🤖 AI Summary
Current AI governance frameworks disproportionately emphasize the geographic accessibility of computational power while neglecting the underlying dynamics of capital flows, ownership structures, and control mechanisms, thereby falling short of achieving genuine compute equity. This study systematically examines 46 AI infrastructure projects across Africa between 2019 and 2025, representing a total investment of $12.7 billion, integrating systematic literature review, publicly available data, and a value chain analysis framework. It reveals that 73% of funding is concentrated in capital and physical infrastructure, with compute control heavily centralized among a few global technology giants, and investments markedly clustered in South Africa, Kenya, Nigeria, and Egypt. Introducing the concept of “asymmetric interdependence,” this work advocates for incorporating capital, ownership, and control dimensions into compute governance to transcend the prevailing paradigm centered solely on technological access.
📝 Abstract
Artificial intelligence depends on large-scale compute resources and their supporting infrastructure. However, AI governance debates treat compute primarily as a technical input rather than as an outcome of investment, ownership, and financial control. This paper examines AI infrastructure investment flows across Africa through a systematic analysis of 46 publicly announced projects totalling USD $12.7 billion between 2019 and 2025. Using a value chain framework, we analyze who invests in AI-relevant infrastructure and where investments concentrate. Our findings reveal a highly concentrated landscape dominated by global data center operators, hyperscale technology firms, and development finance institutions, clustering in South Africa, Kenya, Nigeria, and Egypt. We introduce asymmetrical interdependence to describe a structural condition in which capital and physical infrastructure account for 73% of total funding while control remains concentrated in the compute layer among a small number of global technology firms. We argue that compute governance must account for capital flows, ownership, and control, not only geographic access, because these dynamics shape AI compute equity. Infrastructure presence is necessary but insufficient for meaningful governance capacity.