Key takeaways
- 17.8% of the world's working-age population used generative AI in Q1 2026; 26 economies are above 30%.
- The UAE leads at 70.1%, followed by Singapore (63.4%); the UK is 8th (42.2%), Australia 11th (39.5%), Israel 13th (38.1%) and the US 21st (31.3%).
- Twelve of the fifteen fastest-growing economies are in Asia, led by South Korea (+43%), Thailand and Japan; Vietnam grew about 25% to 26.5%.
- Git pushes rose 78% year on year to 380 million in Q1 2026, and merged pull requests linked to AI coding agents grew more than 28-fold since June 2025.
Microsoft's AI Economy Institute publishes a quarterly measure of AI diffusion: the share of people aged 15 to 64 who used a generative AI product during the period, derived from aggregated, anonymised telemetry and adjusted for device market share, internet access and population. The Q1 2026 edition, published in May, shows adoption still rising — and spreading unevenly.
The global picture
AI use rose from 16.3% to 17.8% of the world's working-age population in a single quarter. Intensity is rising among leaders: 26 economies now exceed 30%.
The divide between richer and poorer economies is widening. In the Global North, usage reached 27.5% (up 2.8 points); in the Global South, 15.4% (up 1.3 points). Access to electricity, internet connectivity and digital skills explain most of the difference.
The leaderboard
The United States moved up only from 24th to 21st. Several smaller, highly connected economies — the Gulf states, Singapore, the Nordics, Ireland — continue to lead.
A growth wave in Asia
Twelve of the fifteen fastest-growing economies since June 2025 are in Asia, each with at least 25% more AI users than a year earlier. South Korea grew 43%, Thailand 36% and Japan 34%; Mongolia, Laos and Turkey all grew more than 30%. Vietnam, Kazakhstan, Uzbekistan and Cambodia are also in the group — Vietnam rose about 25%, to 26.5% of its working-age population.
Microsoft attributes much of this to better performance in local languages. On multilingual benchmarks, the gap between English and other languages has narrowed sharply; Japanese accuracy on a standard knowledge benchmark rose from about 50% to around 80% between model generations, and a recent model scored higher in Japanese than in English on a harder version of the test. Japan moved from 56th to 48th place in the ranking.
How software is now built
The report's most striking data concerns code. Git pushes — the moment developers publish code changes — reached 380 million in Q1 2026, up 78% from 213 million a year earlier. New repositories rose 45% to 21.3 million. In Japan, code uploads grew 129%.
Merged pull requests associated with AI coding agents have grown more than 28-fold since June 2025. Microsoft links the step change to coding models and tools released in late 2025 and early 2026, and to the shift of tools like GitHub Copilot from code suggestions to agents that complete tasks and open pull requests.
The labour-market data, so far, does not show the feared collapse. US software developer employment reached about 2.2 million in 2025, a record and 8.5% higher than a year earlier, and was about 4% higher again in March 2026. The report's explanation: cheaper software production can increase demand for software, if that demand is elastic — while cautioning that it is too early to judge the long-term effect.
Reading the data
A few points help interpret the rankings:
- Usage is not deployment. The metric counts people who used a generative AI product, not organisations that changed processes. Surveys such as Stanford's AI Index find agent deployment in business functions still in single digits.
- Language matters. Improvements in non-English performance translate quickly into adoption, which is why several Asian economies are accelerating now.
- Talent markets follow adoption. Economies where AI use is high and rising — including the UAE, Singapore, the UK, Australia, Israel and Vietnam — are also where demand for engineers who can build and run AI systems grows fastest.
Sources
- Microsoft AI Economy Institute, Global AI Diffusion: Q1 2026 Trends and Insights, May 2026 (with GitHub data on git pushes, repositories and pull requests).
- Stanford Institute for Human-Centered AI, AI Index Report 2026.