Mapping the Artificial Intelligence Divide in Africa: Infrastructure, Accessibility and Capacity

• URL: http://arxiv.org/abs/2606.30656v1
• Date: Tue, 16 Jun 2026 08:50:24 GMT
• Title: Mapping the Artificial Intelligence Divide in Africa: Infrastructure, Accessibility and Capacity
• Abstract summary: Africa is facing a fragmented and challenging "AI divide"<n>Physical infrastructure needed to build an AI economy on the continent is lagging.<n>There are positive trends towards the emergence of local initiatives and grassroots movements.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Artificial Intelligence (AI) has the potential to be transformative for development, but Africa is currently facing a fragmented and challenging "AI divide". This paper provides an empirical analysis of the current state of the AI landscape and how it compares with Africa's technological preparedness for the future. In our analysis, we approach the "AI Divide" from three angles: infrastructure, accessibility, and human capacity. First, we look at the physical constraints that prevent Africa from integrating digitally. We then evaluate the human-centred factors that limit the development of AI technology on the continent. Finally, we examine the human capacity to develop AI systems on the continent and provide three focused case studies. Our investigation shows that the physical infrastructure needed to build an AI economy on the continent is lagging, with only 38% internet penetration, poor broadband coverage and less than 1% of all data centres globally. Other constraints include high data costs relative to income, gender-based digital divides, and the need to build more representative NLP models that can understand Africa's native languages. However, there are positive trends towards the emergence of local initiatives and grassroots movements, such as startups and universities, contributing to AI development on the continent. Based on these findings, we provide concrete recommendations to policymakers to help develop a more comprehensive and equitable AI ecosystem on the African continent.

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