lower. The consistent finding is the gap between tools and guidance: in the US, 47% of employees report AI tools but 25% a clear plan. Training figures come from different questions, so they are listed separately below.", "sources": [ { "creator": "Gallup", "title": "Organizational AI Adoption Jumps Six Points (Q2 2026 workforce study)", "year": 2026, "sample": "22,573 US employees, 6 to 20 May 2026", "method": "Probability-based Gallup Panel; worker-reported, with a don't-know option since late 2025", "figure": "47% say their organization has integrated AI tools (38% in Q4 2025); about 20% don't know; 25% say a clear plan for AI was communicated", "url": "https://www.gallup.com/workplace/712736/organizational-adoption-jumps-six-points.aspx", "quote": "Forty-seven percent of U.S. employees now say their organization has integrated AI tools" }, { "creator": "Gallup", "title": "Indicator: Artificial Intelligence", "year": 2026, "sample": "US employees, quarterly Gallup Panel waves", "method": "Worker-reported; the August 2026 value is read from the indicator's chart data", "figure": "Clear plan for integrating AI communicated: 15% (2024), 22% (2025), 25% (May 2026), 26% (August 2026); AI tools integrated 49% (August 2026)", "url": "https://www.gallup.com/699797/indicator-artificial-intelligence.aspx" }, { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Online survey; worker-reported", "figure": "42% of AI-using employees use employer-provided tools; 34% have a policy guiding generative AI use, 6% a ban, 41% none, 19% don't know", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "only two in five say there is a policy guiding its use" }, { "creator": "Gallup", "title": "AI Use at Work Has Nearly Doubled in Two Years", "year": 2025, "sample": "US employees, Gallup Panel, May 2025", "method": "Worker-reported, before the don't-know option was added", "figure": "30% say their organization has general guidelines or formal policies for AI use (20% in 2024)", "url": "https://www.gallup.com/workplace/691643/work-nearly-doubled-two-years.aspx", "quote": "30% of employees say their organization has either general guidelines or formal policies" } ], "related_findings": [ { "question": "What share of companies use AI?", "answer": "About one in five, counted by firms. 19.95% of EU enterprises with 10 or more employees used AI in 2025, rising to 55% of large ones, and 23.8% of US businesses used AI in the two weeks to 20 September 2026, rising to 37% of firms with 250 or more staff. Weighted by employment the picture changes: 78% of the US labor force works at firms that have adopted AI.", "sources": [ { "creator": "Eurostat", "title": "Use of artificial intelligence in enterprises", "year": 2025, "sample": "157,000 EU enterprises with 10 or more employees, 2025", "method": "Official statistics; firm-reported use of any of eight AI technologies", "figure": "19.95% of EU enterprises (13.48% in 2024); small 17.0%, medium 30.4%, large 55.0%; Denmark 42.0%, Romania 5.2%", "url": "https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Use_of_artificial_intelligence_in_enterprises", "quote": "In 2025, 19.95% of EU enterprises used AI technologies." }, { "creator": "US Census Bureau", "title": "Business Trends and Outlook Survey (BTOS), national estimates", "year": 2026, "sample": "About 20,000 responses per two-week period from US businesses", "method": "Official experimental survey; firm-reported. The question changed in late 2025, so older figures are not comparable.", "figure": "23.8% of US businesses used AI in any business function (period ending 20 September 2026); 37% of firms with 250 or more employees (spring 2026)", "url": "https://www.census.gov/hfp/btos/data", "quote": "did this business use Artificial Intelligence (AI) in any of its business functions?" }, { "creator": "Jeffrey S. Allen, Federal Reserve Board", "title": "Monitoring AI Adoption in the US Economy (FEDS Notes)", "year": 2026, "sample": "Comparison of Census, St. Louis Fed and Atlanta Fed surveys", "method": "Research note comparing firm-weighted and employment-weighted adoption", "figure": "About 18% of US firms used AI at the end of 2025, while 78% of the labor force works at firms that have adopted AI", "url": "https://www.federalreserve.gov/econres/notes/feds-notes/monitoring-ai-adoption-in-the-u-s-economy-20260403.html", "quote": "78 percent of the labor force works at firms that have adopted AI" } ] }, { "question": "How many employers train staff on AI?", "answer": "A minority, though the questions differ. In 2024, 39% of AI users had received AI training from their company (Microsoft). In Denmark, 39% of employers that encourage AI chatbots provide training. About 15% of AI-using US firms report training staff (Census, late 2025). Where employers combine encouragement, tools and training, 93% of Danish workers in exposed jobs use AI, against about 41% where employers do nothing.", "confidence": "low", "sources": [ { "creator": "Microsoft and LinkedIn", "title": "2024 Work Trend Index Annual Report", "year": 2024, "sample": "31,000 knowledge workers in 31 markets", "method": "Online survey. Microsoft sells AI tools and training.", "figure": "39% of people who use AI at work have had AI training from their company", "url": "https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part", "quote": "Only 39% of people globally who use AI at work have gotten AI training" }, { "creator": "Anders Humlum and Emilie Vestergaard, with Statistics Denmark", "title": "Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI (NBER Working Paper 33777)", "year": 2026, "sample": "About 25,000 workers at about 7,000 workplaces, late 2024", "method": "Worker-reported employer policies, linked to government records", "figure": "43% of employers encourage AI chatbot use; of those, 61% provide an enterprise chatbot and 39% training", "url": "https://www.nber.org/papers/w33777", "quote": "about 43% explicitly encourage their use, another 21% allow it" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Only 5% to 10% of US businesses use AI (Census).", "what_the_source_says": "That was the old question, about AI used to produce goods or services. With the current wording it is 17% to 24% (late 2025 to September 2026)." }, { "claim": "78% of companies use AI.", "what_the_source_says": "78% is the share of the US labor force working at firms that have adopted AI, which large firms dominate. Counted by firms it is 18% to 24%." }, { "claim": "Gallup: 44% of organizations have integrated AI.", "what_the_source_says": "It is the share of employees who say so, from May 2025, before Gallup added a don't-know option. The comparable figure for May 2026 is 47%." }, { "claim": "One in five EU companies use generative AI.", "what_the_source_says": "Eurostat's 19.95% counts any of eight AI technologies, including older ones. Text or speech generation alone was 8.76% of enterprises in 2025." }, { "claim": "Only 25% of companies offer AI training (Microsoft).", "what_the_source_says": "Microsoft's 2024 report said 25% of companies were planning to offer generative AI training that year. It was a plan, and is now dated." } ], "citation": "EVY (2026). How many employers provide AI tools, guidance or training to staff? The AI at Work Fact Book, F-20. https://evy.so/facts/employers-providing-ai-tools/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-21", "url": "https://evy.so/facts/trust-in-ai-output/", "chapter": "What Teams Trust", "question": "How much do workers trust the output of AI tools at work?", "answer": "A quarter to a half of workers trust AI output at work, depending on how strictly trust is defined: 24 to 33 percent clearly trust its quality or accuracy, and 53 percent of employees across 47 countries are willing to trust AI for work. Very few trust it with important decisions: 7 percent of developers in 2026.", "range": { "low": 24, "high": 53, "unit": "% of workers who say they trust AI output at work", "display": "24–53% of workers trust AI output at work: 24 to 33% firmly, 53% willing to trust it for work" }, "confidence": "medium", "confidence_reason": "Three independent creators show the same shape: a minority with firm trust, a large group with conditional trust, and little trust for high-stakes use. The range is wide because the questions differ, and two of the three survey software workers only.", "last_checked": "2026-10-14", "how_to_read": "Each source asks about trust differently: the quality of AI output (DORA), its accuracy (Stack Overflow 2025), willingness to trust AI for work (KPMG) and when people trust it (Stack Overflow 2026). Where you draw the line matters: counting DORA's somewhat trust moves the figure from 24% to 70%. DORA and Stack Overflow survey software workers, who can test AI output; KPMG covers all occupations. All are self-reports.", "sources": [ { "creator": "Google Cloud DORA", "title": "State of AI-assisted Software Development 2025 (DORA Report)", "year": 2025, "sample": "Nearly 5,000 technology professionals, June to July 2025", "method": "Online survey: how much did you trust the quality of AI-generated output at work. Google sells AI coding tools.", "figure": "24% trust it a lot or a great deal, 46% somewhat, 30% a little or not at all", "url": "https://dora.dev/research/2025/dora-report/", "quote": "currently report little to no trust in the code generated by AI" }, { "creator": "Stack Overflow", "title": "2025 Developer Survey: AI", "year": 2025, "sample": "33,244 developers answering the trust question, mid-2025", "method": "Opt-in online survey: how much do you trust the accuracy of AI output in your workflow", "figure": "33% trust its accuracy (3.1% highly), 46% distrust it", "url": "https://survey.stackoverflow.co/2025/ai", "quote": "More developers actively distrust the accuracy of AI tools (46%) than trust it (33%)" }, { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Online survey; willing to trust AI for work purposes, including somewhat willing", "figure": "53% trust AI tools for work, from 31% in Japan to 81% in India and Nigeria; 46% of all people are willing to trust AI in general", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "About half (53%) report trusting AI tools for work purposes" }, { "creator": "Stack Overflow", "title": "2026 Developer Survey: AI data", "year": 2026, "sample": "14,304 developers answering this question, June to August 2026", "method": "New 2026 question: when do you trust AI output in your workflow", "figure": "48% trust it when they can easily verify it; 6.6% trust it for important work decisions; 12.3% do not trust it for most work tasks", "url": "https://survey.stackoverflow.co/2026/ai/data", "quote": "48% trust AI when they can easily verify it" } ], "related_findings": [ { "question": "Do workers trust AI with important decisions?", "answer": "Rarely. In 2026, 48% of developers trust AI output when they can easily verify it, and only 6.6% trust it for important work decisions (4% among early-career developers). The pattern holds outside software: people trust AI most where the result is easy to check.", "sources": [] }, { "question": "Is trust in AI rising or falling?", "answer": "Falling a little in the countries tracked longest. Across 47 countries, 46% of people are willing to trust AI in general, while 65% believe it gives accurate output, so trust in AI's answers runs ahead of trust in AI overall. In the 17 countries surveyed in both 2022 and 2024, willingness to rely on AI fell from 52% to 43%.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Only 3% of developers trust AI (Stack Overflow).", "what_the_source_says": "3.1% highly trust the accuracy of AI output. Including those who somewhat trust it, 33% trust it, and 46% distrust it." }, { "claim": "Most workers don't trust AI (KPMG).", "what_the_source_says": "The 54% who are wary combines unwilling and ambivalent people, asked about AI in general. Among employees asked about AI for work, 53% are willing to trust it." }, { "claim": "30% of developers don't trust AI-generated code (DORA).", "what_the_source_says": "The 30% is a little trust (23%) plus none at all (7%). Only 7% have no trust at all." } ], "citation": "EVY (2026). How much do workers trust the output of AI tools at work? The AI at Work Fact Book, F-21. https://evy.so/facts/trust-in-ai-output/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-22", "url": "https://evy.so/facts/checking-ai-output/", "chapter": "What Teams Trust", "question": "How often do people check AI output before using it?", "answer": "About four in ten AI users regularly use AI output without checking it, by their own account: 44 percent of AI-using employees across 47 countries do not verify its accuracy most of the time, and knowledge workers report no critical thinking on 41 percent of their AI-assisted tasks. 56 percent of AI-using employees say AI has caused a mistake in their work at least once.", "range": { "low": 41, "high": 44, "unit": "% of AI users, or of their AI-assisted tasks, where output is used without routine checking", "display": "41–44% of AI users, or of their AI tasks, go without routine checking (self-reported)" }, "confidence": "medium", "confidence_reason": "Two independent creators with very different methods land on almost the same figure, one counting people and one counting tasks. Both are self-reports, which likely understate careless use, and the observed studies are small or older.", "last_checked": "2026-10-14", "how_to_read": "Most of this is self-reported, and people likely flatter themselves. KPMG counts people, Lee and colleagues count tasks. Checking depends on how easy it is: developers can run code, so only about 10% use AI answers as-is, while KPMG finds that people who trust AI more check less. The only observed studies are a 2023 writing experiment and a small 2025 trial of 16 developers, who accepted under 44% of AI code suggestions.", "sources": [ { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Online survey of employees who use AI at work, self-reported frequency", "figure": "56% verify AI accuracy most of the time or always, so 44% do not; 42% rely on output without evaluating it sometimes or more often (66% ever)", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "Two in three report relying on AI output without evaluating the information it provides" }, { "creator": "Hao-Ping (Hank) Lee and colleagues, Microsoft Research and Carnegie Mellon University", "title": "The Impact of Generative AI on Critical Thinking (CHI 2025)", "year": 2025, "sample": "319 knowledge workers using AI at least weekly, describing 936 real tasks", "method": "Online survey; for each task, whether the worker did any critical thinking such as verifying or editing", "figure": "Critical thinking reported on 59.3% of tasks, so none on 40.7%; higher confidence in AI predicted less critical thinking", "url": "https://www.microsoft.com/en-us/research/wp-content/uploads/2025/01/lee_2025_ai_critical_thinking_survey.pdf", "quote": "Our participants self-reported to have enacted critical thinking for 555 (59.29%) of the examples" }, { "creator": "Stack Overflow", "title": "2026 Developer Survey: AI data", "year": 2026, "sample": "13,162 developers answering this question, June to August 2026", "method": "Opt-in survey; what developers usually do with an AI answer, several answers allowed", "figure": "9.6% use AI answers as-is; 76.5% run the code, 63.9% compare it with the codebase", "url": "https://survey.stackoverflow.co/2026/ai/data", "quote": "Only 10% use answers as-is." }, { "creator": "Shakked Noy and Whitney Zhang (MIT)", "title": "Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence", "year": 2023, "sample": "444 college-educated professionals in an online writing experiment, early 2023", "method": "Self-report plus observed activity on the platform; not participants' real jobs", "figure": "68% said they submitted ChatGPT's first output unedited, and were active for about 3 minutes after pasting it in", "url": "https://economics.mit.edu/sites/default/files/inline-files/Noy_Zhang_1.pdf", "quote": "68% of treated participants report submitting ChatGPT’s initial output without editing it" } ], "related_findings": [ { "question": "How many workers have made mistakes because of AI?", "answer": "Between about a third and a half of AI users. 