According to the latest Microsoft Global AI Diffusion Report, worldwide adoption of artificial intelligence increased in the first quarter of 2026. The report determined that AI usage increased by 1.5 percentage points from 16.3% to 17.8% of the global working age population. Twenty-six world economies are the above 30% AI Diffusion of the working age population using AI.
According to the report, one hundred and forty-seven economies with the working-age population using generative AI increased since June 2025. The top ten leading countries using AI include:
Top Ten Countries Using AI, Q1 2026
- United Arab Emirates 70.1%
- Singapore 63.4%
- Norway 48.6%
- Ireland 48.4%
- France 47.8%
- Spain 44.2%
- New Zealand 43.0%
- United Kingdom 42.2%
- Netherlands 42.1%
- Qatar 41.8%
South Korea was determined to have the largest quarterly gain with +6.4 percentage points. Overall AI adoption growth was fastest for the following countries in percentage points:
- South Korea 6.4pp
- United Arab Emirates 6.1pp
- Ireland 3.8pp
- France 3.8pp
- Qatar 3.5pp
- Taiwan 3.4pp
- Japan 3.4pp
- United Kingdom 3.3pp
- Netherlands 3.2pp
- Saudi Arabia 3.2pp
Twelve of the fifteen fastest-growing mostly Asian economies since June 2025 added at least 25% more AI users.
- South Korea 43.2%
- Thailand 36.4%
- Japan 34.1%
- Mongolia 32.3%
- Iran 31.4%
- Laos 31.2%
- Turkey 30.3%
- Belarus 27.6%
- El Salvador 25.7%
- Kazakhstan 25.6%
Software Development has been significantly influenced by AI. GitHub pull request activity tied to AI coding has increased more than 28×:
The acceleration coincides with major model advances: Anthropic’s Claude Opus and OpenAI’s GPT-5 Codex family advanced the state of the art in real-world software engineering, while GitHub Copilot evolved into a broader AI coding platform with multi-model support and autonomous coding agents. Copilot, and other AI coding tools like Claude Code and Codex, are now active participants in the software development lifecycle.
More details on the methodology are available in the AI Diffusion technical paper.[1]
[1] A. Misra, J. Wang, S. McCullers, K. White, and J., L. Ferres, “Measuring AI Diffusion: A Population Normalized Metric for Tracking Global AI Usage,” Nov. 04, 2025, arXiv: arXiv:2511.02781. doi: 10.48550/arXiv.2511.02781.