A systematic scoping review of transformative potential and contextual challenges of integrating AI and collective intelligence in African higher education

The integration of artificial intelligence (AI) into African higher education is characterized by a critical tension between its transformative potential and profound contextual constraints. This systematic scoping review addresses this disjuncture by synthesizing available evidence from 41 sources (32 peer-reviewed articles, 9 policy documents) selected via a PRISMA-ScR-guided protocol and analyzed through thematic synthesis, with evidence strength differentiated as Tier 1 (empirical studies), Tier 2 (theoretical/policy), and Tier 3 (grey literature). The analysis reveals three key findings: (i) continental strategies and context-adapted tools demonstrate promise for enhancing access and collaborative research, though evidence of scalable impact remains largely confined to source-specific illustrations requiring replication; (ii) implementation is critically undermined by interconnected barriers including infrastructural deficits, data scarcity, and unaligned epistemologies; and (iii) without deliberate intervention, current AI adoption trajectories risk exacerbating inequities and perpetuating neocolonial dependencies. Based on the thematic synthesis, we propose the Integrated Digital Transformation Model (IDTM), a conceptual framework combining cloud infrastructure, adaptive AI, and collective intelligence across three interconnected layers, presented as a synthesis requiring empirical validation rather than a tested intervention. The study posits that sustainable transformation requires context-specific policies, investment in local infrastructure and talent, and AI systems grounded in African sociocultural paradigms.