56% of AI-using employees across 47 countries say they have made a mistake in their work because of AI, and 31% say it happens sometimes or more often. In a small 2026 US poll, 30% said a wrong AI answer had caused a problem in their work. Noticing errors is more common still: 66% of developers report AI answers that are almost right, but not quite.", "confidence": "low", "sources": [ { "creator": "Kolmogorov Law, poll on Pollfish", "title": "Half of U.S. Workers Know They Would Be Personally Liable for a Wrong AI Answer", "year": 2026, "sample": "500 employed US adults who use AI for work, September 2026, unweighted", "method": "Online poll commissioned by a law firm; treat as indicative", "figure": "30% say a wrong AI answer has caused a problem in their work; 65% do not always verify AI answers", "url": "https://www.prnewswire.com/news-releases/half-of-us-workers-know-they-would-be-personally-liable-for-a-wrong-ai-answer-two-thirds-still-dont-always-check-kolmogorov-law-survey-finds-302867898.html", "quote": "a wrong or inaccurate AI answer has caused a problem in their work" }, { "creator": "Stack Overflow", "title": "2025 Developer Survey: AI", "year": 2025, "sample": "25,332 developers answering the frustrations question", "method": "Opt-in online survey, several answers allowed", "figure": "66% cite AI answers that are almost right, but not quite; 45.2% say debugging AI code takes more time", "url": "https://survey.stackoverflow.co/2025/ai", "quote": "AI solutions that are almost right, but not quite" } ] }, { "question": "Do AI mistakes reach customers?", "answer": "Sometimes. A quarter of IT leaders (25%) say AI mistakes have already hurt customers or clients, 23% that they cost the company money, and 16% that they seriously disrupted operations. Of employees who review colleagues' AI work, 79% regularly receive output that is low quality or contains errors.", "sources": [ { "creator": "GoTo with Workplace Intelligence", "title": "The Pulse of Work in 2026", "year": 2026, "sample": "1,250 knowledge workers and 1,250 IT decision-makers in 10 countries, November 2025 to January 2026", "method": "Online survey. GoTo sells IT and communications software.", "figure": "25% of IT leaders say AI mistakes hurt customers; 79% of employees who review colleagues' AI work regularly get flawed output", "url": "https://edge.sitecorecloud.io/gototechnol00e8-mktglobalxm07e7-mktglobalpr9498-b870/media/goto/pdfs/ebook/ebook_pulse-of-work-2026.pdf", "quote": "around one-quarter of IT leaders say AI has made mistakes that affected customers" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Two thirds of employees use AI output without checking it (KPMG).", "what_the_source_says": "66% have done so at least once, including rarely. Doing it sometimes or more often is 42%, and 56% verify accuracy most of the time." }, { "claim": "57% of workers have made mistakes because of AI (KPMG).", "what_the_source_says": "The global report says 56%, counting anyone who did so even once. Sometimes or more often is 31%." }, { "claim": "AI is destroying critical thinking (Microsoft and Carnegie Mellon).", "what_the_source_says": "The study measured 319 workers' own sense of effort and whether they thought critically. It did not test thinking skills or show a decline over time." }, { "claim": "77% of employees review AI work as carefully as human work (Workday).", "what_the_source_says": "The 77% covers only employees who use AI every day, at companies with more than $100 million in revenue, in a vendor survey." }, { "claim": "66% of developers spend more time fixing AI code (Stack Overflow).", "what_the_source_says": "66% cite answers that are almost right; 45.2% say debugging AI code takes more time." } ], "citation": "EVY (2026). How often do people check AI output before using it? The AI at Work Fact Book, F-22. https://evy.so/facts/checking-ai-output/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-23", "url": "https://evy.so/facts/ai-error-rates-at-work/", "chapter": "What Teams Trust", "question": "How often is AI output wrong on real work tasks?", "answer": "In independent tests on realistic professional questions, 17 to 45 percent of AI answers contained a hallucination or significant error (2024 to 2025). Rates fall sharply when the AI only summarizes a document it is given, and rise sharply for whole projects, and they change with every model release.", "range": { "low": 17, "high": 45, "unit": "% of AI answers with a hallucination or significant error on realistic professional questions", "display": "17–45% of AI answers had a hallucination or significant error, in independent tests (2024 to 2025)" }, "confidence": "medium", "confidence_reason": "Two independent creators using expert human grading find serious-error rates in this band for question answering. The tasks, error definitions and models differ, the tests are one to two years old, and rates move quickly with each model release.", "last_checked": "2026-10-14", "how_to_read": "Each test sets a different task and defines an error differently, and humans grade all three. Dates matter: the legal tools were tested in 2024 and have been updated since, and in the BBC's own comparison significant issues fell from 51% to 37% in six months. The citation test asks AI to find the source of a quote, a narrow task, so it sits above the range. Error rates depend heavily on whether the AI is given the source material.", "sources": [ { "creator": "Varun Magesh, Faiz Surani, Matthew Dahl, Mirac Suzgun, Christopher D. Manning and Daniel E. Ho (Stanford RegLab and Yale)", "title": "Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools (Journal of Empirical Legal Studies)", "year": 2025, "sample": "202 preregistered legal research queries per system, tested March to May 2024", "method": "Hand-graded by experts. Hallucinated means incorrect, or citing a source that does not support the claim.", "figure": "Lexis+ AI 17%, Ask Practical Law AI 17%, Westlaw AI-Assisted Research 33% hallucinated; GPT-4 without retrieval 43%", "url": "https://doi.org/10.1111/jels.12413", "quote": "each hallucinate between 17% and 33% of the time" }, { "creator": "European Broadcasting Union and BBC, with 22 public service media organizations", "title": "News Integrity in AI Assistants: An international PSM study", "year": 2025, "sample": "2,709 answers from free ChatGPT, Copilot, Gemini and Perplexity, late May to early June 2025, 18 countries", "method": "Journalists rated each answer on accuracy, sourcing, context and more", "figure": "45% had at least one significant issue; 20% a significant accuracy issue; Gemini 76%, Copilot 37%, ChatGPT 36%, Perplexity 30%", "url": "https://www.ebu.ch/files/live/sites/ebu/files/Publications/MIS/open/EBU-MIS-BBC_News_Integrity_in_AI_Assistants_Report_2025.pdf", "quote": "Overall, 45% of all AI responses were found to have at least one ‘significant’ issue." }, { "creator": "Klaudia Jaźwińska and Aisvarya Chandrasekar, Tow Center for Digital Journalism", "title": "AI Search Has a Citation Problem (Columbia Journalism Review)", "year": 2025, "sample": "1,600 queries to eight AI search tools, February 2025", "method": "Manual grading of whether each tool identified the source article of a quoted excerpt. A narrow citation task.", "figure": "Incorrect answers to more than 60% of queries; Perplexity 37%, Grok 3 94%", "url": "https://www.cjr.org/tow_center/we-compared-eight-ai-search-engines-theyre-all-bad-at-citing-news.php", "quote": "Collectively, they provided incorrect answers to more than 60 percent of queries." } ], "related_findings": [ { "question": "How often does AI invent content when summarizing a document?", "answer": "Much less often than when answering from its own knowledge. On Vectara's leaderboard of 22 September 2026, 108 models added unsupported content to 1.8% to 24.2% of summaries, with a median of about 9.6% and frontier models at about 6% to 12%. The judging is done by Vectara's own detection model, not by people.", "sources": [ { "creator": "Vectara", "title": "Hallucination Leaderboard (HHEM-2.3)", "year": 2026, "sample": "Over 7,700 articles summarized by each of 108 models; leaderboard dated 22 September 2026", "method": "Automated benchmark judged by Vectara's own detection model. Vectara sells retrieval and hallucination-detection products.", "figure": "Hallucination rates from 1.8% to 24.2% of summaries; median about 9.6%", "url": "https://github.com/vectara/hallucination-leaderboard", "quote": "This evaluates how often an LLM introduces hallucinations when summarizing a document." } ] }, { "question": "How often can AI agents complete whole work projects?", "answer": "Rarely, but fast-rising. On the Remote Labor Index, which gives AI agents real paid freelance projects averaging 29 hours of human work, the best agent delivered work a client would accept on 21.25% of projects as of 14 October 2026, up from 2.5% at launch in October 2025.", "sources": [ { "creator": "Center for AI Safety and Scale AI", "title": "Remote Labor Index: Measuring AI Automation of Remote Work", "year": 2026, "sample": "230 real freelance projects in design, data analysis, game development, video and more", "method": "Human evaluators judged whether each AI deliverable matched the professional's and was acceptable as commissioned work. Scale AI sells AI evaluation.", "figure": "Best agent 21.25% of projects (read 14 October 2026); 2.5% at launch in October 2025", "url": "https://labs.scale.com/leaderboard/rli", "quote": "The best-performing model achieves an automation rate of only 21.25%." } ] } ], "numbers_you_may_have_seen": [ { "claim": "AI assistants get the news wrong 45% of the time (EBU and BBC).", "what_the_source_says": "45% of answers had at least one significant issue of any kind, mostly sourcing. Significant accuracy errors were 20%." }, { "claim": "AI search engines are wrong 60% of the time (Tow Center).", "what_the_source_says": "The test asked eight tools to find the source article of a quoted excerpt. It measures news citation, not general accuracy." }, { "claim": "Legal AI tools are hallucination-free.", "what_the_source_says": "Stanford's preregistered test found the tools hallucinated on 17% to 33% of queries. Vendor wording refers to whether linked citations exist, a narrower claim." }, { "claim": "Chatbots hallucinate up to 27% of the time (Vectara).", "what_the_source_says": "That comes from 2023 coverage of Vectara's first leaderboard. In September 2026 the range across 108 models was 1.8% to 24.2%, on a new test." }, { "claim": "AI can do only 2.5% of remote work.", "what_the_source_says": "2.5% was the best agent at the Remote Labor Index launch in October 2025. In October 2026 it was 21.25%, counting whole projects done to client standard." } ], "citation": "EVY (2026). How often is AI output wrong on real work tasks? The AI at Work Fact Book, F-23. https://evy.so/facts/ai-error-rates-at-work/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-24", "url": "https://evy.so/facts/tasks-workers-want-ai-to-do/", "chapter": "What Teams Trust", "question": "Which work tasks do people want AI to do on its own, and which do they want to keep?", "answer": "Very few want AI working fully on its own: about 2 percent, in two independent studies. People welcome AI help on many tasks, mostly repetitive ones, and most prefer an equal partnership with AI, while keeping decisions about people, communication and creative control.", "range": { "low": 2, "high": 12, "unit": "% of workers or occupations whose preferred setup gives AI the sole role (about 2%) or the leading role (12%)", "display": "2–12% want AI to work alone (about 2%) or to lead (up to 12%)" }, "confidence": "medium", "confidence_reason": "Two independent academic studies with different methods agree that only about 2% want AI acting fully alone. Beyond that the measures differ: one covers everyday tasks, the other only decisions about people, and both are stated preferences.", "last_checked": "2026-10-14", "how_to_read": "The Stanford study rates everyday tasks across the US workforce; the KPMG question covers only decisions about people. Stanford's 46% is a share of listed tasks, not of work time, and only 7.1% of tasks got a strong vote for automation. All of these are stated preferences, which can differ from what people actually hand to AI. The pattern across sources: people want AI to take repetitive, checkable work and to leave decisions about people, communication and creative control with them.", "sources": [ { "creator": "Yijia Shao, Erik Brynjolfsson, Diyi Yang and colleagues (Stanford University)", "title": "Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce (WORKBank)", "year": 2026, "sample": "1,500 US workers in 104 occupations rating 844 tasks, January to May 2025", "method": "Online survey with audio interviews; preferred level of human involvement per task. Preprint.", "figure": "AI handles it entirely is the preferred level in 1.9% of occupations; equal partnership in 45.2%; workers favor automation for 46.1% of tasks", "url": "https://arxiv.org/abs/2506.06576", "quote": "For 46.1% of tasks, workers express positive attitudes toward AI agent automation" }, { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Most acceptable human-AI split for managerial decisions on hiring, pay, promotion and allocating work", "figure": "AI 100%: 2%; AI 75%: 10%; equal: 29%; humans 75%: 45%; humans 100%: 14%", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "Only ten percent believe AI should dominate managerial decision-making" }, { "creator": "Stack Overflow", "title": "2026 Developer Survey: AI data", "year": 2026, "sample": "12,547 developers answering this question, June to August 2026", "method": "Opt-in survey; tasks developers do not use AI for and do not plan to", "figure": "Writing communications 45.9%; running production systems 36.0%; writing tickets and plans 30.5%; writing tests 8.5%", "url": "https://survey.stackoverflow.co/2026/ai/data", "quote": "46% do not use AI there and do not plan to" } ], "related_findings": [ { "question": "Which tasks do people most want to keep for themselves?", "answer": "Tasks involving people, judgment and creative control. Arts, design and media workers favored automation for only 17.1% of their tasks (Stanford). 71% of Americans opposed AI making final hiring decisions (Pew, December 2022). 46% of developers do not use AI for writing communications and do not plan to.", "sources": [ { "creator": "Pew Research Center", "title": "AI in Hiring and Evaluating Workers: What Americans Think", "year": 2023, "sample": "11,004 US adults, December 2022", "method": "American Trends Panel, probability-based. An older wave of all adults.", "figure": "71% oppose AI making final hiring decisions; 7% favor it", "url": "https://www.pewresearch.org/internet/2023/04/20/ai-in-hiring-and-evaluating-workers-what-americans-think/", "quote": "they oppose AI use in making final hiring decisions by a 71%-7% margin" } ] }, { "question": "Why do workers want AI to take over some tasks?", "answer": "Mainly to free time for higher-value work (69.4% of the reasons given in the Stanford study), and because tasks are repetitive (46.6%) or AI could improve quality (46.6%). Among workers voicing concerns, the top one was lack of trust in AI's accuracy or reliability (45.0%).", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Workers want AI to automate 46% of their jobs (Stanford).", "what_the_source_says": "46.1% is the share of 844 listed tasks whose average rating leans toward automation, not weighted by time. Only 7.1% got a strong vote." }, { "claim": "75% of employees are comfortable working with AI agents (Workday).", "what_the_source_says": "The sample was 2,950 decision-makers and software implementation leaders, in a vendor survey. It does not describe the general workforce." }, { "claim": "Only 10% of employees trust AI to make decisions (KPMG).", "what_the_source_says": "The question covered only managerial decisions about people. 10% chose AI with 75% of the say and 2% AI alone; 29% chose an even split." } ], "citation": "EVY (2026). Which work tasks do people want AI to do on its own, and which do they want to keep? The AI at Work Fact Book, F-24. https://evy.so/facts/tasks-workers-want-ai-to-do/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-25", "url": "https://evy.so/facts/ai-use-against-company-policy/", "chapter": "What Teams Trust", "question": "How many workers use AI in ways that break company policy?", "answer": "About three to four in ten workers have used AI in ways that break company policy: 44 percent of AI-using employees say so themselves, and IT leaders estimate about 30 percent. Missing rules are a big part of it: 56 percent have used AI without knowing whether it was allowed, and only 38 to 44 percent of organizations have a formal AI policy.", "range": { "low": 30, "high": 44, "unit": "% of workers who have used AI against company policy", "display": "30–44% of workers have used AI against company policy (44% self-reported, about 30% by IT leaders' estimate)" }, "confidence": "medium", "confidence_reason": "Two independent creators using different methods land in the same band: employees asked directly, and IT leaders estimating for their staff. Self-reports likely understate rule-breaking, and two of the creators sell products that address it.", "last_checked": "2026-10-14", "how_to_read": "Two of these count workers: the employee self-report (44%) and the IT-leader estimate (about 30%). The third is a stated intention, not a count of violations. Many breaches come from unclear rules: most outside-tool use happens where no explicit rule exists, and bans tend to push use out of sight, since uploading company data is most common where AI is banned (67%). Chapter 3 covers how many people bring their own AI at all.", "sources": [ { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Anonymous online survey of employees who use AI; self-reported frequency", "figure": "44% have used AI in ways that contravene policies or guidelines (31% sometimes or more often); 56% have used AI without knowing whether it was allowed", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "almost half admit to using AI in ways that contravene organizational policies" }, { "creator": "GoTo with Workplace Intelligence", "title": "The Pulse of Work in 2026: Opportunity, Risk, and Responsibility in an AI-Driven Workplace", "year": 2026, "sample": "1,250 IT decision-makers and 1,250 knowledge workers in 10 countries, November 2025 to January 2026", "method": "Online survey; IT leaders estimated the share of workers who violated AI policy. GoTo sells IT software.", "figure": "IT leaders estimate around 3 in 10 workers have violated their company's AI policy; 44% say their company has an AI policy", "url": "https://edge.sitecorecloud.io/gototechnol00e8-mktglobalxm07e7-mktglobalpr9498-b870/media/goto/pdfs/ebook/ebook_pulse-of-work-2026.pdf", "quote": "around 3 out of 10 workers have violated their company’s AI policy" }, { "creator": "Software AG, survey by TEAM LEWIS", "title": "Half of all employees are Shadow AI users, new study finds", "year": 2024, "sample": "6,000 knowledge workers in the US, UK and Germany, September 2024", "method": "Online panel survey; a hypothetical question", "figure": "46% would not give up their personal AI tools even if their organization banned them", "url": "https://newscenter.softwareag.com/en/news-stories/press-releases/2024/1022-half-of-all-employees-use-shadow-ai.html", "archive_url": "https://web.archive.org/web/20251105024925/https://newscenter.softwareag.com/en/news-stories/press-releases/2024/1022-half-of-all-employees-use-shadow-ai.html", "quote": "46% wouldn’t give it up, even