Effective AI deployment in Africa is shaped by conditions the technology itself cannot change: the power infrastructure it depends on, the economic systems it operates within, and the digital infrastructure it runs across. These three research strands investigate those conditions — building the contextual evidence base that makes AI research in Africa analytically complete.
Each strand is a dedicated research programme — not ancillary reading, but a systematic evidence base. Explore the full research pipeline for each pillar below.
Active study: Grid Readiness for AI Infrastructure in Africa →
AI is energy-intensive. Before it can scale in Africa, we need to understand the power infrastructure it runs on, the climate conditions it operates within, and the environmental cost of its expansion. This strand maps what’s available, what’s constrained, and where investment changes the equation.
AI deploys into economic systems with their own incentive structures, affordability constraints, and labour dynamics. This strand investigates what economic conditions make AI adoption viable, sustainable, and equitable across African markets — from fintech to sovereign AI strategy.
AI systems run on infrastructure. In Africa, that infrastructure — connectivity, data centres, digital identity, cloud access, and edge networks — is uneven and in many contexts a binding constraint on what AI can actually do. This strand maps the gaps and what closes them.