AI Statistics 2026
By Axis Intelligence Research
Co-author: Sarah Mitchell | Last updated: October 27, 2026 | License: CC BY 4.0
Gartner now forecasts worldwide AI spending of $2.67 trillion in 2026, after raising its own 2026 number three times this year. Over the same months, McKinsey found the share of companies attributing any EBIT impact to AI stuck at 37%. According to Axis Intelligence Research, that split between money in and payoff out is the defining AI statistic of late 2026.
Quick Answer: The AI Numbers That Matter in October 2026
- $2.67 trillion: worldwide AI spending forecast for 2026, up 49.5%, with $3.64 trillion forecast for 2027 (Gartner, September 16, 2026).
- $581.7 billion: global corporate AI investment in 2025, up 129.9% (Stanford HAI AI Index 2026).
- 900 million: weekly ChatGPT users, company-reported in February 2026 (OpenAI).
- 24.6%: share of US businesses using AI in any business function, up from 17.7% in January (U.S. Census Bureau BTOS, October 2026).
- 13.6%: the Axis Intelligence Research AI Scale-to-Payoff Conversion Rate (SPCR) for 2026, down from 15.8% in 2025.
Key Findings
- According to Axis Intelligence Research, Gartner raised its 2026 worldwide AI spending forecast by $142.6 billion (5.6%) between January and September 2026, and its 2027 forecast by $300.6 billion (9.0%).
- According to Axis Intelligence Research, only 13.6% of the organizational footprint that is scaling AI enterprise-wide converts into material EBIT impact in 2026, down from 15.8% in 2025, based on McKinsey’s State of AI survey.
- McKinsey’s 2026 State of AI survey of 1,719 respondents found 44% of organizations scaling AI across the enterprise, up from 38%, while the share reporting any EBIT impact held at 37%.
- NVIDIA reported $89.0 billion in Data Center revenue for the quarter ended July 26, 2026, up 117% year over year, per its SEC filing.
- According to Axis Intelligence Research, US adults use generative AI at 2.3 times the rate US businesses report using AI (56% versus 24.6%), which is why AI adoption statistics disagree so sharply.
How Much Is Being Spent on AI in 2026?
Worldwide AI spending is forecast at $2.67 trillion in 2026, a 49.5% increase over 2025, according to Gartner’s September 16, 2026 forecast. Gartner puts 2025 spending at $1.79 trillion and 2027 at $3.64 trillion, which implies 36.2% growth next year by Axis Intelligence Research’s calculation.
Infrastructure carries the number. AI infrastructure (servers, networking, semiconductors and infrastructure services) is forecast at $1.48 trillion in 2026, or 55.6% of all AI spending. AI services follow at $576.5 billion, AI software at $461.6 billion, and AI cybersecurity at $51.3 billion.
Worldwide AI Spending by Segment, 2026
| Segment | 2026 forecast | Share of total | Source |
|---|---|---|---|
| AI infrastructure | $1.48 trillion | 55.6% | Gartner, Sep 2026 |
| AI services | $576.5 billion | Gartner, Sep 2026 | |
| AI software | $461.6 billion | Gartner, Sep 2026 | |
| AI cybersecurity | $51.3 billion | Gartner, Sep 2026 | |
| Total AI spending | $2.67 trillion | 100% | Gartner, Sep 2026 |
Source: Gartner press release, September 16, 2026. Share calculated by Axis Intelligence Research.
How Gartner’s AI Spending Forecast Moved During 2026
This table is an Axis Intelligence Research snapshot of the same forecaster revising itself. It tracks one methodology across three editions, so the movement is real rather than definitional.
| Gartner edition | 2026 forecast | 2027 forecast | 2026 growth stated | Source |
|---|---|---|---|---|
| January 15, 2026 | $2.53 trillion | $3.34 trillion | 44% | Gartner |
| May 19, 2026 | $2.60 trillion | $3.49 trillion | 47% | Gartner |
| September 16, 2026 | $2.67 trillion | $3.64 trillion | 49.5% | Gartner |
| Revision, Jan to Sep | +$142.6 billion (+5.6%) | +$300.6 billion (+9.0%) | Axis Intelligence Research calculation |
Sarah Mitchell’s read: A forecast that rises every quarter is telling you about supply, not demand. The revisions sit almost entirely in infrastructure, which means hyperscalers bought ahead of the workloads. The 2027 number grew twice as fast as the 2026 number, so the build-out bet is getting longer, not shorter. What would reverse it: a quarter where hyperscaler capex guidance falls while cloud growth holds.