if it were banned" } ], "related_findings": [ { "question": "How many organizations see prohibited AI use?", "answer": "Most. 69% of organizations suspect or have evidence that employees use prohibited public generative AI (Gartner, 302 security leaders, 2025), and 60% of leaders lack confidence that they could even identify unapproved AI tools in their environment (Cisco, 8,000 leaders, 2025).", "sources": [ { "creator": "Gartner", "title": "Gartner Identifies Critical GenAI Blind Spots That CIOs Must Urgently Address", "year": 2025, "sample": "302 cybersecurity leaders, March to May 2025", "method": "Survey reported in a press release; counts organizations, not workers. Gartner sells research.", "figure": "69% of organizations suspect or have evidence of prohibited public generative AI use", "url": "https://www.gartner.com/en/newsroom/press-releases/2025-11-19-gartner-identifies-critical-genai-blind-spots-that-cios-must-urgently-address0", "quote": "69% of organizations suspect or have evidence that employees are using prohibited public GenAI" }, { "creator": "Cisco", "title": "2025 Cisco Cybersecurity Readiness Index", "year": 2025, "sample": "8,000 business leaders with security responsibilities in 30 markets, early 2025", "method": "Double-blind survey. Cisco sells security products.", "figure": "60% lack confidence in identifying unapproved AI tools; 22% give employees unrestricted access to public AI tools", "url": "https://newsroom.cisco.com/c/dam/r/newsroom/en/us/interactive/cybersecurity-readiness-index/2025/documents/2025_Cisco_Cybersecurity_Readiness_Index.pdf", "quote": "lack confidence in their ability to identify the use of unapproved AI tools" } ] }, { "question": "How many organizations have an AI policy?", "answer": "Fewer than half. 38% of organizations have a formal, comprehensive AI policy, up from 28% a year earlier, 30% have a limited one and 25% none (ISACA, 2026). In GoTo's survey, 44% of IT leaders said their company has an AI policy.", "sources": [ { "creator": "ISACA", "title": "2026 AI Pulse Poll", "year": 2026, "sample": "More than 3,400 digital trust professionals worldwide", "method": "Poll of IT audit, governance, security and privacy professionals", "figure": "38% have a formal, comprehensive AI policy; 30% limited; 25% none", "url": "https://www.isaca.org/about-us/newsroom/press-releases/2026/ai-use-accelerates-while-governance-and-roi-lag-says-new-isaca-research", "quote": "only 38 percent of organizations have a formal, comprehensive AI policy" } ] } ], "numbers_you_may_have_seen": [ { "claim": "44% of workers knowingly break AI rules (KPMG).", "what_the_source_says": "The 44% is of employees who use AI, counts anyone who did it even rarely, and does not say knowingly. Sometimes or more often is 31%." }, { "claim": "69% of employees use banned AI (Gartner).", "what_the_source_says": "It is 69% of organizations whose security leaders suspect or have evidence of any prohibited use." }, { "claim": "70% of employees misuse AI at work (GoTo).", "what_the_source_says": "GoTo counts using AI for task types it labels sensitive. Only 22% of those employees knew their employer prohibited it." }, { "claim": "Over 40% of enterprises will have shadow AI incidents (Gartner).", "what_the_source_says": "This is a forecast for 2030." } ], "citation": "EVY (2026). How many workers use AI in ways that break company policy? The AI at Work Fact Book, F-25. https://evy.so/facts/ai-use-against-company-policy/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-26", "url": "https://evy.so/facts/company-data-in-public-ai/", "chapter": "What Teams Trust", "question": "How often do employees put company data into public AI tools?", "answer": "A little under half of workers say they have put company information into public AI tools: 48 percent of AI-using employees, and 42 percent of privacy and security professionals themselves. Monitoring software confirms it happens routinely, and a third to a half of AI use at work runs through personal accounts.", "range": { "low": 42, "high": 48, "unit": "% of surveyed workers who have put non-public company information into public AI tools", "display": "42–48% of workers say they have put company information into public AI tools (2024 to 2025)" }, "confidence": "medium", "confidence_reason": "Two independent self-report surveys with different populations agree closely. Monitoring data from four security vendors confirms the behavior, but each counts something different and draws on its own customers.", "last_checked": "2026-10-14", "how_to_read": "The two surveys ask people about their own behavior; one covers employees in all jobs, the other privacy and security professionals. Monitoring data from security vendors (below) counts events in their customers' systems and cannot be put on the same scale: one counts interactions, another prompts or files, another users. Every monitoring source sells the product that produced its data. Uploading is most common where AI is banned (67%), which suggests bans push use out of sight.", "sources": [ { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "32,352 employed people in 47 countries, November 2024 to January 2025", "method": "Anonymous online survey of employees who use AI; self-reported", "figure": "48% have uploaded company information such as financial, sales or customer data into a public AI tool (34% sometimes or more often)", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "report that they have uploaded company information, such as financial, sales, or customer information" }, { "creator": "Cisco", "title": "Cisco 2025 Data Privacy Benchmark Study", "year": 2025, "sample": "More than 2,600 privacy and security professionals in 12 countries, fall 2024", "method": "Double-blind survey of what respondents themselves entered into generative AI apps. Cisco sells security products.", "figure": "42% entered non-public information about their company (48% in the 2024 edition); 46% employee information; 31% customer information", "url": "https://www.cisco.com/c/dam/en_us/about/doing_business/trust-center/docs/cisco-privacy-benchmark-study-2025.pdf", "archive_url": "https://web.archive.org/web/2025id_/https://www.cisco.com/c/dam/en_us/about/doing_business/trust-center/docs/cisco-privacy-benchmark-study-2025.pdf", "quote": "nearly half of respondents still reported inputting personal employee information or non-public" } ], "related_findings": [ { "question": "What does monitoring software show about company data in AI tools?", "answer": "That sensitive data reaches AI tools routinely, at rates that depend on what is counted. 39.7% of employee interactions with AI tools involved data the customer labeled sensitive (Cyberhaven, 2025 data). About 2.6% of all prompts and uploads were sensitive, but 26% of uploaded files were (Harmonic Security, 2025). The average organization logged 223 attempts a month to send sensitive data to AI apps, made by about 3% of its AI users (Netskope). All three are vendor data from their own customers.", "sources": [ { "creator": "Cyberhaven Labs", "title": "2026 AI Adoption & Risk Report", "year": 2026, "sample": "Hundreds of thousands of employees at 222 companies, AI usage during 2025", "method": "Vendor telemetry of data moving into AI tools. Cyberhaven sells data security software.", "figure": "39.7% of employee AI interactions involve sensitive data; personal-account share of use: ChatGPT 32.3%, Claude 58.2%, Perplexity 60.9%", "url": "https://info.cyberhaven.com/hubfs/Webflow_Resources/Cyberhaven-AI-Risk-Report-2026.pdf", "quote": "the average employee enters sensitive data into AI tools once every three days" }, { "creator": "Harmonic Security", "title": "What 22 Million Enterprise AI Prompts Reveal About Shadow AI in 2025", "year": 2026, "sample": "22.5 million prompts and uploads across 665 AI tools, 2025, US and UK customers", "method": "Vendor telemetry from browser monitoring. Harmonic sells AI data protection software.", "figure": "579,113 sensitive exposures in 22.5 million prompts and uploads (about 2.6%); 26% of uploaded files in Q3 2025", "url": "https://www.harmonic.security/resources/what-22-million-enterprise-ai-prompts-reveal-about-shadow-ai-in-2025", "quote": "Sensitive Data Instances: 579,113 detected exposures" }, { "creator": "Netskope Threat Labs", "title": "Cloud and Threat Report: 2026", "year": 2026, "sample": "Anonymized data from Netskope customers, October 2024 to October 2025", "method": "Vendor telemetry of data policy violations, only where customers have rules in place. Netskope sells security software.", "figure": "About 3% of AI users commit an average of 223 data policy violations a month per organization; 47% of AI users use personal AI apps", "url": "https://www.netskope.com/resources/cloud-and-threat-reports/cloud-and-threat-report-2026", "quote": "3% of genAI users committing an average of 223 genAI data policy violations" } ] }, { "question": "How much AI use at work runs through personal accounts?", "answer": "A third to a half, depending on the tool and the vendor. 47% of AI users used personal AI apps in 2025 and 44% in mid-2026 (Netskope). 32.3% of ChatGPT use and about 60% of Claude and Perplexity use at work ran through personal accounts (Cyberhaven). Data security leaders estimate that 58% of employees use personal credentials for work AI (Microsoft, 2026).", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "48% of employees enter non-public company information into AI (Cisco).", "what_the_source_says": "Cisco's respondents were privacy and security professionals reporting their own behavior, in the 2024 edition. The 2025 figure is 42%." }, { "claim": "77% of employees paste company data into ChatGPT (LayerX).", "what_the_source_says": "LayerX gives no denominator, so the figure can only describe AI users, and it counts any paste into any AI tool." }, { "claim": "40% of employees leak sensitive data into AI (Cyberhaven).", "what_the_source_says": "39.7% is the share of AI interactions that involve data the customer labeled sensitive. It is not a share of employees." }, { "claim": "Companies see 223 AI data leaks a month (Netskope).", "what_the_source_says": "223 is the average number of detected policy violations per organization, made by about 3% of AI users, and only where rules exist." } ], "citation": "EVY (2026). How often do employees put company data into public AI tools? The AI at Work Fact Book, F-26. https://evy.so/facts/company-data-in-public-ai/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-27", "url": "https://evy.so/facts/ai-security-breaches/", "chapter": "What Teams Trust", "question": "How many organizations have had a security incident or data breach involving AI?", "answer": "About one in five to three in ten organizations report a breach of, or attack on, their own AI systems in the past year: 21 percent of breached organizations in IBM's 2026 study and 29 percent in Gartner's 2025 survey. Employees' unapproved AI was involved in 43 percent of the breaches IBM studied, up from 20 percent.", "range": { "low": 21, "high": 29, "unit": "% of organizations reporting a breach of, or attack on, their own AI in the past 12 months", "display": "21–29% of organizations report a breach of, or attack on, their own AI systems (2025 to 2026)" }, "confidence": "medium", "confidence_reason": "Two independent creators with different methods land close together, though IBM counts breaches among organizations that had one and Gartner counts attacks, successful or not. Both are commercial research, and no government statistic counts AI breaches yet.", "last_checked": "2026-10-14", "how_to_read": "Keep three kinds of AI incident apart: attacks on an organization's own AI, incidents caused by employees' AI use, and attacks that use AI against the company, such as deepfakes. The range covers the first. IBM's sample includes only organizations that had a breach, so its shares are not of all organizations. Broad figures that mix all three run far higher (Cisco: 86% of leaders report any AI-related incident). All sources are vendor or analyst research.", "sources": [ { "creator": "IBM and Ponemon Institute", "title": "Cost of a Data Breach Report 2026", "year": 2026, "sample": "602 organizations breached between March 2025 and February 2026; 3,558 interviews in 16 countries and regions", "method": "Interviews about one breach at each organization, so shares are of breached organizations. IBM sells security software and services.", "figure": "21% had a security incident involving their AI models or applications (13% in 2025); 92% of those lacked proper AI access controls; shadow AI involved in 43% of breaches (20% in 2025)", "url": "https://www.ibm.com/reports/data-breach", "quote": "AI-related breaches grew to 21% this year from 13% last year." }, { "creator": "Gartner", "title": "Gartner Survey Reveals GenAI Attacks Are on the Rise", "year": 2025, "sample": "302 cybersecurity leaders in North America, EMEA and Asia/Pacific, March to May 2025", "method": "Survey reported in a press release; attacks experienced, whether or not they succeeded. Gartner sells research.", "figure": "29% faced an attack on generative AI application infrastructure; 32% an attack using an AI application's prompt; 62% a deepfake attack", "url": "https://www.gartner.com/en/newsroom/press-releases/2025-09-22-gartner-survey-reveals-generative-artificial-intelligence-attacks-are-on-the-rise", "quote": "experienced an attack on enterprise GenAI application infrastructure in the last 12 months" }, { "creator": "Microsoft, survey by Hypothesis Group", "title": "2026 Data Security Index", "year": 2026, "sample": "1,725 data security leaders in 10 countries, July to August 2025", "method": "Online survey; a share of incidents, not of organizations. Microsoft sells data security products.", "figure": "32% of organizations' data security incidents involve the use of generative AI tools", "url": "https://marketingassets.microsoft.com/gdc/gdccYW33N/original", "quote": "a third (32%) of data security incidents involve use of GenAI tools" } ], "related_findings": [ { "question": "How much do employees' unapproved AI tools add to breaches?", "answer": "More each year. Shadow AI, where workers use AI their employer has not approved, was involved in 43% of the breaches IBM studied in 2026, up from 20%. Those incidents averaged USD 5.39 million, against USD 4.99 million for a breach overall, and about one in five led to a regulatory fine. 68% of breached organizations lacked AI governance policies.", "sources": [] }, { "question": "How many organizations face attacks that use AI?", "answer": "Most. 62% of organizations faced a deepfake attack in the past year (Gartner, 2025), and 86% of business leaders reported at least one AI-related security incident, a broad category that includes AI-written phishing (Cisco, 2025). The UK's official breaches survey does not yet ask about AI breaches; it finds that 24% of businesses using or considering AI have practices to manage its cyber risks.", "sources": [ { "creator": "Cisco", "title": "2025 Cisco Cybersecurity Readiness Index", "year": 2025, "sample": "8,000 business leaders with security responsibilities in 30 markets, early 2025", "method": "Double-blind survey; any AI-related incident, including attacks that use AI. Cisco sells security products.", "figure": "86% reported at least one AI-related security incident in the past 12 months", "url": "https://newsroom.cisco.com/c/dam/r/newsroom/en/us/interactive/cybersecurity-readiness-index/2025/documents/2025_Cisco_Cybersecurity_Readiness_Index.pdf", "quote": "reported at least one AI related incident in the past 12 months" }, { "creator": "UK Department for Science, Innovation and Technology and Home Office", "title": "Cyber security breaches survey 2025/2026", "year": 2026, "sample": "2,112 UK businesses and 1,085 charities, August to December 2025", "method": "Official statistics, random probability survey", "figure": "24% of businesses using or considering AI have cyber security practices to manage AI risks", "url": "https://www.gov.uk/government/statistics/cyber-security-breaches-survey-20252026/cyber-security-breaches-survey-20252026", "quote": "around a quarter of businesses (24%) and charities (27%) reported having cyber security practices" } ] } ], "numbers_you_may_have_seen": [ { "claim": "13% of organizations have had an AI breach (IBM).", "what_the_source_says": "IBM studies only organizations that had a breach, and the 13% was 2025. The 2026 edition reports 21%." }, { "claim": "97% of organizations lack AI access controls (IBM).", "what_the_source_says": "The 97% (2025) was of organizations that had an AI breach; it is 92% in 2026. Across all organizations studied, 40% use AI access controls." }, { "claim": "Shadow AI adds $670,000 to the cost of a breach (IBM).", "what_the_source_says": "That 2025 comparison was one of two analyses; the other gave about $200,000. In 2026 shadow AI incidents averaged $5.39 million against $4.99 million overall." }, { "claim": "86% of organizations have suffered AI security incidents (Cisco).", "what_the_source_says": "It counts any AI-related incident reported by leaders, including AI-enhanced phishing aimed at the company. It is not breaches of the company's own AI." }, { "claim": "99% of companies have lost money because of AI (EY).", "what_the_source_says": "EY's respondents were executives at firms above $1 billion revenue, reporting any loss from any AI risk, mostly regulatory and sustainability setbacks." } ], "citation": "EVY (2026). How many organizations have had a security incident or data breach involving AI? The AI at Work Fact Book, F-27. https://evy.so/facts/ai-security-breaches/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-28", "url": "https://evy.so/facts/small-companies-share-of-economy/", "chapter": "Small Teams", "question": "How much of the economy do small companies make up?", "answer": "Companies with fewer than 50 people are 96 to 99 percent of all businesses in the US, EU and UK. They employ about a quarter of US employer-firm workers (26 percent) and nearly half of people working in the EU and UK business economy (47 to 48 percent, counting the self-employed).", "range": { "low": 96.1, "high": 99.3, "unit": "% of businesses with fewer than 50 employees", "display": "96–99% of businesses have fewer than 50 people; they employ 26% (US) to 48% (EU) of workers" }, "confidence": "high", "confidence_reason": "Four official sources built from business registers agree closely on the share of firms. Employment shares differ widely, but the reasons are known: whether the self-employed and one-person firms are counted, and different size cutoffs.", "last_checked": "2026-10-14", "how_to_read": "Definitions decide the answer. The US Census count covers only firms with paid employees; the EU and UK figures include self-employed owners and one-person firms. That is why the employment share of firms under 50 runs from 26% (US employer firms) to 47 to 48% (UK and EU). The common claim that small businesses employ half of US workers uses the official US definition of small: fewer than 500 employees.", "sources": [ { "creator": "US Census Bureau (Statistics of US Businesses)", "title": "2022 SUSB Annual Data Tables by Enterprise Employment Size", "year": 2025, "sample": "All 6.4 million US employer firms, 2022 (released April 2025, the latest year)", "method": "Official counts from the Business Register; firms with no employees are excluded. Shares are our arithmetic from the size rows.", "figure": "Firms under 50 employees: 96.1% of employer firms, 25.6% of their employment (34.8 million people); under 10 employees: 79.2% of firms", "url": "https://www.census.gov/data/tables/2022/econ/susb/2022-susb-annual.html" }, { "creator": "US Small Business Administration, Office of Advocacy", "title": "Frequently Asked Questions About Small Business (February 2026)", "year": 2026, "sample": "All US firms including 29.8 million businesses with no employees, 2022 data", "method": "Official compilation. Defines small business as fewer than 500 employees; the under-50 share is our arithmetic.", "figure": "Firms under 500 employees: 99.9% of all firms and 45.9% of private-sector employees; including firms with no employees, firms under 50 are about 99.3% of all firms", "url": "https://advocacy.sba.gov/wp-content/uploads/2026/02/FINAL_FAQsAboutSmallBusiness_2026_012826.pdf", "quote": "45.9% of private sector employees (62.3 million workers)" }, { "creator": "Eurostat (Structural Business Statistics)", "title": "Enterprise statistics by size class (dataset sbs_sc_ovw)", "year": 2026, "sample": "All 33 million active enterprises in the EU business economy, 2023", "method": "Official statistics from business registers. Persons employed include working owners. Excludes agriculture and the public sector.", "figure": "Enterprises under 50 persons employed: 99.1% of enterprises, 48.3% of persons employed, 34.9% of value added", "url": "https://ec.europa.eu/eurostat/databrowser/view/sbs_sc_ovw/default/table" }, { "creator": "UK Department for Business and Trade", "title": "Business population estimates for the UK and regions 2025", "year": 2025, "sample": "All 5.7 million UK private-sector businesses, start of 2025", "method": "Official statistics in development; includes sole proprietors and partnerships without employees", "figure": "Businesses with 0 to 49 employees: 99.2% of businesses, 47% of employment, 34% of turnover; 75% of all businesses have no employees", "url": "https://www.gov.uk/government/statistics/business-population-estimates-2025/business-population-estimates-for-the-uk-and-regions-2025-statistical-release", "quote": "there were 5.64 million small businesses (with 0 to 49 employees), 99.18%" } ], "related_findings": [ { "question": "How much do small companies produce?", "answer": "EU firms under 50 people produce 35% of the business economy's value added (2023), and UK businesses under 50 account for 34% of turnover (2025). Using the US definition of small business (under 500 employees), small firms produce 43.5% of US GDP, according to the SBA.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Small businesses employ half of all American workers.", "what_the_source_says": "Firms under 500 employees employ 45.9% of private-sector workers (2022). Firms under 50 employees employ 25.6% of employer-firm workers." }, { "claim": "99.9% of US businesses are small.", "what_the_source_says": "It counts firms under 500 employees and includes 29.8 million businesses with no employees. Among firms with employees, 96.1% have fewer than 50." }, { "claim": "SMEs provide 60% of jobs.", "what_the_source_says": "That counts firms with up to 249 employees. For companies under 50 people it is about 26% (US employer firms) to 47 to 48% (UK, EU)." } ], "citation": "EVY (2026). How much of the economy do small companies make up? The AI at Work Fact Book, F-28. https://evy.so/facts/small-companies-share-of-economy/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-29", "url": "https://evy.so/facts/small-businesses-using-ai/", "chapter": "Small Teams", "question": "What share of small businesses use AI, and for what?", "answer": "Between a fifth and a half of small businesses use AI, 20 to 46 percent in official counts and weighted owner surveys from 2025 to 2026, mostly for writing and marketing. Use is shallow: only 7 percent of AI-using US small firms have fully built it into how they work.", "range": { "low": 20, "high": 46, "unit": "% of small businesses using AI (official counts and weighted owner surveys, 2025 to 2026)", "display": "20–46% of small businesses use AI (official counts and weighted owner surveys; vendor surveys report 66 to 77%)" }, "spread": { "low": 20, "high": 77, "unit": "% of small businesses" }, "confidence": "medium", "confidence_reason": "Many independent creators report figures, and they agree on how small firms use AI. The level is uncertain because official surveys ask whether the business uses AI, while owner surveys count any use by anyone at the firm, and size cutoffs differ.", "last_checked": "2026-10-14", "how_to_read": "Read the figures in three tiers and do not average them: official counts for the smallest firms (20 to 29%), weighted owner surveys (24 to 46%) and vendor or advocacy surveys (66 to 77%). Official surveys ask whether the business uses AI, which owners often answer no when only individuals use a chatbot; owner surveys that count anyone at the firm, or AI features inside other software, come out higher. Online panels and program alumni lean toward tech-forward owners.", "sources": [ { "creator": "US Census Bureau", "title": "Business Trends and Outlook Survey (BTOS), employment size class estimates", "year": 2026, "sample": "About 20,000 responses per two-week period; collection ending 4 October 2026", "method": "Official experimental survey; AI used in any business function in the prior two weeks", "figure": "1 to 4 employees 23.9%; 5 to 9: 21.5%; 10 to 19: 22.4%; 20 to 49: 24.8%", "url": "https://www.census.gov/hfp/btos/data", "quote": "did this business use Artificial Intelligence (AI) in any of its business functions?" }, { "creator": "Office for National Statistics (UK)", "title": "Business insights and impact on the UK economy: 8 October 2026", "year": 2026, "sample": "UK business survey, wave live 21 September to 4 October 2026", "method": "Official statistics; current use of at least one listed AI technology", "figure": "28.7% of businesses with 0 to 9 employees and 36.1% with 10 to 49 used AI", "url": "https://www.ons.gov.uk/businessindustryandtrade/business/businessservices/bulletins/businessinsightsandimpactontheukeconomy/8october2026", "quote": "only 29% of businesses with fewer than 10 employees reported using AI technologies" }, { "creator": "Statistics Canada", "title": "Analysis on artificial intelligence use by businesses in Canada, second quarter of 2026", "year": 2026, "sample": "9,251 responding businesses, April to May 2026", "method": "Official survey; AI used to produce goods or deliver services in the past 12 months", "figure": "19.9% of businesses with 1 to 4 employees used AI; 41.4% say it is not relevant to them", "url": "https://www150.statcan.gc.ca/n1/pub/11-621-m/11-621-m2026010-eng.htm", "quote": "Among businesses with 1 to 4 employees, about one-fifth (19.9%) reported using AI" }, { "creator": "NFIB Research Center", "title": "Small Business and Technology Survey (2025)", "year": 2025, "sample": "521 NFIB member employers, March 2025", "method": "Membership survey with a low response rate; run by a business advocacy group", "figure": "24% of small employers use AI; 21% of firms under 10 employees, 48% of firms with 50 or more", "url": "https://www.nfib.com/news/press-release/new-nfib-report-how-small-businesses-incorporate-tech-and-ai-advancements/", "quote": "ranging from 21% uptake for single-digit employee firms to 48% at 50+ employee firms" }, { "creator": "OECD, survey by Ipsos", "title": "Generative AI and the SME Workforce: New Survey Evidence", "year": 2025, "sample": "5,232 SMEs in seven countries, October to December 2024", "method": "Random telephone survey weighted by number of firms; any staff use of generative AI", "figure": "30.7% of SMEs use generative AI; one-person companies 23.6%, firms with 50 to 249 employees 45.8%", "url": "https://www.oecd.org/en/publications/generative-ai-and-the-sme-workforce_2d08b99d-en/full-report/component-4.html", "quote": "It is in use (by the respondent or a colleague) in 31% of SMEs" }, { "creator": "Federal Reserve Banks", "title": "2026 Report on Employer Firms (2025 Small Business Credit Survey)", "year": 2026, "sample": "6,525 US employer firms with 1 to 499 employees, September to November 2025", "method": "Weighted convenience sample; counts any use by the business or its employees, including AI inside existing software", "figure": "46% of employer firms use AI; of users, 49% experimenting, 44% partly integrated, 7% fully integrated", "url": "https://www.fedsmallbusiness.org/-/media/project/clevelandfedtenant/fsbsite/reports/2026/2026-report-on-employer-firms/2026-report-on-employer-firms.pdf", "quote": "46% of employer firms reported that their business or employees were using" }, { "creator": "US Chamber of Commerce Technology Engagement Center, with Teneo Research", "title": "Empowering Small Business: The Impact of Technology on U.S. Small Business (2026)", "year": 2026, "sample": "Online survey of US small businesses under 250 employees, July to August 2026", "method": "Non-probability online survey by a business lobby group", "figure": "66% use some AI tool; 41% a generative AI chatbot", "url": "https://www.uschamber.com/assets/documents/Empowering-Small-Business-The-Impact-of-Technology-on-U.S.-Small-Business-Small-Business-Report-2026.pdf", "quote": "2/3 of small businesses now use AI." }, { "creator": "Intuit QuickBooks, with economists at the University of Chicago", "title": "2026 AI Impact Report", "year": 2026, "sample": "2,222 US owners of businesses with 0 to 100 employees, January 2026; plus payment data on 4.3 million businesses", "method": "Paid panel and Intuit customers; any AI use at least monthly. Intuit sells AI features in QuickBooks.", "figure": "77% use AI regularly; in Intuit's payment data, 12% of US businesses paid for a dedicated AI tool between 2021 and 2025", "url": "https://www.intuit.com/blog/global-stories/ai-impact-report/", "quote": "77% of US businesses now use AI regularly, up from 48% in July 2024." } ], "related_findings": [ { "question": "What do small businesses use AI for?", "answer": "Writing and marketing first, in every source. Among AI-using US employer firms, 83% use it for writing or marketing, 61% for individual productivity, 51% for planning or analysis, 38% for admin and 19% for coding (Federal Reserve, 2025). Across seven OECD countries, 92% of SME users generate text, and only 29% use generative AI in core business activities.", "sources": [] }, { "question": "How many small businesses pay for AI tools, and how much do they spend?", "answer": "About half of the small businesses on Ramp, a spend-management platform: 50.1% of firms with 1 to 24 employees had a paid AI transaction in August 2026, up from 39.7% a year earlier. The median small firm on Ramp spent about $23 per employee per month, roughly $230 a month for a 10-person team. Ramp's customers are more tech-minded than typical small firms, so the share across all small businesses is likely lower: in Census data, only 8 to 9% of AI-using US firms under 50 employees bought software or equipment to use AI.", "confidence": "low", "sources": [ { "creator": "Ramp Economics Lab", "title": "Ramp AI Index", "year": 2026, "sample": "More than 70,000 US businesses on Ramp; small means 1 to 24 employees", "method": "Measured card and bill-pay transactions to AI products. Misses free tools and personal accounts. Ramp sells corporate cards and spend software.", "figure": "50.1% of small businesses paid for AI in August 2026 (medium 62.5%, large 66.8%); median AI spend $23.23 per employee per month for small firms", "url": "https://ramp.com/data/ai-index", "quote": "Share of businesses with spending on AI models, subscriptions, tokens, and APIs" }, { "creator": "US Census Bureau", "title": "BTOS AI Supplement Table 2026", "year": 2026, "sample": "More than 117,000 responding US firms, November 2025 to February 2026", "method": "Official survey of what AI-using firms changed in order to use AI", "figure": "7.6 to 8.8% of AI-using firms under 50 employees bought computing power, equipment or software; about two thirds made no changes", "url": "https://www.census.gov/hfp/btos/downloads/AI_Supplement_Table_2026.xlsx", "quote": "to use Artificial Intelligence (AI), what changes did this business make?" } ] } ], "numbers_you_may_have_seen": [ { "claim": "58% of small businesses use generative AI (US Chamber of Commerce).", "what_the_source_says": "That was the 2025 edition. The 2026 edition says 66% use some AI tool, and 41% use a generative AI chatbot." }, { "claim": "77% of small businesses use AI (Intuit).", "what_the_source_says": "It counts any AI use at least monthly, including features inside other tools, from a paid panel and Intuit customers. Intuit's payment data show 12% paid for a dedicated AI tool." }, { "claim": "76% of small businesses use AI (Goldman Sachs).", "what_the_source_says": "The sample is alumni of a Goldman Sachs growth program for small businesses, who are larger and more growth-minded than typical firms." }, { "claim": "Nearly half of small businesses pay for AI.", "what_the_source_says": "That is Ramp's customers with 1 to 24 employees. Ramp's own chart puts the Census estimate of AI use at about 22% for the same month." }, { "claim": "Only 5% of small businesses use AI (Census).", "what_the_source_says": "That was the old question, about AI used to produce goods or services. With the current wording, 21 to 25% of firms under 50 employees use AI." } ], "citation": "EVY (2026). What share of small businesses use AI, and for what? The AI at Work Fact Book, F-29. https://evy.so/facts/small-businesses-using-ai/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-30", "url": "https://evy.so/facts/ai-adoption-by-company-size/", "chapter": "Small Teams", "question": "How does AI adoption differ by company size?", "answer": "Large firms (250 or more employees) are 1.4 to 3.2 times as likely to use AI as small firms, a gap of 13 to 38 percentage points in 2025 to 2026 official statistics. In the US the gap starts only at about 50 employees: firms with 1 to 49 employees all sit at 21 to 25 percent.", "range": { "low": 13, "high": 38, "unit": "percentage-point gap in AI use, large firms (250+) against small firms", "display": "13–38 pts more AI use in large firms than small ones; large firms are 1.4 to 3.2 times as likely" }, "confidence": "high", "confidence_reason": "Four official statistics agencies and an OECD random survey all find adoption rising with firm size. The direction is settled; the size of the gap depends on how each survey defines AI, its time window and its size bands.", "last_checked": "2026-10-14", "how_to_read": "The surveys define AI and time windows differently: any of seven technologies over a year (EU), any business function in two weeks (US), current use (UK), AI in producing goods or services over twelve months (Canada). Size bands differ too, and Canada compares 100+ firms rather than 250+, so its gap sits below the range. All are firm counts, so the many very small firms dominate national averages. The gap is widest for advanced uses such as generating text or code.", "sources": [ { "creator": "US Census Bureau", "title": "Business Trends and Outlook Survey (BTOS), employment size class estimates", "year": 2026, "sample": "About 20,000 responses per two-week period; collection ending 4 October 2026", "method": "Official experimental survey; AI in any business function in the prior two weeks. The 250+ figure is volatile.", "figure": "1 to 49 employees 21.5% to 24.8%; 50 to 99: 29.2%; 100 to 249: 36.4%; 250+: 36.5% (36.5% to 44.0% across the last seven rounds)", "url": "https://www.census.gov/hfp/btos/data", "quote": "did this business use Artificial Intelligence (AI) in any of its business functions?" }, { "creator": "Office for National Statistics (UK)", "title": "Business insights and impact on the UK economy: 8 October 2026", "year": 2026, "sample": "UK business survey, wave live 21 September to 4 October 2026", "method": "Official statistics; current use of at least one listed AI technology", "figure": "0 to 9 employees 28.7%; 10 to 49: 36.1%; 50 to 99: 45.8%; 250+: 50.9%", "url": "https://www.ons.gov.uk/businessindustryandtrade/business/businessservices/bulletins/businessinsightsandimpactontheukeconomy/8october2026", "quote": "Adoption of AI technologies has consistently been higher for larger businesses." }, { "creator": "Eurostat", "title": "Use of artificial intelligence in enterprises", "year": 2025, "sample": "About 157,000 EU enterprises with 10 or more employees, 2025", "method": "Official statistics; any of seven AI technologies during the year. Firms under 10 are not covered.", "figure": "10 to 49 employees 17.0%; 50 to 249: 30.4%; 250+: 55.0%. AI that generates text, speech or code: 7.0% small, 31.7% large", "url": "https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Use_of_artificial_intelligence_in_enterprises", "quote": "large enterprises used AI more than small and medium enterprises" }, { "creator": "Statistics Canada", "title": "Analysis on artificial intelligence use by businesses in Canada, second quarter of 2026", "year": 2026, "sample": "9,251 responding businesses with employees, April to May 2026", "method": "Official survey; AI used to produce goods or deliver services in the past 12 months", "figure": "1 to 4 employees 19.9%; 100 or more employees 27.8%", "url": "https://www150.statcan.gc.ca/n1/pub/11-621-m/11-621-m2026010-eng.htm", "quote": "Over 1 in 4 (27.8%) businesses with 100 or more employees reported using AI" } ], "related_findings": [ { "question": "Do firms with 5 employees use AI less than firms with 40?", "answer": "Barely, in the US. Firms with 1 to 4 employees (23.9%), 5 to 9 (21.5%), 10 to 19 (22.4%) and 20 to 49 (24.8%) all use AI at about the same rate; the step up comes at 50 employees (29.2%) and 100 (36.4%). Within the OECD's seven-country survey, one-person companies use generative AI half as often as firms with 50 to 249 employees (23.6% against 45.8%). Small adopters may use it more intensively: in the UK, 17% of AI-using firms under 10 employees use it extensively, against 9% of firms with 250 or more.