Generative AI Adoption

FRED has incorporated '137 data series about the adoption of generative artificial intelligence (AI) technology in the United States, reported by Alexander Bick, Adam Blandin, and David Deming' (FRED Announcements, Jul 24, 2026). The RPS GenAI module, fielded quarterly since August 2024, now publishes as official FRED series covering usage rates (overall, work, nonwork), time savings, and adoption compared with the PC and internet, with industry and occupation breakdowns. Latest FRED readings: work adoption 43.4% and overall adoption 57.9% of working-age adults in Q1 2026 (RPSGENAIUSAGESHAREWORK, RPSGENAIUSAGESHAREALL); GenAI-assisted work hours 6.3% in Q2 2026, up from 4.1% in Q4 2024 (RPSGENAIASSISTWRKHRSALL); reported time savings 2.2% of work hours in Q1 2026 (RPSGENAITSALL).

Google's AI & Economy ATLAS v1.0 (Iscenko, Strand, Chen, Imas, Manyika et al., Google/Google DeepMind, Jul 23 2026; reviewed by Diane Coyle and David Autor). 15M de-identified interactions across Gemini App, AI Mode, and Gemini API (Apr 6-19, 2026), mapped to 800+ occupations, 4,000 O*NET tasks, 300 ATUS activities, 150 countries, 140 languages. Work: 'AI adoption spans occupations covering just above 88% of US employment' (68% of detailed occupations) but 'penetration remains shallow' — 'AI is used for only 21% of total tasks in the median occupation with any AI use'; only 3% of occupations show usage for >75% of tasks. 'Attempts to automate tasks end-to-end represent less than 10% of AI conversations in non-routine cognitive work'; >25% for routine cognitive work. Non-routine cognitive tasks = 35% of O*NET universe but 65% of work interactions. Wages: 'a 1% increase in an occupation's median earnings is associated with a more than 2.5% increase in AI usage intensity'; Gemini-weighted median salary $82,919 vs $62,252 employment-weighted national median. Home: 86% of conversational use is non-work; government/civic queries over-represented ~20x vs time spent; household time-savings valued at $14.9B-$149B/yr (0.5-5% scenarios). Global: 1% GDP/capita ↑ → 0.9% usage ↑; English only ~1/3 of conversations across 143 languages.

"More than half of U.S. workers (52%) now use AI in their role, with 30% using it frequently (a few times a week or more). Fifteen percent use it daily." 47% of employees say their organization has integrated AI tools, up from 41%. Fielded May 6-20, 2026 among 22,573 employed U.S. adults, margin of error +/-0.9 percentage points. The 52% figure counts anyone using AI at least a few times a year, a looser threshold than the quarterly survey charted here, so it appears below the chart as a directional signal rather than as a plotted point.

Anthropic's June 2026 Economic Index 'Cadences' report combines anonymized Claude usage patterns with a survey of ~9,700 Claude users. Headline findings: about half of surveyed users report AI can already handle 50% or more of their work tasks; 4% say Claude could perform their entire job today; more than one-third expect AI to do most or nearly all of their work tasks within 12 months. The report also documents a widening 'cadence' gap between experienced and newcomer Claude users — experienced users automate substantially more of their work. Biggest automation increases occur in business sales, automated trading, and routine market-research tasks, flagging those roles as near-term automation candidates.

Anthropic Economic Research (Lyttelton, Massenkoff, Wilmers — May 27, 2026). Survey of 1,260 quantitative social scientists. '81% of respondents said yes' to using generative AI to aid research. '20% of respondents use coding agents' regularly (weekly). '86% of users reporting Claude Code use.' Demographic disparities: 'those with typically male names have adopted coding agents at more than twice the rate of respondents with typically female names.' Career stage: 'Just over a quarter of doctoral students and postdocs use coding agents' vs tenured professors at less than half that rate. University prestige: 'Researchers at top universities are 40% more likely than others to use coding agents.' Task usage: '97% of coding agent users and 77% of other AI users report using it to generate code.' Productivity effects over 6 months: users show approximately 'a quarter of a paper more' in project starts and 'around a half of a working paper more' in working papers, but 'no evidence that coding agent users are submitting more new papers to journals.' '88% of respondents were above a 5' on 10-point AI productivity scale.

responses to a recent survey suggest that most forecasters are quite optimistic about AI's potential but are assuming only a slow pace of AI adoption through 2030

Generative AI Adoption Tracker (Bick, Blandin, Deming), May 2026 update: '45.2% of the employed respondents used genAI for work.' Based on the Real-Time Population Survey (RPS), a nationally representative online labor market survey of US adults 18-64 running continuously since 2020. Tracker visualizes findings from 8 combined survey waves encompassing approximately 40,000 respondents, weighted to be nationally representative.

