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AI Statistics 2026

Sixty numbers on how businesses and people use AI, what it costs, who is paying for it and what it is doing to work. Each one links to the report, survey or company filing it came from, with the date it was published, so you can check it and cite it.

60 statistics · Updated Nov 12, 2026 · Every source checked Nov 12, 2026

Key findings

Business adoption

How many companies use AI, and how far it has spread inside them. Surveys of large firms report far higher use than official counts of all businesses, because most small firms have not started.

88% of surveyed organizations used AI in 2025

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44% of survey respondents say AI is scaling across their whole enterprise, up from 38% a year earlier

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56% of respondents say their organizations use AI in three or more business functions

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40% of respondents at large organizations report scaling AI agents, up from 27% the year before

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32% of organizations decided not to buy at least one software product because they could build it with agentic coding tools

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19.8% of U.S. businesses used AI as of May 2026, the national rate in the Census Bureau survey

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37% of U.S. firms with at least 250 employees reported using AI in their operations

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20.0% of EU enterprises with 10 or more employees used AI technologies in 2025, up from 13.5% in 2024

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78% of the U.S. labor force works at firms that have adopted AI, by an employment weighted estimate

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What it means: Use is close to universal among large companies, yet the official U.S. and EU counts sit near one firm in five. The gap is company size: big firms with data teams adopted early, while most small businesses still have not. The next shift in these numbers is depth, not reach: more functions per company and more agents moving from pilots into daily work.

Consumer and workplace use

Who uses AI tools, how often and for what. ChatGPT is the best measured product, so many of these figures come from it.

1 billion or more people use ChatGPT every week as of August 2026

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50 million or more people pay for a ChatGPT subscription as of March 2026

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34% of U.S. adults say they have ever used ChatGPT, about double the share in 2023

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58% of U.S. adults under 30 have used ChatGPT, up from 33% in 2023

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28% of employed U.S. adults say they use ChatGPT for work

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53% of the population had adopted generative AI within three years of its launch, faster than the PC or the internet

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$172 billion a year is the estimated value U.S. consumers get from generative AI tools as of early 2026

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41% of U.S. workers use generative AI for work, per the Real-Time Population Survey in November 2025

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58% of employees worldwide used AI at work on a semiregular or regular basis in 2025

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What it means: AI chat tools went from new to normal faster than the PC or the internet did. Use skews young, and a large share of it now happens at work, often before a company has a formal policy. Paying users are still a small fraction of weekly users, which is why the big AI companies are adding ads and cheaper tiers.

Market size and revenue

What the world spends on AI, and what the largest AI companies earn from it.

$2.7 trillion is the forecast for worldwide AI spending in 2026, up 49.5% from 2025

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117% is the forecast 2026 growth in spending on generative AI models

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$89.0 billion in data center revenue for Nvidia in its quarter ended July 2026, up 117% from a year earlier

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$2B in revenue per month for OpenAI as of March 2026

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$47 billion in run-rate revenue for Anthropic, crossed in May 2026

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$1 billion annualized revenue run rate for ChatGPT Ads, reached in under 200 days after launch

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$150 billion or more in annual capital spending was reported by Google in 2025 as cloud providers built out AI capacity

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half a trillion dollars was invested in data centres worldwide in 2024, nearly double the 2022 level

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What it means: Spending forecasts now run into the trillions because they include the chips, servers and data centres behind every model. Revenue is real and growing fast at the model makers, but most of the money still flows to hardware: one chip maker books more in a quarter than the leading AI labs earn in a year.

Investment and funding

Private and public money going into AI companies, and how concentrated it is.

$285.9 billion of private AI investment went into U.S. companies in 2025, more than 23 times the amount in China

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127.5% was the growth in private AI investment in 2025, the fastest growing type of corporate AI investment

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200% or more was the growth in generative AI private funding, which took nearly half of all private AI funding

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1,953 newly funded AI companies were in the U.S. in 2025, more than 10 times the next country

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$122 billion in committed capital was raised by OpenAI in one round, at an $852 billion post money valuation

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$65 billion was raised by Anthropic in its Series H round, at a $965 billion post money valuation

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$20.4 billion is what the U.S. government put into AI contracts and grants from 2013 to 2024, far below private investment

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$184 billion was deployed into AI firms by Chinese government guidance funds between 2000 and 2023, by estimate

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What it means: Private money into AI more than doubled in a year, and most of it went to U.S. companies. Single funding rounds for the top labs are now larger than the total that some countries invest. Government spending looks small next to these sums in the U.S., while China leans on state guidance funds that do not show up in private investment counts.