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "Firms with at least 20 employees are the biggest AI users (US Census).", "what_the_source_says": "The headline is about a trend from December 2025 to May 2026. In the latest data, firms with 20 to 49 employees (24.8%) sit close to firms with 1 to 4 (23.9%); the step up comes at 50." }, { "claim": "35% of UK businesses use AI.", "what_the_source_says": "That covers businesses with 10 or more employees in June 2026. Including the smallest firms, it was 29% in June and 30% in September 2026." }, { "claim": "Large companies are twice as likely to use AI as SMEs.", "what_the_source_says": "Roughly right but band-dependent. In 2025 to 2026 data the ratio runs from about 1.4 (US, Canada) to 3.2 (EU, 250+ against 10 to 49)." } ], "citation": "EVY (2026). How does AI adoption differ by company size? The AI at Work Fact Book, F-30. https://evy.so/facts/ai-adoption-by-company-size/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-31", "url": "https://evy.so/facts/what-stops-small-companies-adopting-ai/", "chapter": "Small Teams", "question": "What stops small companies from adopting AI?", "answer": "Mostly the belief that AI does not apply to them: 54 to 63 percent of US firms under 50 employees with no AI plans say so, and 57 percent of non-adopting SMEs in seven OECD countries. Lack of knowledge and privacy worries come next, at about one in five each; cost is cited by 6 to 16 percent.", "range": { "low": 54, "high": 63, "unit": "% of small firms with no AI plans that say AI does not apply to their business", "display": "54–63% of small firms with no AI plans say AI does not apply to their business" }, "confidence": "high", "confidence_reason": "Three independent creators with different methods agree that 'does not apply to us' leads by a wide margin. The ranking of the smaller barriers is less stable, because answer lists differ and one survey asks only firms that had considered AI.", "last_checked": "2026-10-14", "how_to_read": "Each source asks a different group. The Census Bureau and the Federal Reserve ask firms with no plans to use AI; the OECD asks non-users; Eurostat (below) asks only non-users that had considered AI, which is why its shares run much higher. Across creators the order holds: AI seems irrelevant, then knowledge gaps and privacy worries, with cost and regulation minor for small firms. Small firms cite privacy less often than large ones (20% against 30% in the Census data).", "sources": [ { "creator": "US Census Bureau", "title": "BTOS AI Supplement Table 2026", "year": 2026, "sample": "More than 117,000 responding US firms, November 2025 to February 2026", "method": "Official survey of firms not planning to use AI in the next six months; several answers allowed", "figure": "AI not applicable: 63.3% (1 to 4 employees) to 58.1% (20 to 49), 42.2% at 250+; lack of knowledge 21 to 23%; privacy 20 to 22%; too expensive 6.7 to 7.3%", "url": "https://www.census.gov/hfp/btos/downloads/AI_Supplement_Table_2026.xlsx", "quote": "AI is not applicable to this business" }, { "creator": "Federal Reserve Banks", "title": "2026 Report on Employer Firms (2025 Small Business Credit Survey)", "year": 2026, "sample": "1,855 US employer firms with no plans to use AI, September to November 2025", "method": "Weighted convenience sample; several answers allowed", "figure": "AI not applicable: 54% to 60% by size band under 50; prefer not to use it 21 to 33%; cost 6 to 16%", "url": "https://www.fedsmallbusiness.org/reports/survey/2026/2026-report-on-employer-firms", "quote": "AI is not applicable to my business" }, { "creator": "OECD, survey by Ipsos", "title": "Generative AI and the SME Workforce", "year": 2025, "sample": "SMEs not using generative AI, from 5,232 surveyed in seven countries, late 2024", "method": "Random telephone survey weighted by number of firms", "figure": "Not suited to the company's work 57.3%; legal or copyright concerns 54.1%; data concerns 52.5%; staff lack skills 49.8%; value for money 21%", "url": "https://www.oecd.org/en/publications/generative-ai-and-the-sme-workforce_2d08b99d-en/full-report/component-6.html", "quote": "The most common reason for not using generative AI is that it is not suited" } ], "related_findings": [ { "question": "What stops small firms that have looked into AI?", "answer": "Expertise, legal uncertainty and data worries. Among EU firms with 10 to 49 employees that considered AI and did not adopt it, 71% cite lack of expertise, 55% unclear legal consequences, 52% data protection worries and 39% cost (2025). But only about 1 in 8 small EU non-users had ever considered AI, so as shares of all small firms these are 4 to 7%.", "sources": [ { "creator": "Eurostat", "title": "Artificial intelligence by size class of enterprise (dataset isoc_eb_ai)", "year": 2026, "sample": "EU enterprises with 10 or more employees, 2025 survey", "method": "Official statistics; asked only of non-users that had considered AI", "figure": "Small firms that considered AI: lack of expertise 70.87%, legal uncertainty 54.79%, data protection 52.49%, cost 38.82%; 12.65% of small non-users had considered AI", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_ai/default/table", "quote": "Enterprises do not use AI technologies, because of a lack of relevant expertise" } ] }, { "question": "Do most small firms face barriers to AI at all?", "answer": "Many say they do not. In the UK in June 2026, 52% of businesses under 10 employees and 42% of those with 10 to 49 reported no barrier to adopting AI, and no single barrier reached 14% among firms with 10 to 49 employees. In Canada, 41% of businesses with 1 to 4 employees say AI is not relevant to them.", "sources": [ { "creator": "Office for National Statistics (UK)", "title": "Artificial intelligence in UK businesses: 2023 to 2026", "year": 2026, "sample": "38,637 responding UK businesses, June 2026", "method": "Official statistics in development; barriers in the last three months", "figure": "No barriers: 51.6% (0 to 9 employees), 42.0% (10 to 49); expertise 7.0% and 13.3%; cost 6.5% and 11.3%", "url": "https://www.ons.gov.uk/businessindustryandtrade/business/businessservices/articles/artificialintelligenceinukbusinesses/2023to2026", "quote": "41% of UK businesses with 10 or more employees report no barriers to adoption." } ] } ], "numbers_you_may_have_seen": [ { "claim": "Cost is the biggest barrier stopping small businesses from using AI.", "what_the_source_says": "Official surveys don't support it: cost is cited by 6.7 to 7.3% of small US firms with no AI plans (Census) and 6 to 16% (Federal Reserve). It ranks high only among EU firms that had considered AI." }, { "claim": "70.89% of EU companies cite lack of expertise as the main barrier (2025).", "what_the_source_says": "70.89% is Eurostat's 2024 value shown under a 2025 label; the 2025 value is 70.31%. It is asked only of non-users that had considered AI. As a share of all EU enterprises, lack of expertise is 7.8%." }, { "claim": "Census: 65% of businesses say AI is not applicable to them.", "what_the_source_says": "That appears in a working paper's text. Its own chart and the published table give 61.6% of firms not planning to use AI." }, { "claim": "Lack of skills is the top barrier for SMEs.", "what_the_source_says": "True in Japan and Korea and among EU firms that considered AI. Across the seven OECD countries and in US official data, the top reason is that AI does not fit the business." } ], "citation": "EVY (2026). What stops small companies from adopting AI? The AI at Work Fact Book, F-31. https://evy.so/facts/what-stops-small-companies-adopting-ai/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-32", "url": "https://evy.so/facts/small-firms-gains-from-ai/", "chapter": "Small Teams", "question": "Do small firms that use AI see gains?", "answer": "Most say yes on productivity: 65 to 78 percent of AI-using small firms report that AI raised productivity or employee performance, by their own account and with no size of gain attached. Far fewer report higher sales, about 3 in 10, and almost none report changes in jobs.", "range": { "low": 65, "high": 78, "unit": "% of AI-using small firms reporting higher productivity or employee performance (self-reported)", "display": "65–78% of AI-using small firms say AI raised productivity (self-reported, no size of gain)" }, "confidence": "medium", "confidence_reason": "Two independent creators with different methods agree on the self-reported share, and two official agencies agree that almost no small firm reports job changes. All the benefit figures are perceptions with no magnitude, and the only causal evidence comes from two trials in special populations that point in different directions.", "last_checked": "2026-10-14", "how_to_read": "Every benefit figure here is the owner's or manager's own view, and neither survey asked how large the gains were. The Federal Reserve leaves out firms answering not applicable or unsure; the OECD asks yes or no on a list of benefits and is weighted toward one-person and micro firms. Official surveys measure jobs and tasks, not productivity. No representative source measures the size of small-firm gains.", "sources": [ { "creator": "Federal Reserve Banks", "title": "2026 Report on Employer Firms (2025 Small Business Credit Survey)", "year": 2026, "sample": "1,738 to 2,011 AI-using US employer firms, September to November 2025", "method": "Weighted convenience sample; owner-reported direction of change", "figure": "Productivity up 68% to 78% by size band under 50; sales up 30% to 35%; labor costs unchanged for 75% to 78%", "url": "https://www.fedsmallbusiness.org/reports/survey/2026/2026-report-on-employer-firms", "quote": "71% said its use led to increased productivity" }, { "creator": "OECD, survey by Ipsos", "title": "Generative AI and the SME Workforce", "year": 2025, "sample": "SMEs using generative AI, from 5,232 surveyed in seven countries, late 2024", "method": "Random telephone survey; yes or no on listed benefits, with no size of gain asked", "figure": "Improved employee performance 65.1%; saved money 45.2%; increased revenue 25.9%", "url": "https://www.oecd.org/en/publications/generative-ai-and-the-sme-workforce_2d08b99d-en/full-report/component-4.html", "quote": "65.1% of SMEs using generative AI report that it helped increase employee performance" } ], "related_findings": [ { "question": "Do small firms cut jobs because of AI?", "answer": "Almost none, so far. 96% of AI-using US firms under 50 employees report no change in employment from AI, and AI mostly supports tasks (43 to 45% of small users) rather than taking them over (8 to 11%), according to the Census Bureau. In the UK, about 4% of AI-using firms under 50 employees report a smaller headcount.", "sources": [ { "creator": "US Census Bureau", "title": "BTOS AI Supplement Table 2026", "year": 2026, "sample": "More than 117,000 responding US firms, November 2025 to February 2026", "method": "Official survey of AI-using firms' effects over the last six months", "figure": "No change in total employment 95.6% to 96.3% (firms under 50); AI supplemented tasks 42.8% to 44.8%; AI performed tasks previously done by staff 8.4% to 10.9%", "url": "https://www.census.gov/hfp/btos/downloads/AI_Supplement_Table_2026.xlsx", "quote": "how did the use of Artificial Intelligence (AI) affect this business's total employment?" } ] }, { "question": "What do controlled trials show about small firms and AI?", "answer": "Few trials exist, and they disagree. In Kenya, 640 small business owners given a GPT-4 business adviser saw no average change in revenue or profit; strong performers gained and weak ones did nearly 10% worse (see F-12). In a trial with 515 early-stage startups, showing founders where other firms use AI led to 1.9 times higher revenue, though only weakly significant, driven by the top tenth of firms, and in a paper not yet peer reviewed.", "confidence": "low", "sources": [ { "creator": "Hyunjin Kim and Dahyeon Kim (INSEAD), Rembrand Koning (Harvard Business School)", "title": "Mapping AI into Production: A Field Experiment on Firm Performance (INSEAD Working Paper 2026/20/STR)", "year": 2026, "sample": "515 pre-seed startups in an online accelerator; median team of four", "method": "Preregistered randomized experiment; working paper, not peer reviewed", "figure": "Treated startups found 44% more AI use cases and had 1.9 times higher revenue (p < 0.1)", "url": "https://ssrn.com/abstract=6513481", "quote": "Treated firms complete 12% more tasks, are 18% more likely to acquire paying customers" }, { "creator": "Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning", "title": "The Uneven Impact of Generative Artificial Intelligence on Entrepreneurial Performance (Management Science)", "year": 2026, "sample": "640 small business owners in Kenya, 2023", "method": "Randomized controlled trial, published July 2026", "figure": "No average effect on revenue or profit; low performers did nearly 10% worse", "url": "https://doi.org/10.1287/mnsc.2024.06909", "quote": "low performers did nearly 10% worse due to the AI assistant" } ] } ], "numbers_you_may_have_seen": [ { "claim": "AI boosts small business revenue by 15% (Harvard Kenya study).", "what_the_source_says": "The trial found no average effect. Only high performers may have gained over 15%, while low performers did about 10% worse." }, { "claim": "AI nearly doubles startup revenue.", "what_the_source_says": "The 1.9 times comes from 515 accelerator startups shown where to use AI, is significant only at p < 0.1, is driven by the top 10% of firms, and is not yet peer reviewed." }, { "claim": "Small businesses are cutting jobs because of AI.", "what_the_source_says": "96% of AI-using US firms under 50 employees report no employment change from AI (Census, 2025 to 2026)." } ], "citation": "EVY (2026). Do small firms that use AI see gains? The AI at Work Fact Book, F-32. https://evy.so/facts/small-firms-gains-from-ai/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-33", "url": "https://evy.so/facts/small-business-owner-hours/", "chapter": "Small Teams", "question": "How many hours do small business owners work, and how much goes to admin?", "answer": "Small business owners work about 45 to 52 hours a week, roughly 10 hours more than employees: EU employers worked 46.3 hours in 2025 against 36.6 for employees. Admin takes about a fifth to a third of owner time, by vendor surveys.", "range": { "low": 45, "high": 52, "unit": "hours a week worked by small business owners", "display": "45–52 h a week worked by small business owners; employees work about 37" }, "spread": { "low": 45, "high": 60, "unit": "hours a week" }, "confidence": "medium", "confidence_reason": "An official, large-sample source agrees with independent owner surveys using different methods on 45 to 52 hours for owners of employer firms. The admin share rests on two small vendor surveys, and no official source measures it.", "last_checked": "2026-10-14", "how_to_read": "Eurostat's household survey is the most comparable across countries; the owner surveys are self-reported, from small or undisclosed samples, by companies that sell software or services to owners. Eurostat counts employers of any firm size, though most run small firms. The often quoted 52 hours comes from a 2005 Gallup poll. No current official US figure exists: the Census Bureau's owner survey has no hours question.", "sources": [ { "creator": "Eurostat (EU Labour Force Survey)", "title": "Average number of usual weekly hours of work in main job (dataset lfsa_ewhuis)", "year": 2025, "sample": "EU Labour Force Survey, ages 20 to 64, all 27 member states, 2025", "method": "Official household survey of usual weekly hours. Employers are self-employed people with employees; there is no firm-size breakdown.", "figure": "Employers 46.3 hours a week (full-time 47.5); self-employed without employees 39.7; employees 36.6", "url": "https://ec.europa.eu/eurostat/databrowser/view/lfsa_ewhuis/default/table?lang=en", "quote": "Self-employed persons with employees (employers)" }, { "creator": "Time etc, survey by Censuswide", "title": "The Big Price Of Small Tasks", "year": 2023, "sample": "251 US owners of growing businesses, September 2023", "method": "Online panel survey by a virtual-assistant company that sells admin outsourcing", "figure": "45.5 hours a week; 36% of the week on small admin tasks such as