UAE leads global generative AI adoption as gap between regions widens

Monday 28 - 19:00

By: Azzat Manal

UAE leads global generative AI adoption as gap between regions widens

Generative artificial intelligence continued to expand worldwide during the second quarter of 2026, although adoption remained highly uneven across countries and regions. New data from Microsoft's AI Economy Institute show that the United Arab Emirates maintained its position at the top of the global ranking, while the gap between the Global North and Global South widened.

According to Microsoft's latest Global AI Diffusion Report, 18.8% of the world's working-age population used generative AI tools in the second quarter, up from 17.8% during the first quarter. The increase of one percentage point indicates that AI applications are becoming increasingly integrated into everyday activities, from learning and content creation to workplace tasks and information gathering.

The United Arab Emirates recorded the highest adoption rate at 73.3%, followed by Singapore at 64.3%. Ireland ranked third with 49.9%, while France and Norway recorded 49.6% and 49.4%, respectively. Spain, New Zealand, the United Kingdom, the Netherlands and Qatar also remained among the economies with the highest levels of generative AI use.

The figures also show rapid growth in several Asian markets. South Korea reached 40.6%, rising to 12th place globally after recording the largest quarterly increase among major economies, at 3.5 percentage points. Saudi Arabia also made notable progress, climbing five positions from 30th to 25th in the global ranking.

Microsoft's indicator measures the share of people aged between 15 and 64 who used at least one generative AI product during the period studied. The company uses aggregated and anonymized telemetry data and adjusts the results to account for differences in internet penetration, operating-system and device market shares, and population size. Microsoft also cautions that no single indicator can fully capture the complexity of AI adoption around the world.

Despite the global increase, the distribution of AI use remains sharply unequal. In the second quarter, adoption reached 28.8% in the Global North, compared with 16.2% in the Global South. The resulting 12.6-percentage-point gap was wider than in the previous quarter, when the difference stood at 12.1 points.

Microsoft attributes part of this disparity to structural factors such as access to electricity, reliable internet connectivity, digital skills and support for local languages. These conditions can determine whether individuals, businesses and public institutions are able to make effective use of increasingly sophisticated AI systems.

The difference is not only visible in adoption rates but also in how people use AI. Microsoft's analysis suggests that learning and skills development represent a relatively larger share of AI use in the Global South, while users in the Global North show comparatively stronger use for activities such as shopping, search and feedback. Image, text and code generation and editing are also significant areas of use across regions.

The growing availability of open-weight AI models could also influence future adoption. Microsoft says improvements in the performance of these models, combined with lower costs and greater possibilities for customization, could make advanced AI more accessible to organizations and communities that face financial or infrastructure constraints.

The latest figures underline the importance of digital infrastructure and skills as AI becomes increasingly integrated into economies and societies. High adoption in countries such as the UAE demonstrates how quickly generative AI can spread where connectivity, digital capabilities and institutional readiness are strong, while the widening regional gap highlights the challenges facing countries seeking broader access to the technology.

As generative AI moves from an emerging technology toward a more common tool for work, education and everyday activities, differences in infrastructure, skills and affordability are likely to remain important factors shaping who benefits from the next phase of the AI economy.