How Much Money Went Into AI Companies?
Global corporate AI investment reached $581.7 billion in 2025, up 129.9% from $253 billion in 2024, per the Stanford HAI AI Index 2026, Chapter 4. Corporate investment combines private funding, mergers and acquisitions, minority stakes and public offerings. Private investment alone was $344.7 billion (up 127.5%), and AI mergers and acquisitions were $214.4 billion.
Generative AI companies raised $170.9 billion in private funding in 2025, nearly half of all private AI investment. The deal sizes stretched: 28 private AI rounds exceeded $1 billion in 2025, up from 15 in 2024, and the average private AI deal rose to $66.5 million. There were 3,499 newly funded AI companies worldwide, 1,953 of them in the United States.
Private AI Investment by Country, 2025
| Country or region | Private AI investment 2025 | Source |
|---|---|---|
| United States | $285.9 billion | Stanford HAI AI Index 2026 |
| Europe | $20.9 billion | Stanford HAI AI Index 2026 |
| China | $12.4 billion | Stanford HAI AI Index 2026 |
| United Kingdom | $5.9 billion | Stanford HAI AI Index 2026 |
US private AI investment was 23.1 times China’s. That ratio understates China, because Stanford estimates Chinese government guidance funds deployed $184 billion into AI firms between 2000 and 2023, outside the private tally. Inside the US, California alone took $218 billion. For the funding round detail and quarterly flows, see our AI investment statistics, and for the country comparison, our China AI statistics.
OpenAI is the single largest recipient. OpenAI announced $110 billion in new investment at a $730 billion pre-money valuation on February 27, 2026, per its own announcement.
Is AI Infrastructure Spending Still Accelerating?
Yes, on every filed number. Alphabet’s purchases of property and equipment were $44.9 billion in Q2 2026, versus $22.4 billion a year earlier, per Alphabet’s Q2 2026 earnings release. By Axis Intelligence Research’s calculation, that is 100.1% growth. Alphabet’s free cash flow for the quarter was negative $5.9 billion, while Google Cloud revenue rose 82% to $24.8 billion.
Meta spent $34.9 billion on capex including finance lease principal in Q3 2026, against $19.4 billion a year earlier, per Meta’s Q3 2026 release filed October 21, 2026. That is 80.2% growth, and Meta narrowed its 2026 capex outlook to $135 billion to $145 billion.
The chip side confirms it. NVIDIA reported revenue of $96.2 billion for the quarter ended July 26, 2026, with Data Center revenue of $89.0 billion, up 117% year over year, per NVIDIA’s SEC filing. Annualized, that Data Center line is a $356 billion run-rate by Axis Intelligence Research’s arithmetic (a run-rate, not company guidance). NVIDIA guided Q3 revenue to $108.0 billion.
How long hyperscalers can fund this from operating cash is tracked by our Capex Funding Self-Sufficiency Ratio on the AI bubble statistics page, and quarter-by-quarter company capex sits in the AI capex tracker.
How Many People Use AI in 2026?
ChatGPT had more than 900 million weekly users and more than 50 million consumer subscribers as of February 27, 2026, according to OpenAI (company-reported). OpenAI also reported 9 million paying business users.
In the United States, 49% of adults say they use AI chatbots and 44% use ChatGPT, per Pew Research Center’s survey of 5,119 US adults fielded February 17 to 23, 2026. In August 2024, 33% had used a chatbot. And 36% of US adults now interact with AI several times a day or almost constantly.
AI Use by Country, Second Half of 2025
Microsoft’s telemetry-based AI diffusion measure, reported in the Stanford AI Index, ranks countries by the share of the population using AI tools.
| Country | AI diffusion, H2 2025 | Source |
|---|---|---|
| United Arab Emirates | 64.0% | Microsoft AI Economy Institute via Stanford HAI |
| Singapore | 60.9% | Microsoft AI Economy Institute via Stanford HAI |
| Norway | 46.4% | Microsoft AI Economy Institute via Stanford HAI |
| United Kingdom | 38.9% | Microsoft AI Economy Institute via Stanford HAI |
| South Korea | 30.7% | Microsoft AI Economy Institute via Stanford HAI |
| Germany | 28.6% | Microsoft AI Economy Institute via Stanford HAI |
| United States (24th) | 28.3% | Microsoft AI Economy Institute via Stanford HAI |
The US ranks 24th despite leading in investment and model development. Country-level detail lives on our AI adoption statistics and Africa AI statistics pages.