Hundreds of millions of people use artificial intelligence (AI) for writing assistance.

The mean productivity rating was 5.1, corresponding to 'substantially more productive'... the most common productivity enhancement is in scope, which was cited by 48% of users who explicitly mentioned productivity effects. 40% of users who mentioned productivity emphasized speed.

In 23% (41%, employment-weighted) of firms, workers use AI in work-related tasks. Writing, document analysis, and information search are the leading Generative AI use in tasks, though 65% of firms limit use to three or fewer tasks.

Metaculus community forecasts for 2030 and 2035: overall US employment -1.9%/-3.4%; most vulnerable AI-exposed occupations -11.4%/-17.2%; software developers -15.1%/-22.3%; financial specialists -8.1%/-15.3%; services sales -11%/-14%; lawyers -5.4%/-9.6%; designers -4%/-8.4%; K-12 teachers -1.3%/+1.3%; overall median wage -0.6%/+1.4%; percent workers using AI daily 52.5%/70.9%; new-grad unemployment ~10%/12%.

We find that ChatGPT is used about 3x more in the kinds of jobs our framework identifies as most at risk of automation. This is true even when AI can perform similar tasks in less affected jobs. That gap between capabilities and usage makes the limitation of exposure-only measures clear: capability alone doesn't tell us where change in the labor market is actually happening.

Among currently employed respondents, 39 percent report that they are either using AI tools in their current job or have used AI tools in their jobs in the last twelve months. College graduates are more than twice as likely to have used AI tools at work in the past twelve months as those without a college degree (58.7 percent versus 22.9 percent). AI adoption rises from 15.9 percent among workers earning under $50,000 to 66.3 percent among those earning over $200,000 annually. Around 38 percent of employed respondents said that having training in how to use AI tools is important to them, yet only 15.9 percent report that their employer currently offers any AI training.

Generative AI reached 53% population adoption within three years, faster than the personal computer or the internet, though the pace varies by country and correlates strongly with GDP per capita. Some show higher-than-expected adoption, such as Singapore (61%) and the United Arab Emirates (54%), while the U.S. ranks 24th at 28.3%.

28% of employed U.S. adults use AI a few times a week or more; 13% use daily (up from 10% in 2024). 41% of employees report their organization has integrated AI tools. 23% in AI-adopting orgs report workforce reductions vs. 16% in non-adopting. Survey of 23,717 employed adults, margin of error +/-0.9pp.

The right panel of figure 2 shows that work-related GenAI adoption reported in the RPS stands at about 41 percent of the workforce, and non-work-related usage at about 50 percent of the population as of the latest survey in November 2025. These metrics grew by about 31 percent (9.7 percentage points) and 26 percent (10.4 percentage points), respectively, for the year ending in November.

Work Hours Assisted by Generative AI. In 2030, they estimate the percentage of assisted work hours will be 10.1% for the unconditional scenario, 8.0% for the slow, 12.9% for the moderate, and 24.2% for the rapid, compared to a 2024 estimate of 3.35%. By 2050, they expect this to surge to 40.0% (unconditional), 25.0% (slow), 44.7% (moderate), and 62.0% (rapid).

69 economists' median unconditional forecast: 10.1% of work hours GenAI-assisted by 2030. Rapid scenario (14% prob): 62% of work hours by 2050.

Number of AI applications grew 6x from 2022-2024 (TAAFT dataset), but the set of work activities they cover expanded only 1.2x. Adoption is intensifying within a narrow band of activities rather than broadening.

people in this higher-tenure group have a 10% higher success rate in their conversations, an association that is not explained by their task selection, country of origin, or other factors.

PMs and marketers should default to an AI interface. These functions should be doing 80-100% of their work through a chat interface.

Today, AI apps have crossed 1 billion weekly active users and ChatGPT alone accounts for 900M of that.

in 2026 we find that 43% of US workers use AI for their job compared with 32% among European workers in our surveys.

55% are seeing slight or significant adoption (employees beginning to accept and integrate agents in their work).

