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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月3日

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  • Ayubu Ismail Ngao,
  • Anna Benson Boreka,
  • Michael A. Peters

摘要

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.