invoicing and data entry", "url": "https://www.timeetc.com/resources/how-to-achieve-more/the-big-price-of-small-tasks-how-entrepreneurs-may-be-unwittingly-keeping-their-businesses-small", "quote": "the average work week for entrepreneurs at the helm of growing businesses is 45.5 hours" }, { "creator": "Sage", "title": "An extra hour of SMB productivity a week worth £7bn to UK economy", "year": 2024, "sample": "UK small business owners; sample size not stated", "method": "Vendor survey; Sage sells accounting software", "figure": "51 hours a week on average; 51% wish they spent less time on admin", "url": "https://www.sage.com/en-gb/company/digital-newsroom/2024/04/24/an-extra-hour-of-smb-productivity-a-week-worth-7bn-to-uk-economy", "quote": "On average, they invest 51 hours weekly in their business" }, { "creator": "UENI Research", "title": "How microbusiness owners spend their time", "year": 2024, "sample": "837 US businesses with five or fewer employees, May 2024", "method": "Vendor survey; recruitment not stated. UENI sells websites and AI tools to microbusinesses.", "figure": "Median 60 hours a week; 62% work more than 50; admin plus legal and compliance take 22.4% of owner time", "url": "https://ueni.com/en-us/small-business-research/how-microbusiness-owners-spend-their-time", "quote": "The median number of hours worked per week among microbusinesses surveyed was 60 hours." } ], "related_findings": [ { "question": "How much of a small business owner's time goes to admin?", "answer": "About a fifth to a third, in two vendor surveys: 22% for administration plus legal and compliance among US firms with five or fewer employees (UENI, 2024), and 36% for small admin tasks such as invoicing and data entry among owners of growing businesses (Time etc, 2023). Applied to a 45-hour week that is roughly 10 to 16 hours; the surveys report only the shares.", "confidence": "low", "sources": [] }, { "question": "Does AI shorten small business owners' workdays?", "answer": "For some. In January 2026, 27% of AI-using US businesses with up to 100 employees said AI had shortened their workday and 8% that it had lengthened it, in Intuit's vendor survey.", "sources": [ { "creator": "Intuit QuickBooks, with economists at the University of Chicago", "title": "2026 AI Impact Report", "year": 2026, "sample": "2,222 US owners of businesses with 0 to 100 employees, January 2026", "method": "Paid panel and Intuit customers. Intuit sells AI features in QuickBooks.", "figure": "27% say AI shortened their workday; 8% that it lengthened it", "url": "https://www.intuit.com/blog/global-stories/ai-impact-report/", "quote": "27% of US businesses using AI said it had shortened their workday" } ] } ], "numbers_you_may_have_seen": [ { "claim": "Small business owners work 52 hours a week.", "what_the_source_says": "That comes from a Gallup telephone poll of 607 owners in June 2005, usually repeated without the year. Current figures run 45 to 51 hours." }, { "claim": "Small business owners spend 16 hours a week on admin.", "what_the_source_says": "Third parties derived it by multiplying a 45.5-hour week by a 36% admin share. The survey reports only those two numbers." }, { "claim": "Small business owners spend 23 hours a week on admin (SCORE).", "what_the_source_says": "We found no primary report containing it; it appears only on aggregator pages." } ], "citation": "EVY (2026). How many hours do small business owners work, and how much goes to admin? The AI at Work Fact Book, F-33. https://evy.so/facts/small-business-owner-hours/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-34", "url": "https://evy.so/facts/ai-use-by-eu-country/", "chapter": "Europe", "question": "Which EU countries' companies use AI the most and least?", "answer": "In 2025, between 5 percent of companies (Romania) and 42 percent (Denmark) used AI, among firms with 10 or more employees; the EU average was 20 percent. Germany was at 26 percent, Spain 20, France 18 and Portugal 12, with the Nordic countries and the Netherlands at 33 to 42 percent.", "range": { "low": 5.2, "high": 42, "unit": "% of enterprises with 10+ employees using AI, lowest and highest EU country, 2025", "display": "5–42% of companies used AI in 2025, from Romania to Denmark; EU average 20%" }, "confidence": "high", "confidence_reason": "One official, harmonized survey of about 157,000 firms, run the same way in every country. Two independent creators with different methods confirm the country ranking. Part of the 2024 to 2025 rise comes from a new technology added to the list.", "last_checked": "2026-10-14", "how_to_read": "Each chart row is one country from the same official survey, so the countries compare cleanly. The survey counts firms with 10 or more employees using any of eight AI technologies, with every firm counted equally. In 2025 it added an eighth technology (generating pictures, video or audio), so part of the rise from 2024 is definitional. Surveys with broader questions or that weight big firms more, such as Bitkom's 57% for German firms with 20 or more staff, give much higher numbers.", "sources": [ { "creator": "Eurostat", "title": "Artificial intelligence by size class of enterprise (dataset isoc_eb_ai)", "year": 2025, "sample": "About 157,000 EU enterprises with 10 or more employees, early 2025", "method": "Official harmonized survey; use of any of eight listed AI technologies during the year. Excludes agriculture, mining and finance.", "figure": "Denmark 42.0%, Finland 37.8%, Sweden 35.0%, Netherlands 33.2%, Norway 28.9%, Germany 26.0%, Spain 20.3%, France 18.2%, Italy 16.4%, Portugal 11.5%, Poland 8.4%, Romania 5.2%; EU 19.95% (8.06% in 2023)", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_ai/default/table?lang=en", "quote": "Enterprises using AI technologies generating written or spoken language or programming codes" }, { "creator": "Eurostat", "title": "Artificial intelligence by size class of enterprise (dataset isoc_eb_ai)", "year": 2025, "sample": "German enterprises with 10 or more employees in the same survey", "method": "Same survey and definition", "figure": "Germany 25.97% (11.55% in 2023); AI that generates text, speech or code 9.0%", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_ai/default/table?lang=en" }, { "creator": "Eurostat", "title": "Use of artificial intelligence in enterprises (Statistics Explained)", "year": 2025, "sample": "157,000 enterprises surveyed in 2025", "method": "Eurostat's commentary on the same survey", "figure": "EU average 19.95%, up 6.47 points from 2024; country range 5.21% to 42.03%", "url": "https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Use_of_artificial_intelligence_in_enterprises", "quote": "the share of enterprises using AI ranged between 5.21% and 42.03%" }, { "creator": "Eurostat", "title": "Artificial intelligence by size class of enterprise (dataset isoc_eb_ai)", "year": 2025, "sample": "Romanian enterprises with 10 or more employees in the same survey", "method": "Same survey and definition", "figure": "Romania 5.21% (1.51% in 2023)", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_ai/default/table?lang=en" }, { "creator": "Alexander Bick, Adam Blandin, David J. Deming, Nicola Fuchs-Schündeln and Jonas Jessen", "title": "Mind the Gap: AI Adoption in Europe and the US (St. Louis Fed Working Paper 2026-003)", "year": 2026, "sample": "Eurostat enterprise survey 2021 to 2025, 32 European countries", "method": "Analysis of the official data at country and industry level", "figure": "Early leaders kept their lead and grew faster; the spread between countries doubled from 2021 to 2025", "url": "https://doi.org/10.20955/wp.2026.003", "quote": "with early adoption leaders tending to pull further ahead of early laggards" } ], "related_findings": [ { "question": "How fast is AI use growing among European companies?", "answer": "About 2.5 times since 2023: from 8.1% of EU firms in 2023 to 13.5% in 2024 and 20.0% in 2025. The leaders pulled ahead: the gap between the top and bottom country widened from 14 to 37 points. Denmark (+14.5 points) and Finland (+13.5) grew most from 2024 to 2025.", "sources": [] }, { "question": "How many European companies use generative AI?", "answer": "8.8% of EU firms used AI that generates text, speech or code in 2025, from 3.1% in Romania to 30.8% in Denmark (Germany 9.0%, Spain 8.9%, France 7.8%, Portugal 5.3%, Netherlands 16.3%, Finland 20.1%, Sweden 19.7%). A further 9.6% generated pictures, video or audio.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "The EU wants 75% of companies using AI by 2030.", "what_the_source_says": "The Digital Decade target is that three in four companies use cloud computing, big data or AI, any of the three." }, { "claim": "57% of German companies use AI (Bitkom, 2026).", "what_the_source_says": "Bitkom surveyed 603 firms with 20 or more employees with one broad question. The official figure for German firms with 10 or more employees is 26% (2025)." }, { "claim": "More than 70% of euro area firms use AI (ECB).", "what_the_source_says": "That counts any use, including occasional. Only 7% use AI intensively, and the official enterprise survey puts the EU at 20%." }, { "claim": "37% of EU firms use generative AI (EIB).", "what_the_source_says": "The EIB weights firms by value added, so big firms dominate. Counted by number of firms, 8.8% of EU enterprises generate text, speech or code with AI." }, { "claim": "Only 8% (or 13.5%) of EU companies use AI.", "what_the_source_says": "Those are the 2023 and 2024 figures. In 2025 it was 19.95%." } ], "citation": "EVY (2026). Which EU countries' companies use AI the most and least? The AI at Work Fact Book, F-34. https://evy.so/facts/ai-use-by-eu-country/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-35", "url": "https://evy.so/facts/genai-use-for-work-by-eu-country/", "chapter": "Europe", "question": "What share of workers in each EU country use generative AI for work?", "answer": "In 2025, between 9 percent of workers (Romania) and 37 percent (Netherlands) had used generative AI for work in the previous three months; the EU figure was 22 percent. Germany was at 21 percent, France 25, Spain 26 and Portugal 28. Surveys a year later with broader questions find higher shares, up to about half of workers.", "range": { "low": 8.6, "high": 37.1, "unit": "% of employed people who used generative AI for work in the previous 3 months, lowest and highest EU country, 2025", "display": "9–37% of workers used generative AI for work in 2025, from Romania to the Netherlands; EU 22%" }, "confidence": "medium", "confidence_reason": "The country figures are official, harmonized statistics, and an independent survey correlates 0.88 with them, so the ranking is solid. The level is less certain: the data describe early 2025, and newer surveys with broader wording find higher shares.", "last_checked": "2026-10-14", "how_to_read": "The chart shows the top country, the EU, Germany and the lowest country from one official survey; the table above lists the others. The survey asks about generative AI in the previous three months in early 2025, a fast-moving area. Within countries the gap between office and manual workers (28% against 5%) is larger than most gaps between countries. Chapter 3 covers the US and the share of workers worldwide.", "sources": [ { "creator": "Eurostat", "title": "Individuals: use of generative AI tools (dataset isoc_ai_iaiu)", "year": 2025, "sample": "Official household survey in all EU countries, mostly second quarter of 2025", "method": "Self-reported use of generative AI tools for work in the previous 3 months, employed people aged 16 to 74", "figure": "Netherlands 37.1%, Finland 36.9%, Denmark 35.0%, Sweden 29.9%, Portugal 27.6%, Spain 26.1%, France 24.6%, Germany 20.8%, Italy 12.5%, Romania 8.6%; Norway 43.8%; EU 21.8%", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_ai_iaiu/default/table", "quote": "Use of generative AI tools: for professional (work) purposes" }, { "creator": "Eurostat", "title": "Individuals: use of generative AI tools (dataset isoc_ai_iaiu)", "year": 2025, "sample": "Same survey, all EU countries", "method": "Same definition", "figure": "21.8% of employed people; 27.6% in non-manual jobs, 5.3% in manual jobs", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_ai_iaiu/default/table" }, { "creator": "Eurostat", "title": "Individuals: use of generative AI tools (dataset isoc_ai_iaiu)", "year": 2025, "sample": "Same survey, Germany", "method": "Same definition", "figure": "Germany 20.8% for work; 36.7% for any purpose", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_ai_iaiu/default/table" }, { "creator": "Eurostat", "title": "Individuals: use of generative AI tools (dataset isoc_ai_iaiu)", "year": 2025, "sample": "Same survey, Romania", "method": "Same definition", "figure": "Romania 8.6%", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_ai_iaiu/default/table" }, { "creator": "Alexander Bick, Adam Blandin, David J. Deming, Nicola Fuchs-Schündeln and Jonas Jessen", "title": "Mind the Gap: AI Adoption in Europe and the US (St. Louis Fed Working Paper 2026-003)", "year": 2026, "sample": "About 3,000 workers per country, January to February 2026", "method": "Online panel weighted to labor force surveys; the same question in each country", "figure": "Netherlands and Sweden 35.6%, Germany 31.5%, France 28.1%, Italy 25.6%; correlation with Eurostat country rates 0.88", "url": "https://doi.org/10.20955/wp.2026.003", "quote": "Do you use Generative AI for your job? (No/Yes)" } ], "related_findings": [ { "question": "How many European workers use AI at work in 2026?", "answer": "About a third to a half, in surveys with broader questions. 34.5% of employed people in 18 EU countries used AI for work in February to March 2026 (European Commission). 52% of workers in 11 euro area countries used AI in their work in 2026 (ECB, any AI tool). In Germany, 48% of workers use AI at work at any frequency, and 8% daily (Bitkom, 2026).", "sources": [ { "creator": "European Central Bank", "title": "AI adoption and the productivity promise: what workers report (ECB Blog)", "year": 2026, "sample": "About 20,000 people a month in 11 euro area countries", "method": "Consumer Expectations Survey; any AI tool, no time window", "figure": "52% of employed workers use AI in their work (26% in 2024, 41% in 2025)", "url": "https://www.ecb.europa.eu/press/blog/date/2026/html/ecb.blog20260826~e1c1a89999.en.html", "quote": "A majority of workers now report using AI for work" }, { "creator": "Bitkom", "title": "Ein Drittel nutzt KI mindestens einmal pro Woche (press release, 28 April 2026)", "year": 2026, "sample": "550 employed people in Germany, by telephone, February to March 2026", "method": "Industry association survey; any AI use at work, any frequency", "figure": "48% of German workers use AI at work: 8% daily, 18% weekly, 22% less often; 12% of users do so without their employer's knowledge", "url": "https://www.bitkom.org/Presse/Presseinformation/Ein-Drittel-nutzt-KI-mindestens-einmal-pro-Woche", "quote": "48 Prozent der Erwerbstätigen nutzen KI bei der Arbeit" } ] } ], "numbers_you_may_have_seen": [ { "claim": "15% of Europeans use generative AI for work (Eurostat).", "what_the_source_says": "That counts everyone aged 16 to 74, including students and retirees. Among employed people it is 21.8%." }, { "claim": "Over half of working-age Europeans use generative AI for work.", "what_the_source_says": "Eurostat's over 50% refers to users: 55.6% of users aged 25 to 64 use it for work, which is 18.2% of everyone that age." }, { "claim": "Half of German workers use AI at work (Bitkom).", "what_the_source_says": "It counts any frequency, including 22% who use it less than weekly. Daily use is 8%; the official 2025 rate for generative AI is 20.8%." }, { "claim": "A third of Europeans use generative AI at work.", "what_the_source_says": "The 32.7% is use for any purpose by all adults. Work use is 21.8% of employed people." } ], "citation": "EVY (2026). What share of workers in each EU country use generative AI for work? The AI at Work Fact Book, F-35. https://evy.so/facts/genai-use-for-work-by-eu-country/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-36", "url": "https://evy.so/facts/ai-at-work-europe-vs-us/", "chapter": "Europe", "question": "How does AI use at work in Europe compare with the US?", "answer": "US workers use AI more: in a survey asking the same question in seven countries in early 2026, 43 percent of US workers used generative AI for their job, against 26 to 36 percent in six large European countries, a gap of 7 to 17 points. For companies there is no clean comparison, and US firms that use AI spread it across more of their business.", "range": { "low": 7, "high": 17, "unit": "percentage points by which US worker use exceeds use in six European countries, same survey, early 2026", "display": "7–17 pts more US than European workers use generative AI for their job (same survey, 2026)" }, "confidence": "medium", "confidence_reason": "The worker gap rests on one study that asked identical questions in all seven countries, in two waves with the same order. A 47-country survey agrees for the big economies but puts Norway and Denmark at or above the US. The company-level evidence conflicts.", "last_checked": "2026-10-14", "how_to_read": "Only one study asks the same question in the same way and at the same time in the US and Europe, so its gap is the only clean worker comparison; it covers six large European countries, not the whole EU. Comparing the official EU survey (22%, early 2025, past three months) with the official US series (45%, May 2026, use for your job) mixes different questions and dates. The KPMG survey uses a looser definition and finds Norway and Denmark at or above the US.", "sources": [ { "creator": "Alexander Bick, Adam Blandin, David Deming, Nicola Fuchs-Schündeln and Jonas Jessen (Federal Reserve Bank of St. Louis)", "title": "Mind the Gap: AI Adoption in Europe and the U.S. (On the Economy)", "year": 2026, "sample": "About 3,000 workers per