Why Do AI Adoption Statistics Disagree So Much?
Because they count different things. The same country, the United States, produces four defensible adoption numbers that run from 24.6% to 56%. According to Axis Intelligence Research, these figures should be published side by side and never averaged, because each measures a different population.
| What is measured | US figure | As of | Source |
|---|---|---|---|
| Adults using generative AI | 56% | Early 2026 | Bick et al., cited in Stanford HAI AI Index 2026 |
| Adults using AI chatbots | 49% | Feb 2026 | Pew Research Center |
| Population using AI (device telemetry) | 28.3% | H2 2025 | Microsoft AI Economy Institute via Stanford HAI |
| Businesses using AI in any function | 24.6% | Oct 18, 2026 | U.S. Census Bureau BTOS |
According to Axis Intelligence Research, US adults use generative AI at 2.3 times the rate US businesses report using AI. Workers bring the tools to work before employers formalize them, and the Census question counts firms, most of which are small.
One widely repeated figure needs correcting. The “53% adoption within three years” statistic in the AI Index refers to US adults aged 18 to 64, measured by a US population survey, and compares generative AI with the US personal computer and internet curves. It is not a global adoption rate, as our earlier version of this page stated.
AI Use by US Businesses, by Firm Size and Sector
The Census Bureau’s Business Trends and Outlook Survey (BTOS) is a biweekly, nationally representative survey of US employer businesses. Its AI question changed on November 17, 2025, from AI use “in producing goods or services” to use “in any business function,” so earlier readings are not comparable. The Census Bureau now also words the item as “Super Intelligence or SI (formerly referred to as Artificial Intelligence or AI).”
The latest cycle, collected October 5 to 18, 2026 and published October 22, puts US business AI use at 24.6%, up from 23.8% two weeks earlier and 17.7% in the first cycle of 2026. According to Axis Intelligence Research, that is a 6.9-point gain in ten months. Expected use over the next six months is 28.6%.
| US business segment | AI use rate | As of | Source |
|---|---|---|---|
| All US businesses | 24.6% | Oct 18, 2026 | U.S. Census Bureau BTOS |
| Information sector | 46.4% | Oct 18, 2026 | U.S. Census Bureau BTOS |
| Professional, scientific and technical services | 43.8% | Oct 18, 2026 | U.S. Census Bureau BTOS |
| Finance and insurance | 40.5% | Oct 18, 2026 | U.S. Census Bureau BTOS |
| Manufacturing | 22.9% | Oct 18, 2026 | U.S. Census Bureau BTOS |
| Retail trade | 18.5% | Oct 18, 2026 | U.S. Census Bureau BTOS |
| Accommodation and food services | 10.7% | Oct 18, 2026 | U.S. Census Bureau BTOS |
| Firms with 250+ employees | 37% | May 3, 2026 | U.S. Census Bureau |
| Firms with 100 to 249 employees | 32% | May 3, 2026 | U.S. Census Bureau |
In the European Union, 19.95% of enterprises with 10 or more employees used at least one AI technology in 2025, up from 13.48% in 2024, per Eurostat’s enterprise AI dataset. Rates range from 42.03% in Denmark, 37.82% in Finland and 35.04% in Sweden to 25.97% in Germany, 18.16% in France and 5.21% in Romania. The survey-versus-Census gap is analyzed in depth on our AI in business statistics page.
Is AI Paying Off for Companies?
Not at the enterprise level yet. McKinsey’s State of AI 2026, fielded May 4 to June 8, 2026 with 1,719 respondents in 97 nations, found 37% of respondents attributing any EBIT impact to AI, essentially unchanged from 2025. AI high performers, defined by McKinsey as those attributing at least 5% of EBIT to AI and reporting significant value, stayed at about 6%.
Deployment kept deepening anyway. The share of organizations scaling AI across the enterprise rose to 44% from 38%, and use in three or more business functions rose to 56% from 51%. Individually, 80% of respondents say AI has improved their own productivity.
The AI Scale-to-Payoff Conversion Rate (SPCR)
Axis Intelligence Research created the AI Scale-to-Payoff Conversion Rate (SPCR) to answer one question: as more organizations scale AI, does payoff keep up?
