The United Arab Emirates had the highest measured population-level generative-AI adoption in Microsoft’s H2 2025 dataset, at 64.0%. Singapore ranked second at 60.9%, while the global AI User Share reached 16.3%. The United States ranked 24th at 28.3%—a result that does not contradict its leadership in AI investment, infrastructure, and frontier-model development.
This report measures activity during the second half of 2025 and was published by Microsoft on January 8, 2026. It is a ranking of estimated generative-AI usage, not a general score for AI readiness, business deployment, national innovation, or economic value.
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What this AI-adoption ranking measures
Microsoft’s AI User Share is the estimated share of a country’s working-age population that used a generative-AI product during the reporting period. The estimate is based on aggregated and anonymized Microsoft telemetry, adjusted for operating-system and device-market share, internet penetration, and population.
In practical terms, the figures indicate whether people used generative-AI products during H2 2025. They do not establish that users relied on AI daily, paid for a subscription, used it at work, achieved productivity gains, or continued using it after trying it.
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Accordingly, this is not a ranking of:
- Business or enterprise AI deployment
- AI investment or data-center capacity
- Frontier-model development
- AI research, patents, or developer numbers
- Government AI implementation
- AI safety, quality, or economic impact
See Microsoft’s Global AI Adoption in 2025 report and its H2 2025 technical report.
AI adoption by country: complete top-30 ranking
The table compares Microsoft’s H1 and H2 2025 estimates. “Change” is the percentage-point movement between the two periods.
| Rank | Country or economy | H1 2025 | H2 2025 | Change |
|---|---|---|---|---|
| 1 | United Arab Emirates | 59.4% | 64.0% | +4.6 pp |
| 2 | Singapore | 58.6% | 60.9% | +2.3 pp |
| 3 | Norway | 45.3% | 46.4% | +1.1 pp |
| 4 | Ireland | 41.7% | 44.6% | +2.9 pp |
| 5 | France | 40.9% | 44.0% | +3.1 pp |
| 6 | Spain | 39.7% | 41.8% | +2.1 pp |
| 7 | New Zealand | 37.6% | 40.5% | +2.9 pp |
| 8 | United Kingdom | 36.4% | 38.9% | +2.5 pp |
| 9 | Netherlands | 36.3% | 38.9% | +2.6 pp |
| 10 | Qatar | 35.7% | 38.3% | +2.6 pp |
| 11 | Australia | 34.5% | 36.9% | +2.4 pp |
| 12 | Israel | 33.9% | 36.1% | +2.2 pp |
| 13 | Belgium | 33.5% | 36.0% | +2.5 pp |
| 14 | Canada | 33.5% | 35.0% | +1.5 pp |
| 15 | Switzerland | 32.4% | 34.8% | +2.5 pp |
| 16 | Sweden | 31.2% | 33.3% | +2.2 pp |
| 17 | Austria | 29.1% | 31.4% | +2.2 pp |
| 18 | South Korea | 25.9% | 30.7% | +4.8 pp |
| 19 | Hungary | 27.9% | 29.8% | +1.9 pp |
| 20 | Denmark | 26.6% | 28.7% | +2.1 pp |
| 21 | Germany | 26.5% | 28.6% | +2.1 pp |
| 22 | Poland | 26.4% | 28.5% | +2.1 pp |
| 23 | Taiwan | 26.4% | 28.4% | +2.0 pp |
| 24 | United States | 26.3% | 28.3% | +2.1 pp |
| 25 | Czechia | 26.0% | 27.8% | +1.8 pp |
| 26 | Italy | 25.8% | 27.8% | +2.0 pp |
| 27 | Bulgaria | 25.4% | 27.3% | +1.9 pp |
| 28 | Finland | 25.6% | 27.3% | +1.7 pp |
| 29 | Jordan | 25.4% | 27.0% | +1.6 pp |
| 30 | Costa Rica | 25.1% | 26.5% | +1.4 pp |
The United Kingdom and Netherlands both display 38.9%. Because the published figures are rounded, they should be treated as tied at the displayed precision rather than assumed to have identical underlying values. Microsoft uses “economy” in its table and includes Taiwan; those labels are preserved here.
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United Arab Emirates: 64.0%
The UAE led the H2 ranking by a wide margin. Microsoft associates high adoption with early and sustained investment in digital infrastructure, AI skills, government adoption, national AI strategies, and broad accessibility. Those factors are plausible contributors, not proof that any single policy caused the result.
Singapore: 60.9%
Singapore’s second-place position is consistent with its highly developed digital infrastructure, coordinated policy environment, AI education, and national AI planning. The ranking shows widespread measured usage, but does not independently measure the depth or economic value of that use.
Norway, Ireland, and France
Norway ranked third at 46.4%, making it the highest-ranking European country. Ireland reached 44.6%, up 2.9 percentage points, while France ranked fifth at 44.0%, up 3.1 points. The leading group is dominated by digitally connected economies, but the presence of the UAE and Qatar shows that high measured adoption is not limited to Western Europe or English-speaking countries.
Fastest movers in H2 2025
South Korea recorded the largest increase among the top 30 economies: its AI User Share rose from 25.9% to 30.7%, a 4.8-point increase. Microsoft links this growth to government policy, improved Korean-language frontier models, and consumer-facing features designed for local users.
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The UAE was another major mover, rising from 59.4% to 64.0%. Subtracting the rounded endpoints produces a 4.6-point increase; Microsoft’s web table displays the change as approximately 4.5 points, reflecting rounding. France rose 3.1 points, while Ireland and New Zealand each rose 2.9 points.
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Major-country comparison
| Country or economy | H2 2025 AI User Share |
|---|---|
| United States | 28.3% |
| South Korea | 30.7% |
| Japan | 19.1% |
| Brazil | 17.1% |
| Mexico | 17.8% |
| South Africa | 21.1% |
| China | 16.3% |
| India | 15.7% |
Other selected figures were 26.2% for Saudi Arabia, 23.5% for Vietnam, 19.7% for Malaysia, 18.3% for the Philippines, 14.6% for Türkiye, 13.4% for Egypt, 12.7% for Indonesia, and 13.0% for Nepal. These are selected figures, not a complete ranking of every economy in Microsoft’s broader dataset.
Why the United States ranked 24th
The U.S. result illustrates the difference between AI adoption and AI capability. The United States led in frontier-model development, AI infrastructure, and private investment, but its estimated share of the working-age population using generative-AI products was 28.3% in H2 2025.
Those measurements answer different questions:
- Adoption: How widely do people use AI tools?
- Capability: Who builds models, infrastructure, companies, and research?
- Business deployment: How deeply have organizations integrated AI into workflows?
A smaller, highly connected country can therefore rank higher on population usage even while the United States remains more dominant in the technologies and companies behind the products.
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The Global North–South divide
Microsoft estimated H2 2025 AI User Share at 24.7% in the Global North and 14.1% in the Global South, a gap of 10.6 percentage points. The gap increased from 9.8 points in H1 2025. The Global North gained 1.8 points, compared with 1.0 point for the Global South.
These are absolute adoption levels, not a judgment about interest or potential. A country starting from a low base may grow quickly while still having a much smaller overall user share. Lower observed adoption can reflect internet access, device ownership, broadband quality, affordability, payment access, language support, service restrictions, or product availability.
The technical research behind the measure also reports substantial latent demand among internet-connected populations in lower-income economies. Low measured usage should not be interpreted as proof that people in those markets do not want AI tools.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How DeepSeek affected the 2025 diffusion picture
Microsoft identifies DeepSeek as an important 2025 development. Its free chatbot and open-source MIT-licensed model reduced some financial and access barriers, with particularly strong traction reported in China, Russia, Iran, Cuba, and parts of Africa. Microsoft estimated DeepSeek usage in Africa at roughly two to four times the level of other regions.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsThat estimate should be treated as Microsoft’s analysis rather than a universal market-share statistic. The available evidence does not prove that DeepSeek alone caused country-level adoption changes. Affordability, availability, local distribution, language support, and competing product releases can all affect diffusion.
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Methodology and limitations
The associated technical paper describes AI User Share as an estimate covering 147 economies. Microsoft uses anonymized telemetry and adjusts for device access, operating-system and device-market share, internet penetration, population, and mobile scaling.
Strengths
- Provides a consistent cross-country measure of actual product usage.
- Normalizes the comparison for population rather than counting raw users.
- Allows H1-to-H2 changes to be tracked.
- Captures diffusion beyond countries known mainly for AI laboratories or investment.
Limitations
- It is telemetry-based, not a conventional opinion survey.
- It does not show frequency, duration, purpose, or quality of use.
- It does not establish whether use was personal, educational, or employer-directed.
- It may reflect Microsoft’s platform reach and the availability of particular devices and services.
- Adjustments may not fully remove differences among iOS, Android, browsers, and regional ecosystems.
- Access restrictions, pricing, language support, and local product availability may affect results.
- Rounded figures can obscure small differences between countries.
Microsoft itself notes that no single metric is perfect and that cross-country measurement continues to be refined. The ranking is best read as a timely H2 2025 snapshot, not a permanent league table.
How this differs from Stanford’s AI Index
Stanford’s 2025 AI Index covers a much broader set of topics, including investment, research, model development, business use, jobs, and policy. Its finding that 78% of organizations reported using AI in 2024 is not equivalent to Microsoft’s estimate of the share of a country’s working-age population using generative-AI products in H2 2025.
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How to use this ranking responsibly
- Label the figures as Microsoft’s H2 2025 AI User Share estimates.
- State that the denominator is the working-age population, not all residents or households.
- Keep generative-AI usage separate from business adoption and AI readiness.
- Pair usage data with measures of infrastructure, investment, research, skills, and business deployment.
- Check country-specific access, language, pricing, and regulatory conditions before drawing commercial conclusions.
- Do not treat a high user share as evidence of safe, productive, or economically valuable use.
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