Jul 2026· AI in Education· Vol 2, pp. 24· 0 citations· 151 references
TL;DR
The study investigates how AI integration offers opportunities for personalized learning, streamlined administration, and enhanced educational quality, while simultaneously exposing risks related to algorithmic bias, digital divides, and the erosion of student agency.
Abstract
Artificial intelligence (AI) is reshaping higher education worldwide, raising tensions between efficiency, equity, and autonomy. This paper examines these dynamics in South Africa and Kenya, two countries that illustrate distinct governance frameworks and infrastructural challenges within African higher education. Using qualitative document analysis of policy frameworks, scholarly literature, and institutional reports, the study investigates how AI integration offers opportunities for personalized learning, streamlined administration, and enhanced educational quality, while simultaneously exposing risks related to algorithmic bias, digital divides, and the erosion of student agency. The findings show that AI can improve efficiency and enrich student experiences, but without ethical safeguards it may reinforce existing inequalities and diminish learner autonomy. Through situating the analysis in South Africa and Kenya, the paper contributes to debates on AI in education by demonstrating that efficiency gains must be balanced with equity and autonomy considerations. The study concludes with recommendations for educators and policymakers on responsible AI adoption, emphasizing ethical literacy, inclusive infrastructure, and participatory approaches to ensure that technological innovation enhances rather than undermines social justice in higher education.
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 implementation and equitable use of AI in undergraduate education while contributing to international discourse on responsible AI governance. Guided by an interpretivist research paradigm, the study adopted a qualitative approach and employed a single-case study design within one public university in South Africa. Participants comprised university leaders, academic staff, professional support staff, and undergraduate students involved in or affected by AI governance and implementation. Data were collected through semi-structured interviews, focus group discussions, and document analysis and analysed using thematic analysis supported by inductive coding. The findings indicate that limited policy transparency, context-insensitive governance frameworks, unequal access to AI technologies, and weak institutional accountability can reinforce educational inequalities, particularly among first-generation and under-resourced students. Conversely, participatory governance, transparent decision-making, stakeholder engagement, and enhanced digital literacy promote more equitable and responsible AI implementation. The study proposes a multi-level governance model integrating institutional policy, stakeholder participation, and pedagogical practice to strengthen equitable AI adoption. It concludes that higher education institutions should develop context-sensitive AI governance frameworks, strengthen institutional capacity, and expand equitable access to AI technologies to advance fairness, inclusion, and responsible AI implementation.
R. Lumadi· International Journal of Stu...· 0 citations
The study identifies key themes in generative AI governance, including responsible experimentation, transparency, AI literacy and faculty discretion in policy implementation, including responsible experimentation, transparency, AI literacy and faculty discretion in policy implementation.
Abdullah Alotaibi, A. Aseery, Abdulaziz A. Alfayez et al.· British Educational Research...· 0 citations
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.
Dr. Sixbert Sangwa, Dennis Ngobi, Emmanuel Ekosse et al.· Artificial Intelligence and...· 11 citations· ⚡1
This conceptual paper synthesizes insights from ten institutional cases across global contexts and draws on five theoretical foundations, Diffusion of Innovation, the Technology Acceptance Model, Self-Determination Theory, Social Learning Theory, and Academic Integrity frameworks, to propose a process model of AI adoption and use in higher education.
Nayyer Naseem, Maureen Leary, Johnson C. Smith University· 1 citation
The findings indicate that GenAI adoption in African HEIs is expanding but uneven, concentrated in digitally advanced nations, enhancing personalization, multilingual learning, and research productivity, yet raises ethical concerns about academic integrity.
O. Apata, Peter Oyewole, S. Ajose et al.· Journal of University Teachi...· 1 citation
Regression analysis showed that AI familiarity, frequency of use, and policy awareness were significantly associated with stronger support for empowerment-oriented governance, which inform a five-pillar framework for responsible AI integration encompassing AI Literacy Integration, Stage-Based Access, Transparent Use Norms, Assessment Innovation, and Faculty Development.
A. Akib, Mohammad Aseer Intisar, Md. Sabbir Ahmed et al.· The Compass· 0 citations
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