The study proposes a phased, ethically grounded governance framework tailored to Africa’s educational context, contributing new insights into readiness differentials, governance diffusion, and policy convergence, offering a foundation for inclusive, future-oriented AI policy in African higher education.
Abstract
As artificial intelligence (AI) reshapes global education systems, African higher education institutions (HEIs) face pressure to adopt and govern AI ethically and effectively. This study investigates five questions: (1) What is the status of AI governance in African HEIs? (2) How ready are institutions to adopt AI policy? (3) What ethical and operational risks are emerging? (4) How do institutional and national AI strategies align? and (5) What future-proof governance framework can be proposed? Using a desk-based meta-synthesis, the study analyzes over 30 publicly available institutional, national, and regional documents. The analysis is guided by Resource Dependence Theory, Diffusion of Innovation, and Complexity Theory. No human subjects were involved, and international ethical standards were followed; PRISMA guidelines were deemed not applicable due to the qualitative scope. Findings reveal wide disparities in policy development and readiness. South Africa, Nigeria, and Rwanda are early adopters, aligning institutional policies with national digital strategies (RQ1 & RQ4). Most institutions remain in aspirational phases, limited by infrastructure and human capacity (RQ2). Where policies exist, they emphasize academic integrity and responsible use, though enforcement is uneven and impact largely unevaluated (RQ3). Cross-national alignment varies, with regional frameworks lacking strong enforcement mechanisms (RQ4). Evidence suggests that institutions with structured policies invest more in training and faculty engagement (RQ2 & RQ5). The study proposes a phased, ethically grounded governance framework tailored to Africa’s educational context (RQ5). It contributes new insights into readiness differentials, governance diffusion, and policy convergence, offering a foundation for inclusive, future-oriented AI policy in African higher education.
A six-element governance framework is developed comprising legitimate purpose and proportionality; explicit allocation of roles and responsibility; traceable data, evidence, and uncertainty; competent human oversight and calibrated reliance; stakeholder participation, contestability, and redress; and continuous monitor...
As artificial intelligence (AI) becomes increasingly embedded in higher education, empirical evidence on how institutional governance shapes its equitable and responsible implementation in South African universities remains limited. This study examined how institutional policies and governance practices influence the i...
R. Lumadi· International Journal of Stu...· 0 citations
It is suggested that sustainable AI adoption requires institutions to first establish robust governance structures, ensure data readiness and embed ethical safeguards before expanding technological investments, with particular relevance for resource-constrained higher education contexts in Malaysia and the broader Glob...
Nurul Aisyah Kamrozzaman, N. Muhiddin, Washima Che Dan et al.· International Research Journ...· 0 citations
The study concluded that effective governance requires combining research evidence, sectoral frameworks, and institutional policies, while translating general principles into clear procedures at the university and course levels, and revealed the need for more specialized policies that address privacy, linguistic equity...
Mohammed Al Mutawtah· Academic Journal of Research...· 0 citations
The framework demonstrates that the sustainable value derived from AI in higher education depends less on the level of the technology adopted than on the ethical bases and consistency of the leadership responsibility for its integration, offering higher education leaders and policymakers a structured path toward respon...
Asem S. Obied, Ahmed Raja Haj Ali· Frontiers in Education· 0 citations
A maqāṣid-based governance framework that translates core ethical objectives into measurable, sustainability-oriented indicators embedded within lifecycle decision points is developed, structured as a prototype institutional scorecard enabling university administrators and policymakers to evaluate AI adoption within ri...
F. Atallah· Frontiers in Education· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.