Jobs, skills and productivity

What AI is doing to pay, hiring and output. Early evidence is mixed: wage premiums and productivity gains on one side, fewer entry level roles on the other.

56% average wage premium for workers with AI skills in 2024, double the 25% of the year before

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66% faster is the rate at which the skills employers seek are changing in jobs most exposed to AI

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3x higher growth in revenue per employee was seen in industries most exposed to AI (27% vs 9%)

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41% of employers plan to reduce their workforce as AI automates certain tasks

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39% of respondents expect AI to reduce total employment at their organization in the coming year, up from 32%

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80% of respondents say AI has improved their individual productivity

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nearly 20% is how far employment of software developers aged 22 to 25 has fallen since 2024

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26% productivity gain from AI is reported by studies of software development, with 14% to 15% in customer support

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64% of Americans expect AI to lead to fewer jobs over the next 20 years, while only 5% expect more

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What it means: Workers with AI skills earn a clear premium, and studies find real productivity gains in coding, support and marketing. At the same time, a large share of employers plan smaller teams, and entry level software jobs have already fallen. The early cost of AI lands on people starting their careers, while the gains go to those who already have experience.

Models, costs and compute

How capable models have become, how cheap they are to run and how much power they need.

near 100% is where top scores on the SWE-bench Verified coding benchmark reached in 2025, up from 60% a year earlier

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66.3% success rate for AI agents on OSWorld computer tasks, up from roughly 12%

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50.6% is how often the top AI model read analog clocks correctly, against 90.1% for humans

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280-fold drop in the inference cost of a GPT-3.5 level system between November 2022 and October 2024

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17.1 million H100 equivalents is the global AI compute capacity, growing 3.3x a year since 2022

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29.6 GW of power capacity in AI data centers, comparable to New York state at peak demand

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415 TWh of electricity was used by data centres in 2024, around 1.5% of world consumption

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945 TWh is the projected data centre electricity use by 2030, more than double the 2024 level

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1.9 GW of compute was available to OpenAI in 2025, up from 0.2 GW in 2023

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What it means: Models solve coding tasks that were out of reach two years ago, while still failing at simple things like reading a clock. Running them has become hundreds of times cheaper, which is why AI features now appear in ordinary software. The limit has moved to electricity: data centre demand is set to more than double by 2030.

Trust, risk and regulation

What the public and experts think about AI, and how much they trust anyone to govern it.

50% of Americans are more concerned than excited about the growing use of AI in daily life, up from 37% in 2021

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57% of Americans rate the societal risks of AI as high, while 25% rate its benefits as high

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76% of Americans say it is extremely or very important to be able to tell if content was made by AI or people

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73% of AI experts expect a positive impact on how people do their jobs, against 23% of the U.S. public

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31% of Americans trust their own government to regulate AI, the lowest of any country surveyed

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59% of people worldwide say AI products offer more benefits than drawbacks, while 52% say they make them nervous

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41% of Americans say federal AI regulation will not go far enough, against 27% who say it will go too far

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362 documented AI incidents were recorded in 2025, up from 233 in 2024

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What it means: People use AI more each year and trust it less. Concern outweighs excitement in the U.S., experts are far more optimistic than the public, and few Americans trust their government to regulate it. Recorded AI incidents keep rising, which feeds the demand for labels that show when content was made by AI.

How we collect these numbers

We take numbers only from primary sources: company announcements and filings, government statistics offices, and named surveys and research reports such as the Stanford AI Index, McKinsey, Pew Research Center, Gartner and the IEA. Each figure is copied from the source page, and the page is opened again when this list is updated. Survey figures describe the people or firms the survey asked, not the whole world. Revenue and funding figures are what the companies themselves reported. If you find an error, tell us through the contact page and we will check it against the source.

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