SPCR = (share of AI high performers ÷ share of organizations scaling AI enterprise-wide) × 100
| Input | 2025 | 2026 | Source |
|---|---|---|---|
| Organizations scaling AI enterprise-wide | 38% | 44% | McKinsey State of AI 2026 |
| AI high performers (5%+ of EBIT from AI) | 6% | 6% | McKinsey State of AI 2026 |
| SPCR | 15.8% | 13.6% | Axis Intelligence Research calculation |
According to Axis Intelligence Research, the SPCR fell 2.2 points in a year: the scaling base grew 6 points while the high-performer share did not move. Both inputs come from the same survey and the same definitions, which is why they can be divided. The SPCR is a ratio of two population shares, so it reads as the payoff density of the scaling footprint, not as the probability that any single scaling company succeeds.
A second reading on the same inputs: respondents reporting any EBIT impact equal 84.1% of the scaling share in 2026. Some EBIT impact is common. Material EBIT impact is rare.
Sarah Mitchell’s read: Scaling is a deployment decision. Payoff is a redesign decision. McKinsey’s high performers report fundamentally redesigning workflows at nearly three-quarters, up from 55% in 2025, against about one-quarter for everyone else. The SPCR rises when organizations stop bolting models onto old processes. It will keep falling as long as scaling outruns redesign.
Where AI Costs Are Starting to Bite
About 20% of organizations say AI operating costs, including tokens, constrain their AI use, per McKinsey. Even so, 28% spend more than 10% of their ICT budget on AI, and 60% expect AI investment to rise next year. Coding agents are changing the software budget itself: 32% of organizations decided against buying at least one software product because coding agents could build it in-house. Model what this means for your own budget with the AI ROI calculator.
How Widely Are AI Agents Deployed?
Agent adoption is splitting by company size. Among organizations with more than $1 billion in revenue, 40% are scaling AI agents in at least one function, up from 27% in 2025, while smaller organizations held at 22%, per McKinsey. Chatbots remain the most scaled tool, at 47% of organizations.
Capability is close to the human bar on some tasks. On OSWorld, a benchmark of agents operating a computer, the best 2025 system scored 66.3% against a 72.35% human baseline, a 6.05-point gap, per the Stanford HAI AI Index 2026.
The failure risk is forecast, not hypothetical: Gartner expects over 40% of agentic AI projects to be canceled by the end of 2027, citing cost and unclear business value (Gartner, June 2025). Track new agent and model launches on our AI model release tracker.
What Value Does AI Create for Consumers?
US consumer surplus from generative AI reached an estimated $172 billion a year by early 2026, up from $112 billion, a 53.6% increase, per research by Brynjolfsson and coauthors reported in the AI Index 2026. Consumer surplus is the compensation users say they would need to give up all generative AI tools for a month.
The study counts 115 million US adult users. The average surplus is $125 per user per month, and the median rose from $3.40 to $11.40. Most of that value is captured by users rather than vendors, because most generative AI tools are free or close to it.
Frontier labs are capturing more each quarter. Epoch AI tracking, cited by Stanford, puts OpenAI’s annualized revenue at about $25 billion and Anthropic’s at about $19 billion in early 2026, directional figures that Stanford flags as varying in reliability. Their compute bills are large too: OpenAI spent $16.3 billion on compute in 2025 and Anthropic $6.8 billion.
Is AI Raising Productivity?
At the task level, yes. Customer support agents with an AI assistant resolved 14% to 15% more issues per hour, developers using GitHub Copilot completed 26% more pull requests, and marketing teams using multimodal AI raised output per worker by 50%, according to studies compiled in the AI Index 2026.
The counter-evidence is specific. METR found experienced open-source developers became 19% slower with AI assistance in its 2025 trial, though METR could not replicate that result in a later study. At the economy level, US labor productivity grew 2.7% in 2025 against a 1.4% average over the prior decade, which Erik Brynjolfsson frames as an early J-curve rather than proof of AI causation. Across 12,000 European firms, AI adoption raised labor productivity by 4%.
Is AI Taking Jobs in 2026?
The damage is concentrated, not broad. Employment for US software developers aged 22 to 25 fell close to 20% from its 2022 peak by September 2025, while older developers’ headcount grew, per Brynjolfsson and coauthors in the AI Index 2026. Early-career workers in the most AI-exposed jobs saw headcount fall about 16% relative to the least-exposed.
