The book is a single-volume resource on what it will take for Africa to shape - rather than merely absorb - the AI transformation reordering the global economy. Written for policymakers, researchers, and practitioners, it moves beyond both the boosterism of consultancy projections and the fatalism of pure critique, offering an evidence-based account of the capabilities the continent must build, layer by layer, to turn AI's promise into inclusive development. Its principal analytical contribution is the Africa AI Stack, a layered-systems framework of six horizontal layers - Energy, Infrastructure, Data, Model, Orchestration, and Application - three vertical enablers of Talent, Governance, and Continental Integration, and a transverse Ethics and Standards dimension grounded in a rights-based, Ubuntu-informed normative account. Each stratum is a necessary condition for those above it, so that a deficit at any layer propagates upward and constrains the value obtainable from investment higher in the stack. Applied consistently across twenty-three chapters, it yields a proposition that recurs throughout the sectoral analysis: pilot failures are typically attributable not to model inadequacy but to unmet conditions at the Data, Orchestration, or Infrastructure layers, or to weaknesses in the enablers. Treating ethics as infrastructure rather than as an external constraint is itself a theoretical commitment of the volume. Empirically, the book assembles documented African deployments across ten application sectors - agriculture, health, education, finance, trade, climate, public services, cities, security, and culture - analyzed comparatively against India, Brazil, China, Southeast Asia, the Gulf states, and the Caribbean, whose constraints offer more instructive analogies than those of the frontier AI economies. Cases including chest-X-ray screening in South Africa, agentic customs administration in Ghana, solar forecasting in Morocco, and AI property valuation in Rwanda are interrogated for what they reveal about the underlying system rather than presented as illustration alone.

Agentic AI is treated throughout, addressing both its capability implications for institutionally thin, high-caseload public systems and the accountability problems it introduces. The concluding analysis develops a scenario framework for the 2026-2040 horizon and makes the case for pooled continental action as the mechanism through which African AI sovereignty is most plausibly realized.