Artificial Intelligence and Poverty Reduction in Africa: Assessing the Pathways to Inclusive Economic Growth

By James Mane

2026 Africa African Development Review

Abstract

Artificial intelligence (AI) is widely expected to help African countries reduce poverty and grow more inclusively, but the evidence for this is uneven. This paper reviews six pathways from AI to poverty reduction in sub-Saharan Africa (agriculture, health, financial inclusion, education, public services, and jobs and enterprise) and assesses the African evidence for each. It sets out a framework with four channels (productivity of the poor, access to services, employment, and public resources) and tests each pathway against whether it reaches people below the poverty line, lowers costs, shows measured outcomes and shares value locally. The review finds that the strongest evidence lies in education (a randomised trial of an AI maths tutor in Ghana found a gain of 0.36 standard deviations at about US$5 per student) and in clinical decision support in Kenya (diagnostic errors down 16% across nearly 40,000 visits). Evidence is weaker for agriculture, AI-enabled credit and public services, and the quality of entry-level AI jobs is a concern. No pathway yet has proof of lasting income gains for poor households. The binding constraints are connectivity (about 900 million Africans offline), energy and compute (0.6% of global data centre capacity), language coverage (88% of African languages poorly served by language technology) and weak governance capacity. The paper closes with recommendations for governments, firms, development partners and researchers: set poverty targets in AI strategies, treat connectivity and compute as AI policy, build African-language data, protect workers and users, and fund outcome evaluations.

Keywords

artificial intelligence; poverty reduction; inclusive growth; Africa; digital inclusion; AI governance

References

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