Applying the Pangram AI-text detector to a random sample of 1,600 federal civil complaints (200/year, 2019-2026): the share of complaints classified as AI-generated rose monotonically from 1.0% in 2023 to 3.5% in 2024, 10.5% in 2025, and 18.0% in early 2026, against a pre-AI false-positive rate of 0.1% (1 of 800).

Identifies five categories of labor-affecting technology: labor-augmenting, capital-augmenting, automating, expertise-leveling, and new task-creating. Only new task-creating technologies are unambiguously pro-worker because they expand the range of valuable work humans can do and raise the value of human expertise; the other four can lift productivity while reducing the scarcity value of expertise. Cites Schneider Electric AI tool for field electricians that cuts average maintenance-report completion time roughly in half as augmentation evidence. As reported in MIT Sloan Ideas Made to Matter, June 17, 2026.

36.8% of individuals across OECD used generative AI in 2025. 20.2% of firms used AI in 2025 (up from 8.7% in 2023). 41.1% of employed individuals used generative AI. 52.0% of large firms vs 17.4% small.

Only about 43% of US workers reported regularly using AI at work last year

AI skills significantly increase interview invitation probabilities by approximately 8 to 15 percentage points, compared with candidates without such skills

Workforce access to AI has expanded by 50% in just one year—growing from under 40% to under 60% of workers now equipped with sanctioned AI tools.

85% of employees report saving one to seven hours per week using AI. Employees who use AI every day are overwhelmingly optimistic – more than 90% believe it will help them succeed.

Gender gap in AI adoption: women adopt less; 5.3 percentage point gap in UK data.

50% of SMEs report that their employees lack the skills to use generative AI.

14.03% of post-LLM applications on Freelancer.com utilized the platform's AI writing tool, indicating rapid adoption of generative AI in job application workflows.

Snapshot of the GenAIAdoptionTracker.com dashboard at the time of ingestion (Nov 2025). Used here for the Feb 2025 (33.5%) and May 2025 (35.5%) quarterly waves — both estimated from the tracker chart before those results were published in the working paper. Later quarterly waves are captured in separate source entries (bick-blandin-deming-wp-2025 for Aug/Nov 2025; bick-deming-mind-the-gap-2026 for Feb 2026; genai-adoption-tracker-may-2026 for May 2026). The underlying RPS runs continuously and updates each quarter.

23% of employed workers used generative AI at work weekly as of late 2024. Share of work hours with GenAI increased from 4.1% (Nov 2024) to 5.7% (Aug 2025). GenAI may have increased aggregate labor productivity by up to 1.3%.

Nationally representative survey of 25,000+ working-age adults finds generative AI adoption reached 55.9% overall and 40.7% at work by November 2025, outpacing PC and internet adoption at comparable points post-launch.

Pew Research Center (Sidoti & McClain), '34% of U.S. Adults Have Used ChatGPT, About Double the Share in 2023' — Jun 25, 2025. Survey of 5,123 U.S. adults via American Trends Panel, Feb 24 - Mar 2, 2025. Overall: '34% of U.S. adults say they have ever used ChatGPT' (up from ~17% in summer 2023). By age: under-30 = 58% (up from 43% in 2024); 30-49 = 41%; 50-64 = 25%; 65+ = 10%. By education: postgrad 52%; bachelor's 51%; some college 33%; HS or less 18%. Work usage (employed adults): overall 28% (up from 8% in early 2023); 18-29 = 38%; 30-49 = 30%; 50+ = 18%; postgrad 45%; bachelor's 36%. Other use cases: learning 26% (up from 8% in 2023); entertainment 22% (up from 11% in 2023). Awareness: 79% have heard at least a little about ChatGPT (up from 58% in March 2023).

AI-assisted coding jumped from around 5% in 2022 to nearly 30% in Q4 2024.

GitHub Copilot saves 26 minutes per day across 20,000 UK civil servants.

We describe our research with 21 developers at the cutting edge of using AI

75% of knowledge workers use AI at work. 78% bring their own AI tools. Survey of 31,000 workers across 31 countries.

56% of Americans use AI tools; 28% weekly. Skepticism about AI's effects increased 8 percentage points year over year.

almost two-thirds (59%) say their department is currently using AI while one-third (31%) of respondents are experimenting with its use

About 20% use AI professionally; 57% personal use. Adoption varies significantly by education and income.

Among 595 business school students in Norway, male students were 25 percent more likely to be high AI users, and the gap was widest among the highest-performing women.

Almost half of US households use generative artificial intelligence tools. Average expected probability of higher productivity: 30%; of job loss: 13%.