country, January to February 2026 (20,916 in total)", "method": "Online panel weighted to labor force surveys; identical wording in each country", "figure": "US 43.0%, UK 36.3%, Sweden 35.6%, Netherlands 35.6%, Germany 31.5%, France 28.1%, Italy 25.6%; US workers spent 5.2% of work hours using AI", "url": "https://www.stlouisfed.org/on-the-economy/2026/mar/mind-gap-ai-adoption-europe-us", "quote": "43.0% of U.S. workers reported using AI for their jobs in January-February 2026" }, { "creator": "Alexander Bick, Adam Blandin, David J. Deming, Nicola Fuchs-Schündeln and Jonas Jessen", "title": "Mind the Gap: AI Adoption in Europe and the US (St. Louis Fed Working Paper 2026-003)", "year": 2026, "sample": "Same survey, two waves (May to June 2025 and January to February 2026)", "method": "Same survey; working paper with methods and the company-level comparison", "figure": "UK 36.3% (34.7% in 2025); share of work hours using AI: US 5.2%, UK 2.8%, Germany 1.7%, France 1.5%", "url": "https://doi.org/10.20955/wp.2026.003", "quote": "In 2025, 7% of US firms use AI for production versus 4% of EU firms" }, { "creator": "Alexander Bick, Adam Blandin, David J. Deming, Nicola Fuchs-Schündeln and Jonas Jessen", "title": "Mind the Gap: AI Adoption in Europe and the US (St. Louis Fed Working Paper 2026-003)", "year": 2026, "sample": "Same survey", "method": "Same survey", "figure": "Germany 31.5% (30.7% in 2025)", "url": "https://doi.org/10.20955/wp.2026.003" }, { "creator": "Alexander Bick, Adam Blandin, David J. Deming, Nicola Fuchs-Schündeln and Jonas Jessen", "title": "Mind the Gap: AI Adoption in Europe and the US (St. Louis Fed Working Paper 2026-003)", "year": 2026, "sample": "Same survey", "method": "Same survey", "figure": "Italy 25.6% (24.5% in 2025)", "url": "https://doi.org/10.20955/wp.2026.003" }, { "creator": "University of Melbourne and KPMG International", "title": "Trust, attitudes and use of artificial intelligence: A global study 2025", "year": 2025, "sample": "About 1,000 people per country in 47 countries, November 2024 to January 2025", "method": "Online survey; any AI use at work at least every few months", "figure": "US 52%; Norway 67%, Denmark 53%, Spain 50%, UK 48%, France 44%, Sweden 44%, Germany 42%, Netherlands 42%", "url": "https://mbs.edu/-/media/PDF/Research/Trust_in_AI_Report.pdf", "quote": "% Using AI on a semi-regular or regular basis" } ], "related_findings": [ { "question": "Do US companies use AI more than European companies?", "answer": "There is no clean answer. On the one question both official surveys shared in early 2025, AI used to produce goods or services, 7% of US firms said yes against 4% of EU firms. The EIB, which asks firms on both sides the same questions, finds near parity: 37% of EU and 36% of US firms invest in generative AI (2025, weighted by value added). The clearer difference is breadth: 81% of US firms using AI apply it in two or more business areas, against 55% in the EU.", "sources": [ { "creator": "European Investment Bank, fieldwork by Ipsos", "title": "EIB Investment Survey 2025: European Union overview", "year": 2025, "sample": "More than 12,000 EU firms and about 800 US firms, April to July 2025", "method": "Telephone survey of senior managers, weighted by value added", "figure": "Generative AI: EU 37%, US 36%; of AI users, 81% (US) and 55% (EU) use it in two or more business areas", "url": "https://www.eib.org/en/publications/20250216-econ-eibis-2025-eu", "quote": "Around 37% of EU firms use generative artificial intelligence, in line with US firms." } ] }, { "question": "Do US workers use AI more intensively than Europeans?", "answer": "Yes. US workers spent 5.2% of their work hours using generative AI in early 2026, about double the share in the UK (2.8%), Sweden (2.5%) and the Netherlands (2.2%), and more than triple Germany (1.7%), Italy (1.6%) and France (1.5%). About half of the average gap comes from differences in jobs, industries, firm size and demographics.", "sources": [] } ], "numbers_you_may_have_seen": [ { "claim": "45% of US workers use generative AI, against 22% in the EU.", "what_the_source_says": "That mixes two surveys with different questions, ages and dates. With the same question in both places the gap is about 11 points (43% against 32%)." }, { "claim": "US workers are 68% more likely to use AI than Europeans.", "what_the_source_says": "The 68% compares the US with Italy, the lowest of six countries. Against the UK, Sweden and the Netherlands the US lead is 18 to 21%." }, { "claim": "34% of US firms use AI.", "what_the_source_says": "A projection by researchers, never measured. The measured US rate was 17% in November 2025 and 23.8% in September 2026." }, { "claim": "European companies have caught up with US companies on AI (EIB).", "what_the_source_says": "The EIB's 37% against 36% is weighted by value added and rests on about 800 US firms. US firms that use AI spread it much more widely." } ], "citation": "EVY (2026). How does AI use at work in Europe compare with the US? The AI at Work Fact Book, F-36. https://evy.so/facts/ai-at-work-europe-vs-us/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-37", "url": "https://evy.so/facts/european-attitudes-to-ai-at-work/", "chapter": "Europe", "question": "How do European workers feel about AI at work?", "answer": "Most Europeans view AI at work positively: 62 percent across the EU, from 48 percent in Portugal and Greece to 86 percent in Denmark (2024). Large majorities want rules on how employers use it, and two thirds expect AI to cost jobs overall, though far fewer worry about their own job.", "range": { "low": 48, "high": 86, "unit": "% who view robots and AI at work positively, lowest and highest EU country, 2024", "display": "48–86% view AI at work positively, by country (EU 62%, 2024)" }, "confidence": "medium", "confidence_reason": "The EU-wide figures come from one official survey with a clear method, but it dates from spring 2024, covers all adults and asks about robots and AI together. Later surveys of workers about AI alone find lower positive shares; the other findings point the same way across creators.", "last_checked": "2026-10-14", "how_to_read": "The Eurobarometer asks all adults, face to face, about robots and AI together, in 2024. Newer surveys that ask workers about AI alone come out lower, around 41 to 49% positive in 2026, and the two should not be read as a trend. The country pattern holds across sources: the Nordic countries and the Netherlands are most positive and least worried about jobs; Portugal, Greece and France least positive.", "sources": [ { "creator": "European Commission, fieldwork by Verian", "title": "Special Eurobarometer 554: Artificial Intelligence and the future of work", "year": 2025, "sample": "26,415 face-to-face interviews with people aged 15 and over in all 27 EU countries, April to May 2024", "method": "Official Eurobarometer; asks about robots and AI in the workplace together", "figure": "Viewed positively: Denmark 86%, Finland 80%, Sweden 79%, Netherlands 77%, Germany 65%, EU 62%, Spain 56%, France 53%, Greece and Portugal 48%", "url": "https://europa.eu/eurobarometer/surveys/detail/3222", "quote": "positively perceive the use of robots and Artificial Intelligence in the workplace" }, { "creator": "European Commission, fieldwork by Verian", "title": "Special Eurobarometer 554: Artificial Intelligence and the future of work", "year": 2025, "sample": "Same survey, Germany", "method": "Same survey", "figure": "Germany 65% positive; 53% expect AI to destroy more jobs than it creates (EU 66%)", "url": "https://europa.eu/eurobarometer/surveys/detail/3222" }, { "creator": "European Commission, fieldwork by Verian", "title": "Special Eurobarometer 554: Artificial Intelligence and the future of work", "year": 2025, "sample": "Same survey, all 27 countries", "method": "Same survey", "figure": "EU 62% positive, 32% negative; 66% of people in work say recent digital technologies including AI help their job", "url": "https://europa.eu/eurobarometer/surveys/detail/3222" }, { "creator": "European Commission, fieldwork by Verian", "title": "Special Eurobarometer 554: Artificial Intelligence and the future of work", "year": 2025, "sample": "Same survey, Portugal and Greece", "method": "Same survey", "figure": "Portugal and Greece 48% positive", "url": "https://europa.eu/eurobarometer/surveys/detail/3222" }, { "creator": "European Central Bank", "title": "AI adoption and the productivity promise: what workers report (ECB Blog)", "year": 2026, "sample": "About 20,000 people a month in 11 euro area countries, 2026 wave", "method": "Consumer Expectations Survey; workers' views of AI alone", "figure": "41% of workers view AI positively, down from 43% a year earlier; 41% are uninterested in using it", "url": "https://www.ecb.europa.eu/press/blog/date/2026/html/ecb.blog20260826~e1c1a89999.en.html", "quote": "AI is perceived less favourably today than one year ago" } ], "related_findings": [ { "question": "What rules do Europeans want on AI at work?", "answer": "Between 72% and 82% call each of five workplace rules important: protecting workers' privacy (82%), involving workers in designing and adopting new technology (77%), transparency in HR decisions (75%), banning fully automated decisions (74%) and limiting automated monitoring (72%). Europeans object most to AI automatically firing workers (78%) and monitoring them (63%).", "sources": [] }, { "question": "Do Europeans fear losing their jobs to AI?", "answer": "In general, yes; for themselves, much less. 66% believe AI will destroy more jobs than it creates, from 45% in Denmark to 80% in Greece (Germany 53%). But only 22% of German workers name worry about their own job as a drawback of AI (Bitkom, 2026), and 41% of EU workers who use AI are very or somewhat concerned about losing their job to it (European Commission, 2026).", "sources": [ { "creator": "Bitkom", "title": "Ein Drittel nutzt KI mindestens einmal pro Woche (press release, 28 April 2026)", "year": 2026, "sample": "550 employed people in Germany, by telephone, February to March 2026", "method": "Industry association survey; drawbacks named, several answers allowed", "figure": "Worry about own job 22%; unclear who is responsible for AI errors 62%; unclear where data goes 59%; 49% would like an AI assistant, 45% want no AI support", "url": "https://www.bitkom.org/Presse/Presseinformation/Ein-Drittel-nutzt-KI-mindestens-einmal-pro-Woche", "quote": "22 Prozent haben Sorge um den eigenen Arbeitsplatz" }, { "creator": "European Commission, Directorate-General for Economic and Financial Affairs", "title": "The AI-adoption divide: who benefits, who doesn't, and what it means for workers", "year": 2026, "sample": "21,207 responses in 18 EU countries, February and March 2026; this question asked of AI users", "method": "Ad-hoc module in the harmonized consumer surveys", "figure": "Of employed AI users, 14% very and 27% somewhat concerned about losing their job to AI", "url": "https://economy-finance.ec.europa.eu/economic-forecast-and-surveys/economic-forecasts/spring-2026-economic-forecast-slowdown-growth-energy-shock-drives-inflation/ai-adoption-divide-who-benefits-who-doesnt-and-what-it-means-workers_en", "quote": "14% are very concerned and 27% are somewhat concerned about potential job displacement" } ] } ], "numbers_you_may_have_seen": [ { "claim": "84% of Europeans want AI at work regulated (Eurobarometer).", "what_the_source_says": "84% agree robots and AI require careful management, a general statement. The specific workplace rules drew 72 to 82%." }, { "claim": "66% of Europeans fear losing their job to AI.", "what_the_source_says": "66% believe AI will destroy more jobs than it creates in general. Fear for one's own job is much lower." }, { "claim": "62% of European workers are positive about AI.", "what_the_source_says": "The Eurobarometer asked all adults about robots and AI together, in 2024. Among euro area workers asked about AI in 2026, 41% are positive (ECB)." }, { "claim": "Half of Germans reject AI at work (Bitkom).", "what_the_source_says": "45% of German workers want no AI support at work, against 49% who would like an AI assistant: a split among workers only." } ], "citation": "EVY (2026). How do European workers feel about AI at work? The AI at Work Fact Book, F-37. https://evy.so/facts/european-attitudes-to-ai-at-work/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-38", "url": "https://evy.so/facts/eu-ai-act-readiness/", "chapter": "Europe", "question": "How ready are European companies for the EU AI Act?", "answer": "About 3 in 10 companies say they understand what the AI Act requires: 28 percent in two independent 2026 surveys, and 71 percent of German firms feel poorly informed. Engagement is rising fast, and the deadlines for high-risk AI moved in July 2026 to December 2027 and August 2028.", "range": { "low": 28, "high": 28, "unit": "% of firms or professionals who say they understand the AI Act's requirements well, 2026", "display": "28% of companies say they understand what the AI Act requires (two 2026 surveys)" }, "confidence": "medium", "confidence_reason": "Two independent surveys with different populations and methods land on the same 28%, and a third confirms the direction. No EU-wide official survey exists, so the evidence leans on Germany, is self-reported, and two of the creators sell compliance services.", "last_checked": "2026-10-14", "how_to_read": "Feeling informed is different from being compliant, and all of this is self-reported. The German surveys cover firms with 20 or more employees; the four-country survey asks IT professionals and includes the UK, where the Act applies only to firms selling into the EU. Most firms are users of AI, not providers (88% of German AI users), so their main duties are AI literacy, transparency and, for high-risk uses, deployer duties.", "sources": [ { "creator": "Federal Office for Information Security (BSI) and TÜV-Verband, survey by forsa", "title": "KI-Sicherheitsstudie 2026", "year": 2026, "sample": "505 companies with 20 or more employees in Germany (246 using AI), June to July 2026", "method": "Representative survey for a federal authority and the testing association, whose members sell AI audits", "figure": "28% well informed about the Act's requirements, 71% poorly informed; of AI-using firms, 65% trained staff, 37% classified systems by risk, 23% took none of six steps", "url": "https://www.tuev-verband.de/fileadmin/user_upload/Content_local/Studien_local/2026_BSI-TUEV-KI-Sicherheitsstudie.pdf", "quote": "darüber fühlt sich die überwiegende Mehrheit der Befragten schlecht informiert (71 Prozent)" }, { "creator": "ESSCA School of Management with Forvis Mazars", "title": "AI, Business and Sustainability Barometer 2026", "year": 2026, "sample": "826 IT and digital professionals in France, Germany, Spain and the UK, March 2026", "method": "Survey by a business school and an audit firm that sells compliance advice; summary page only", "figure": "28% say their organization understands the AI Act well; 57% provide AI training for employees", "url": "https://www.essca.eu/en/news/2026-ai-barometer-businesses-accelerate-ai-adoption-governance-keep-pace/", "quote": "believe their organisation has a good understanding of the EU AI Act" }, { "creator": "Bitkom", "title": "Erstmals nutzt die Mehrheit der Unternehmen KI (press release and chart deck, 14 September 2026)", "year": 2026, "sample": "603 companies with 20 or more employees in Germany, July to August 2026", "method": "Representative telephone survey by the German digital industry association", "figure": "37% expect to be affected as AI users (23% in 2025), 34% are still checking, 8% have not looked at the Act; 89% of those affected expect high effort", "url": "https://www.bitkom.org/Presse/Presseinformation/Erstmals-nutzt-Mehrheit-Unternehmen-KI", "quote": "8 Prozent haben sich mit dem AI Act noch nicht beschäftigt" } ], "related_findings": [ { "question": "When do the EU AI Act's rules apply?", "answer": "The Act entered into force on 1 August 2024. Bans on prohibited practices and the AI literacy duty apply from 2 February 2025, rules for general-purpose AI models from 2 August 2025, and the general application date, including transparency duties, is 2 August 2026. The Digital Omnibus on AI (Regulation (EU) 2026/1744, in force since 27 July 2026) moved the high-risk rules to 2 December 2027 for uses such as hiring, credit and education, and to 2 August 2028 for AI built into regulated products. It also softened the AI literacy duty to taking measures to support it, and added bans on non-consensual intimate deepfakes and child abuse material from 2 December 2026. The separate data and GDPR half of the Digital Omnibus, COM(2025) 837, is still only a proposal.", "sources": [ { "creator": "European Parliament and Council of the European Union", "title": "Regulation (EU) 2024/1689 (Artificial Intelligence Act), Article 113", "year": 2024, "sample": "Legal text", "method": "Official text on EUR-Lex", "figure": "In force 1 August 2024; bans and AI literacy from 2 February 2025; general-purpose AI rules from 2 August 2025; general application from 2 August 2026", "url": "https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32024R1689", "quote": "It shall apply from 2 August 2026." }, { "creator": "European Parliament and Council of the European Union", "title": "Regulation (EU) 2026/1744 (Digital Omnibus on AI)", "year": 2026, "sample": "Legal text, signed 8 July 2026", "method": "Official text on EUR-Lex; amendments in effect from 27 July 2026", "figure": "High-risk rules for Annex III uses from 2 December 2027 and for regulated products from 2 August 2028; new bans from 2 December 2026", "url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32026R1744", "quote": "2 December 2027 as regards AI systems classified as high-risk pursuant to Article 6(2)" }, { "creator": "European Parliament, Legislative Observatory", "title": "Procedure file 2025/0360(COD): Digital Omnibus on data, GDPR, ePrivacy and