Artificial intelligence is the next general purpose technology and the fastest growing technology in human history.
In less than three years, more than 1.2 billion people around the world are using AI tools, faster than the internet, computers, or smartphones.
According to the Microsoft AI Adoption Report, a select group of African countries are emerging as continental leaders in the use of AI, even though most countries in the Global South continue to lag behind developed countries. These countries are currently shaping Africa’s place on the global AI adoption curve.
Three forces for the spread of AI
To understand this uneven adoption, it helps to consider three forces driving AI adoption. Frontier builders pushing the boundaries of what is technically possible. Infrastructure builders that provide essential computing power, energy, and connectivity. Users apply these technologies to address real-world challenges.
Measuring AI adoption in Africa
Against this backdrop, the table below ranks the top 10 African countries by AI user share, defined as the percentage of working-age adults using AI tools in 2025. Notably, only one country in Africa exceeds the global average of 15%, with other countries still falling below this benchmark.
Unequal adoption across Africa
Despite these leaders, some of Africa’s largest economies have been slow to adopt AI. Nigeria, Guinea, Liberia, Ghana, and Burkina Faso reported a share of AI users of approximately 8.71%.
On the other hand, unexpected cases include Lesotho at 8.77%, Madagascar at 8.91%, Kenya at 7.83%, and Tanzania at 6.37%.
These numbers highlight the uneven pace of adoption and show that the adoption of AI depends not only on country size and GDP, but also on infrastructure, connectivity, and digital readiness.
Key drivers and barriers
The disparity in adoption is closely tied to underlying systems such as power, internet connectivity, and computing infrastructure.
Nearly 4 billion people around the world still lack the basic requirements needed to use AI tools. GDP per capita also influences adoption patterns, with countries with income above $20,000 per capita generally having higher adoption rates.
Languages add further complexity because languages with fewer resources limit accessibility even when infrastructure exists.
Infrastructure and connectivity challenges
Infrastructure constraints in Africa remain severe. While some countries have electricity almost universally, 18 of the 20 countries with the highest deficits are in sub-Saharan Africa, and around 85% of the world’s population currently lacks electricity. This gap in basic infrastructure directly impacts the continent’s ability to deploy and use AI technologies.
Similarly, data centers are highly concentrated in the US and China, which together host 86 percent of the world’s capacity.
Overall, Africa accounts for less than 1% of the world’s data center capacity, resulting in increased latency, reduced performance, and increased costs for users.
Internet access further illustrates the importance of infrastructure. For example, Zambia’s national AI adoption rate is 12 percent, but usage rises to 34 percent among citizens with internet access.
However, connectivity alone is not enough. Digital literacy and AI fluency are equally important for individuals to use AI productively in work, education, and entrepreneurship.
Global benchmarks and lessons learned
Only seven countries consistently lead the way on the AI model development front: the United States, China, France, South Korea, the United Kingdom, Canada, and Israel.
Countries such as Singapore and the UAE have demonstrated that strong policy coordination, infrastructure, and education can drive high adoption, even without hosting state-of-the-art AI labs.
Africa’s AI challenges
Taken together, Africa’s rankings show that each continent is disproportionately entering the AI era. Countries with higher incomes, greater electricity coverage, greater internet access and better digital skills record higher adoption rates.
The challenge is to scale up the infrastructure, connectivity, digital skills and language support so that Africa can fully participate in the AI economy, rather than remain on its periphery.
