Building Economic Intelligence Infrastructure for AI-Driven Decision-Making in Africa

Artificial intelligence is increasingly presented as a development accelerator for Africa, yet much of the policy debate focuses on visible applications such as chatbots, predictive models, automated services, and generative interfaces rather than on the information systems that determine what those applications can reliably know. This paper argues that Africa's central AI challenge is not merely access to advanced models, but the representativeness, accessibility, interoperability, and governance of the economic information ecosystems on which AI depends. The paper develops the concept of the Digital Representation Gap: the distance between actual economic reality and the reality contained in accessible, usable, and contextually meaningful digital information. It then proposes the African Economic Intelligence Infrastructure (AEII), a six-layer institutional architecture connecting economic reality, representation, digital infrastructure, analytics, accountable decisions, and development outcomes. Complementary tools include the THEVTIG Data Visibility Matrix, an Economic Data-to-Intelligence Maturity Model, and a Responsible Economic Intelligence Test. Comparative illustrations from Kenya, Nigeria, Rwanda, and Côte d'Ivoire/UEMOA demonstrate that African countries face distinct combinations of traceability, fragmentation, representativeness, and institutional coordination. The paper identifies five high-impact applications, trade and supply chains, investment, fiscal intelligence, food and commodities, and macroeconomic early warning, and presents a sequenced roadmap for implementation. The central conclusion is that AI should be embedded within broader economic intelligence institutions. Africa's long-term advantage will depend not only on deploying larger models, but on strengthening its capacity to observe itself, document its knowledge, govern its data, develop analytical sovereignty, and convert intelligence into accountable action.