cybersecurity", "year": 2026, "sample": "Procedure record, checked 14 October 2026", "method": "Legislative Observatory page", "figure": "Proposal COM(2025) 837, awaiting committee decision; not adopted", "url": "https://oeil.secure.europarl.europa.eu/oeil/en/procedure-file?reference=2025/0360(COD)", "quote": "Awaiting committee decision" } ] }, { "question": "How many European workers get AI training?", "answer": "Few, though firms are catching up. In 2024, 15% of employees in 11 EU countries took part in any AI training in the previous year (Germany 14%), while 42% said they needed to build AI skills (Cedefop). In 2026, 70% of German firms with 20 or more employees train at least some staff on AI, but only 11% train all of them (Bitkom); asked whether they had already trained staff, 27% said yes (TÜV-Verband). ICT specialists, who build and run AI systems, are 5.0% of EU employment (Germany 5.5%).", "confidence": "low", "sources": [ { "creator": "Cedefop (European Centre for the Development of Vocational Training)", "title": "Skills empower workers in the AI revolution: first results of Cedefop's 2024 AI skills survey", "year": 2025, "sample": "5,342 employees aged 16 to 64 in 11 EU countries, February to May 2024", "method": "Probability-based online panels, weighted", "figure": "15% took part in AI training in the past 12 months (Germany 14%); 42% report an AI skill gap", "url": "https://www.cedefop.europa.eu/files/9201_en.pdf", "quote": "a relatively small share (15%) of workers participated in education or training" }, { "creator": "TÜV-Verband, survey by forsa", "title": "TÜV Weiterbildungsstudie 2026", "year": 2026, "sample": "500 companies with 20 or more employees in Germany", "method": "Representative survey for the testing association, whose members sell training", "figure": "27% of firms have already trained staff on AI (12% in 2024); 49% of firms with 250 or more employees", "url": "https://www.tuev-verband.de/pressemitteilungen/ki-schulungen-in-unternehmen-innerhalb-von-zwei-jahren-verdoppelt", "quote": "27 Prozent der Unternehmen haben ihre Beschäftigten bereits im Umgang mit KI geschult" }, { "creator": "Eurostat (EU Labour Force Survey)", "title": "Employed ICT specialists (dataset isoc_sks_itspt)", "year": 2026, "sample": "EU Labour Force Survey, 2025", "method": "Official statistics", "figure": "ICT specialists 5.0% of EU employment (10.45 million people); Germany 5.5% (2.32 million)", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_sks_itspt/default/table", "quote": "Employed information and communications technology (ICT) specialists" } ] } ], "numbers_you_may_have_seen": [ { "claim": "High-risk AI Act rules apply from 2 August 2026.", "what_the_source_says": "Regulation (EU) 2026/1744 moved them to 2 December 2027 (uses such as hiring) and 2 August 2028 (regulated products). 2 August 2026 remains the general date, including transparency duties." }, { "claim": "The AI Act requires every company to ensure all staff are AI literate.", "what_the_source_says": "Since 27 July 2026, the duty is to take measures to support AI literacy, and the text says it does not require guaranteeing any level of literacy." }, { "claim": "The Digital Omnibus has been adopted.", "what_the_source_says": "Only the AI part, Regulation (EU) 2026/1744. The data and GDPR part, COM(2025) 837, is still awaiting a committee decision in Parliament." }, { "claim": "56% of companies are completely unprepared for the AI Act (attributed to TÜV).", "what_the_source_says": "We found no primary source for it. The BSI and TÜV study says 71% of German firms feel poorly informed and 23% of AI users have taken none of six compliance steps." }, { "claim": "70% of German companies train their staff on AI (Bitkom).", "what_the_source_says": "It includes firms training only selected employees; 11% train everyone, and TÜV-Verband finds 27% have actually trained staff." } ], "citation": "EVY (2026). How ready are European companies for the EU AI Act? The AI at Work Fact Book, F-38. https://evy.so/facts/eu-ai-act-readiness/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-39", "url": "https://evy.so/facts/ai-data-protection-in-europe/", "chapter": "Europe", "question": "How much do European firms care where their AI processes data?", "answer": "A lot, by what they say: 53 to 66 percent of European firms that use or have considered AI cite data protection as an obstacle, more than any other concern. What they use tells a different story: in Germany, 93 percent said they would prefer a German AI provider, yet 76 percent of AI-using firms use ChatGPT and only 35 percent use any European or German AI application.", "range": { "low": 53, "high": 66, "unit": "% of firms that use or considered AI citing data protection as an obstacle", "display": "53–66% of firms that use or considered AI cite data protection as an obstacle" }, "confidence": "medium", "confidence_reason": "Two independent creators with different methods agree that data protection is the top or near-top concern among firms that engage with AI. The bases differ sharply, the evidence on preferred provider origin is German only, and the one multi-country sovereignty survey is a vendor study.", "last_checked": "2026-10-14", "how_to_read": "Always check the base. Eurostat asks only firms that considered AI and passed, about 14% of non-users; across all EU firms the same answer is 5.8%. Bitkom asks firms already using AI. Stated preferences (which provider firms would choose) and actual use (which tools they run) diverge widely, so both are shown. There is no EU-wide official statistic on where firms want their AI data hosted.", "sources": [ { "creator": "Eurostat", "title": "Artificial intelligence by size class of enterprise (dataset isoc_eb_ai)", "year": 2026, "sample": "About 157,000 EU enterprises with 10 or more employees, early 2025", "method": "Official statistics; asked only of non-users that had considered AI (14% of non-users)", "figure": "Data protection and privacy concerns: EU 52.72% (42.42% in 2023), Germany 60.01%, Spain 53.79%, Netherlands 47.34%; as a share of all EU firms 5.82% (Germany 8.97%)", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_ai/default/table", "quote": "because of concerns regarding violation of data protection and privacy" }, { "creator": "Eurostat", "title": "Artificial intelligence by size class of enterprise (dataset isoc_eb_ai)", "year": 2026, "sample": "German enterprises with 10 or more employees in the same survey", "method": "Same survey and base", "figure": "Germany 60.01% (53.01% in 2024); unclear legal consequences 62.22%", "url": "https://ec.europa.eu/eurostat/databrowser/view/isoc_eb_ai/default/table" }, { "creator": "Bitkom", "title": "KI aus China? Für die deutsche Wirtschaft praktisch kein Thema (press release, 9 September 2026)", "year": 2026, "sample": "603 companies with 20 or more employees in Germany, July to August 2026", "method": "Representative telephone survey by the German digital industry association", "figure": "Data protection requirements are the top obstacle for AI users (66%); tools used: ChatGPT 76%, Microsoft Copilot 35%, Google Gemini 28%, Mistral 0%", "url": "https://www.bitkom.org/Presse/Presseinformation/KI-aus-China-fuer-deutsche-Wirtschaft-kein-Thema", "quote": "Vorne stehen hier Anforderungen an den Datenschutz mit 66 Prozent" } ], "related_findings": [ { "question": "Do European firms use European AI providers?", "answer": "Mostly not, in Germany. In 2025, 88% of German firms said the provider's country matters and 93% would prefer a German AI provider (firms could name several; 51% also preferred the US). In 2026, 76% of German AI-using firms use ChatGPT, and no surveyed firm reported using Mistral (Bitkom). Only 35% of German AI users use any European or German AI application, and 54% run their AI mainly in an external cloud (BSI and TÜV-Verband).", "sources": [ { "creator": "Bitkom", "title": "Durchbruch bei Künstlicher Intelligenz (press release and chart deck, 15 September 2025)", "year": 2025, "sample": "604 companies with 20 or more employees in Germany, July to August 2025", "method": "Representative telephone survey; several origins could be preferred", "figure": "88% say provider origin is important; 93% prefer Germany, 51% the US, 40% other EU", "url": "https://www.bitkom.org/Presse/Presseinformation/Durchbruch-Kuenstliche-Intelligenz", "quote": "Dabei würden 93 Prozent eine KI aus Deutschland bevorzugen" }, { "creator": "Federal Office for Information Security (BSI) and TÜV-Verband, survey by forsa", "title": "KI-Sicherheitsstudie 2026", "year": 2026, "sample": "505 companies with 20 or more employees in Germany, June to July 2026", "method": "Representative survey for a federal authority and the testing association", "figure": "35% of AI users use a European or German AI application; 54% run AI mainly in an external cloud; 93% rate data protection important when choosing AI", "url": "https://www.tuev-verband.de/fileadmin/user_upload/Content_local/Studien_local/2026_BSI-TUEV-KI-Sicherheitsstudie.pdf", "quote": "Bei rund einem Drittel (35 Prozent) ist dies der Fall." } ] }, { "question": "How dependent do European firms feel on non-European AI?", "answer": "It depends on how you ask. 68% of German firms say they are largely or completely dependent on non-EU countries for AI (DIHK, late 2025), but only 30% of German AI users feel strongly dependent on non-European AI providers, and 10% call it a big problem (BSI and TÜV-Verband, 2026).", "sources": [ { "creator": "Deutsche Industrie- und Handelskammer (DIHK)", "title": "Künstliche Intelligenz, Souveränität und Resilienz: DIHK-Digitalisierungsumfrage 2026", "year": 2026, "sample": "4,686 member companies of all sizes, November 2025", "method": "Online survey of chamber of commerce members", "figure": "68% largely or completely dependent on non-EU countries for AI; 76% for operating systems, 55% for cloud", "url": "https://www.dihk.de/resource/blob/163540/486d8384c94a630d9aa0eaa978f0a786/dihk-digitalisierungsumfrage-2026-data.pdf", "quote": "weitgehend oder vollkommen abhängig von Technologien, Innovationen oder Dienstleistungen aus Nicht-EU-Ländern" } ] } ], "numbers_you_may_have_seen": [ { "claim": "93% of German companies want German AI (Bitkom, 2026).", "what_the_source_says": "It is the 2025 survey; firms could prefer several origins (51% also preferred the US), and it is a stated preference, not buying behavior." }, { "claim": "53% of German companies distrust non-European AI providers (DIHK).", "what_the_source_says": "The DIHK report has no trust question. It shows 68% feel largely or completely dependent on non-EU countries for AI." }, { "claim": "Half of EU companies avoid AI over data protection (Eurostat).", "what_the_source_says": "The base is only non-users that had considered AI. Across all EU firms, 5.8% cite data protection (2025)." }, { "claim": "62% of European firms want sovereign AI (Accenture).", "what_the_source_says": "A vendor survey of large organizations that already rate sovereignty as highly important. It is not a cross-section of European firms." } ], "citation": "EVY (2026). How much do European firms care where their AI processes data? The AI at Work Fact Book, F-39. https://evy.so/facts/ai-data-protection-in-europe/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" }, { "id": "F-40", "url": "https://evy.so/facts/ai-investment-europe-vs-us/", "chapter": "Europe", "question": "How does AI investment in Europe compare with the US?", "answer": "Private investment in AI companies was 12 to 14 times higher in the US than in Europe in 2025: $285.9 billion against $20.9 billion. The gap is about companies that build AI; among firms that use it, Europe roughly matches the US. Most public money is announced, not yet spent.", "range": { "low": 12, "high": 14, "unit": "times more private AI investment in the US than in Europe, 2025", "display": "12–14× more private AI investment in the US than in Europe (2025)" }, "confidence": "high", "confidence_reason": "Two independent creators using different deal databases and scopes (all private investment for Europe, venture capital for the EU27) agree on a US advantage of 12 to 14 times in 2025.", "last_checked": "2026-10-14", "how_to_read": "This measures money for companies that build AI, from deal databases that miss undisclosed deals and government funds. Investment by ordinary firms in using AI is a different measure and shows near parity (below). The OECD notes that AI-related investment inside EU firms and the public sector may be far larger than venture capital: up to €294 billion in 2023 in experimental estimates. Public pledges are shown separately because announced is not spent.", "sources": [ { "creator": "Stanford Institute for Human-Centered AI (data from Quid)", "title": "The 2026 AI Index Report, chapter 4 (Economy)", "year": 2026, "sample": "Disclosed private investments in AI companies raising over $1.5 million, by headquarters", "method": "Commercial deal database; Europe appears to include the UK. Government funds are not counted.", "figure": "2025 private AI investment: US $285.9 billion, Europe $20.9 billion (13.7 times; our arithmetic), China $12.4 billion; UK $5.9 billion, France $4.4 billion, Germany $3.9 billion. US grew 160% from 2024, Europe 7%", "url": "https://hai.stanford.edu/assets/files/ai_index_report_2026.pdf", "quote": "United States was the global leader with nearly $285.9 billion total invested" }, { "creator": "OECD (data from Preqin)", "title": "Venture capital investments in artificial intelligence through 2025 (OECD policy brief)", "year": 2026, "sample": "Preqin deal data, updated January 2026", "method": "Venture capital deals in AI firms, by firm location; EU27 without the UK", "figure": "2025 AI venture capital: US $194 billion (75%), EU27 $15.8 billion (6%; 12.3 times less, our arithmetic), UK $13.8 billion", "url": "https://www.oecd.org/en/publications/venture-capital-investments-in-artificial-intelligence-through-2025_a13752f5-en.html", "quote": "followed by the EU27 (6%, USD 15.8 billion)" } ], "related_findings": [ { "question": "How much private AI investment goes to Germany?", "answer": "$3.9 billion in 2025, third in Europe after the UK ($5.9 billion) and France ($4.4 billion). Germany had 92 newly funded AI companies, against 1,953 in the US, and $17.2 billion of private AI investment in total from 2013 to 2025, against $757.3 billion in the US (Stanford AI Index).", "sources": [] }, { "question": "Do European companies invest in using AI as much as US companies?", "answer": "Roughly, yes. 37% of EU firms invest in or systematically use generative AI tools, against 36% of US firms, and 39% in Germany (EIB, 2025). The difference is breadth: 81% of US firms using AI apply it in two or more business areas, against 55% in the EU. See F-36.", "sources": [ { "creator": "European Investment Bank", "title": "EIB Investment Survey 2025: European Union overview", "year": 2025, "sample": "12,033 EU firms and a smaller US sample, April to July 2025", "method": "Telephone survey, weighted by value added", "figure": "Generative AI tools: EU 37%, US 36%, Germany 39%; EU large firms 47%, SMEs 27%", "url": "https://www.eib.org/attachments/lucalli/20250216-141025-econ-eibis-2025-eu-en.pdf", "quote": "Around 37% of EU firms use generative artificial intelligence, in line with US firms." } ] }, { "question": "How much public money is the EU putting into AI?", "answer": "Mostly announced, not yet spent. InvestAI (February 2025) aims to mobilize €200 billion, mostly from private and other partners, including a €20 billion fund for AI gigafactories. The gigafactory call opened only on 30 July 2026 with up to €10 billion in EU and national funding, closes 12 November 2026, and awards are expected in early 2027. AI factories are co-financed with €10 billion. No total for money spent has been published.", "sources": [ { "creator": "European Commission", "title": "EU launches InvestAI initiative to mobilise €200 billion of investment in artificial intelligence (IP/25/467)", "year": 2025, "sample": "Policy announcement, 11 February 2025", "method": "Press release; a mobilization target", "figure": "Aim to mobilize €200 billion, including a €20 billion gigafactory fund", "url": "https://ec.europa.eu/commission/presscorner/detail/en/ip_25_467", "quote": "an initiative to mobilise €200 billion for investment in AI" }, { "creator": "European Commission", "title": "EU launches AI Gigafactories call (IP/26/1708)", "year": 2026, "sample": "Policy announcement, 30 July 2026", "method": "Press release; funding available under an open call", "figure": "Up to €10 billion in EU and national funding for up to seven gigafactories; call closes 12 November 2026", "url": "https://ec.europa.eu/commission/presscorner/detail/en/ip_26_1708", "quote": "supported by up to €10 billion in EU and national funding" } ] } ], "numbers_you_may_have_seen": [ { "claim": "The EU is investing €200 billion in AI (InvestAI).", "what_the_source_says": "The Commission's wording is a target to mobilize €200 billion, mostly from private and other partners. No spending total has been published." }, { "claim": "The US invests 23 times more in AI than Europe.", "what_the_source_says": "23 times is the US compared with China. Against Europe it is about 13.7 times." }, { "claim": "European companies lag US companies in adopting AI.", "what_the_source_says": "Among firms using it, the EIB finds 37% of EU and 36% of US firms invest in generative AI tools. The gap is in breadth of use and in money for AI builders." }, { "claim": "The EU has a €20 billion AI gigafactory fund.", "what_the_source_says": "Announced in February 2025; the call opened in July 2026 with up to €10 billion in public funding, and no awards are due before early 2027." } ], "citation": "EVY (2026). How does AI investment in Europe compare with the US? The AI at Work Fact Book, F-40. https://evy.so/facts/ai-investment-europe-vs-us/ (last checked October 14, 2026). CC BY 4.0.", "license": "CC BY 4.0" } ] }