Artificial intelligence is the next general-purpose technology and the fastest-spreading technology in human history.
In less than three years, more than 1.2 billion people worldwide have used AI tools, a rate faster than the internet, the personal computer, or the smartphone.
According to the Microsoft AI Diffusion Report, although most countries in the Global South continue to trail advanced economies, a select group of African nations has emerged as continental leaders in AI usage. These countries now shape Africa’s positioning in the global AI adoption curve.
The Three Forces of AI Diffusion
To understand this uneven adoption, it is helpful to consider the three forces driving AI diffusion: Frontier builders, who push the boundaries of what is technologically possible; Infrastructure builders, who provide essential computing power, energy, and connectivity; and Users, who apply these technologies to address real-world challenges.
Measuring Africa’s AI Adoption
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. The global average is 15 percent, placing several African countries above the world benchmark, while many others remain below it.
Uneven Adoption Across Africa
Despite these leaders, several large African economies are adopting AI more slowly. Nigeria, Guinea, Liberia, Ghana, and Burkina Faso report an AI user share of around 8.71 percent.
Meanwhile, some unexpected cases include Lesotho at 8.77 percent, Madagascar at 8.91 percent, Kenya at 7.83 percent, and Tanzania at 6.37 percent.
These figures highlight the uneven pace of adoption and demonstrate that AI uptake is shaped not only by country size or GDP, but also by infrastructure, connectivity, and digital readiness.
Key Drivers and Barriers
The disparities in adoption are closely linked to foundational systems: electricity, internet connectivity, and computing infrastructure.
Nearly four billion people globally still lack the basic requirements needed to use AI tools. GDP per capita also influences adoption patterns, with countries above $20,000 per capita generally seeing higher uptake.
Language adds another layer of complexity, as low-resource languages limit accessibility even where infrastructure exists.
Infrastructure and Connectivity Challenges
Africa’s infrastructure constraints remain significant. While some countries have near-universal electricity, 18 of the 20 nations with the largest deficits are in Sub-Saharan Africa, which now accounts for about 85 percent of the global population without electricity. This gap in basic infrastructure directly affects the continent’s ability to adopt and use AI technologies.
Similarly, data centres are heavily concentrated in the United States and China, which together host 86 percent of global capacity.
Overall, Africa accounts for less than 1 percent of global data centre capacity, resulting in higher 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 among citizens with internet access, usage rises to 34 percent.
However, connectivity alone is insufficient; digital literacy and AI fluency are equally critical for individuals to use AI productively in work, education, and entrepreneurship.
Global Benchmarks and Lessons
At the frontier of AI model development, only seven countries consistently lead: the United States, China, France, South Korea, the United Kingdom, Canada, and Israel.
Countries such as Singapore and the UAE demonstrate that strong policy coordination, infrastructure, and education can drive high adoption even without hosting frontier AI labs.
Africa’s AI Challenge
Taken together, the African rankings show a continent entering the AI era unevenly. Countries with stronger incomes, broader electricity coverage, wider internet access, and higher digital skills record higher adoption rates.
The challenge is to expand infrastructure, connectivity, digital skills, and language support to ensure Africa participates fully in the AI economy, rather than remaining on its periphery.
