AI inclusivity and the centrality of Africa: a systematic review of representation, innovation, and governance in global artificial intelligence
Abstract
Artificial Intelligence (AI) is reshaping global systems across education, healthcare, finance, and agriculture. Despite its transformative potential, concerns about inclusivity persist, particularly regarding the underrepresentation of African contexts in AI development. This study examines Africa's role in achieving globally inclusive AI and explores the implications of its marginalization. A qualitative systematic review design was adopted, guided by PRISMA protocols, synthesizing peer-reviewed literature, policy documents, and grey sources published between 2018 and 2025. The analysis was structured around a conceptual framework linking data diversity, development processes, and AI outcomes. Findings reveal that limited African representation in datasets, governance institutions, and innovation ecosystems contributes to algorithmic bias, reduced contextual relevance, and reinforcement of global digital inequalities. Conversely, African contributions, including context-sensitive innovation, sector-specific AI innovation, and ethical frameworks grounded in communal philosophies such as Ubuntu, demonstrate the continent's centrality to equitable AI systems. Structural barriers such as infrastructure gaps, funding constraints, and unequal global partnerships continue to limit participation. The study concludes that AI inclusivity is unattainable without meaningful African engagement in data production, model development, and governance structures. Policy recommendations…
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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