Company expectations keep running ahead of reality. In McKinsey’s 2025 survey, 32% of respondents expected AI-driven workforce declines over the following year; in 2026, only 14% reported an actual AI-driven decline. Yet 39% now expect declines next year, while 43% expect little or no change, and just 13% say AI makes them anxious about their own career.
Demand for AI skills is still rising: AI postings were 2.6% of all US job postings in 2025, against 4.69% in Singapore. The World Economic Forum’s January 2025 forecast of 170 million jobs created and 92 million displaced by 2030, a net 78 million, remains the most cited long-range estimate (WEF); its next edition is the review trigger for this section. Layoffs that companies attribute to AI are logged on our AI layoff tracker.
How Much Electricity Does AI Use?
Data centre electricity demand rose 17% in 2025, against 3% growth in global electricity demand, and AI-focused data centres grew faster still, per the International Energy Agency (IEA) on April 16, 2026. The IEA projects data centre electricity demand to double by 2030 and AI-focused data centre power use to triple.
The IEA also counts more than $400 billion of 2025 capex at five large technology companies, expected to rise a further 75% in 2026. Grid-level detail by country and utility is on our data center electricity demand tracker, and the sites themselves on the AI data center tracker.
Is the US Ahead of China in AI?
On models and money, yes; on deployment hardware, no. The top US model held an Arena score of 1,503 against 1,464 for the top Chinese model in 2026, a 39-point gap, per the AI Index. US private AI investment was 23.1 times China’s in 2025.
China leads on physical infrastructure. China has 85 public or public-private AI supercomputers, more than any region, and installed 295,000 industrial robots in 2024, or 54.4% of the world total. Live model rankings are on our LLM leaderboard.
What Do People Think About AI?
Public opinion is moving the opposite way from usage. In the US, 63% of adults say AI is advancing too quickly and 67% have little or no confidence in the government to regulate it, per Pew Research Center. Globally, trust in government regulation of AI ranges from 91% in Singapore to 31% in the United States, per the AI Index. Reported AI incidents hit a record 362 in 2025. Rules by jurisdiction are logged on our AI regulation tracker.
What Do the 2027 AI Forecasts Say?
Gartner forecasts worldwide AI spending of $3.64 trillion in 2027, 36.2% above 2026, and has raised that 2027 figure by $300.6 billion since January. Meta says it is still developing its 2027 capacity plans. McKinsey respondents lean toward more spending and fewer people: 60% expect higher AI investment and 39% expect AI-driven headcount declines.
According to Axis Intelligence Research, 2027 statistics today are forecasts, not measurements. The first measured 2026 full-year figures arrive with the Stanford AI Index 2027 and McKinsey’s next survey, so this page keeps 2026 as the reporting year and treats 2027 as an outlook until then.
Methodology
Collection. Every figure on this page was fetched from its producer during an October 27, 2026 research session: Stanford HAI (AI Index 2026 and its Chapter 4 PDF), McKinsey (State of AI 2026), Gartner (January, May and September 2026 forecast releases, captured as page PDFs on October 27, 2026), the U.S. Census Bureau (BTOS data files and narrative release), Pew Research Center (report PDF), Eurostat, the IEA, the World Economic Forum, and SEC filings from NVIDIA, Alphabet and Meta. Company user and revenue figures are labeled company-reported; Gartner, Microsoft telemetry, Epoch AI and consumer surplus figures are labeled estimates.
Axis calculations. The SPCR divides McKinsey’s high-performer share by its enterprise-scaling share, both from the same survey and definitions. Gartner revisions subtract the January 2026 edition from the September 2026 edition for the same forecast year. Growth rates, run-rates and shares are simple arithmetic shown beside each figure and in the CSV method_note column.
Scope. The SPCR inherits McKinsey’s self-reported, GDP-weighted survey design and its rounding of the high-performer share (“about 6%”). The US adoption ladder compares different populations on purpose and is never merged into one number. Census business figures come from the BTOS National and Sector data files for cycle 202621 (collected October 5 to 18, 2026); firm-size rates are from the Census narrative release dated May 26, 2026, because the size breakdown was not in the files reviewed.
Corrections from the July 2026 version. Retired figures are kept in the CSV as data_type = retracted rows with the reason for each.
About This Dataset
ai-statistics-2026.csv holds 342 rows covering AI spending forecasts (2025 to 2027), private and corporate AI investment (2024 to 2025), company capex and chip revenue (2025 to 2026), enterprise adoption and payoff (2025 to 2026), US and global usage, productivity, labor, energy, capability and public opinion, country-level map series, the 2026 Census BTOS biweekly series, plus 10 retracted rows. Each row carries value, unit, as-of date, source organization, document, URL, retrieval date, primary-source flag, Axis-calculation flag and method note. It is updated when a source publishes new data, not on a calendar. License: CC BY 4.0. Cite as: Axis Intelligence Research, AI Statistics 2026, axis-intelligence.com/ai-statistics/.
Cite This Research
APA: Axis Intelligence Research, & Mitchell, S. (2026, October 27). AI statistics 2026: Spending hits $2.67 trillion, payoff stays flat, and what the 2027 forecasts say. Axis Intelligence. https://axis-intelligence.com/ai-statistics/
MLA: Axis Intelligence Research, and Sarah Mitchell. “AI Statistics 2026: Spending Hits $2.67 Trillion, Payoff Stays Flat, and What the 2027 Forecasts Say.” Axis Intelligence, 27 Oct. 2026, axis-intelligence.com/ai-statistics/.
Chicago: Axis Intelligence Research, and Sarah Mitchell. “AI Statistics 2026: Spending Hits $2.67 Trillion, Payoff Stays Flat, and What the 2027 Forecasts Say.” Axis Intelligence, October 27, 2026. https://axis-intelligence.com/ai-statistics/.
Frequently Asked Questions
Is AI spending paying off for companies in 2026?
Mostly not at the enterprise level. McKinsey’s 2026 survey found 37% of organizations attribute any EBIT impact to AI and about 6% attribute 5% or more of EBIT to it, both flat from 2025. According to Axis Intelligence Research, the SPCR fell from 15.8% to 13.6%, meaning payoff is not keeping pace with scaling.
How many people use ChatGPT every week?
OpenAI reported more than 900 million weekly ChatGPT users on February 27, 2026, along with more than 50 million consumer subscribers. In the US, Pew found 44% of adults use ChatGPT as of February 2026.
What percentage of US businesses use AI?
24.6% of US employer businesses used AI in some business function in the two weeks before the survey, per the Census Bureau’s BTOS cycle collected October 5 to 18, 2026, up from 17.7% in January. The rate is highest in the information sector, at 46.4%.
Why do some reports say 88% of companies use AI and others say about a quarter?
The 88% figure comes from McKinsey’s survey of mostly larger organizations reporting use in at least one function. The 24.6% figure is the Census Bureau’s count of all US employer businesses, most of which are small. Both are correct for their own populations.
How big will AI spending be in 2027?
Gartner forecasts $3.64 trillion in worldwide AI spending in 2027, 36.2% above its $2.67 trillion forecast for 2026. Gartner has already raised the 2027 figure by $300.6 billion since January 2026.
Is AI replacing entry-level jobs?
The clearest evidence points that way in AI-exposed occupations. US software developers aged 22 to 25 saw employment fall close to 20% from the 2022 peak by September 2025, per research cited in the Stanford AI Index 2026, while older developers’ headcount grew.
How fast is AI electricity demand growing?
Data centre electricity demand grew 17% in 2025, 5.7 times the 3% growth in total global demand, per the IEA. The IEA projects data centre demand to double and AI-focused data centre demand to triple by 2030.
How much do Big Tech companies spend on AI data centers?
Alphabet spent $44.9 billion on property and equipment in Q2 2026, double the prior year, and Meta spent $34.9 billion in Q3 2026 with a 2026 outlook of $135 billion to $145 billion, per their SEC filings. The IEA counts more than $400 billion of 2025 capex at five large technology companies.
Correction, October 27, 2026: an earlier version of this page described the 53% generative AI adoption figure as global; it measures US adults aged 18 to 64. It stated generative AI private investment grew 404% in 2025; Stanford reports growth of over 200%. It stated 72% of organizations used generative AI, up from 33% in 2024; the AI Index reports 79% in 2025, up from 71%. It cited a $122 billion OpenAI round; OpenAI announced $110 billion. The AIADI index has been retired because its 0.88 dampening factor was not reproducible, and several unsourced comparisons were removed. Retired figures remain in the dataset as retracted rows.