Generative AI governance in higher education: a case study from Africa

Introduction The rapid rise of generative artificial intelligence (Gen-AI), particularly large language models (LLMs), is reshaping the higher education landscape. Yet, there is limited empirical documentation of how African universities are integrating Gen-AI into teaching, learning, and research. This study presents a case study of the University of KwaZulu-Natal (UKZN), one of the first African institutions to develop and implement comprehensive academic guidelines for the responsible use of Gen-AI, aligned with national policy priorities and global debates on academic integrity, transparency, and innovation. Methods Adopting a qualitative, single-institution case study design, this research draws on process tracing, comparative policy analysis, institutional records, and the authors’ direct involvement as members of the AI Task Team. The guideline development process was documented and analysed, from inception and internal deliberation to external peer review, institutional consultation, and final adoption. Results The resulting UKZN AI Academic Guidelines are based on four foundational principles: encouraging innovation, ensuring ethical and responsible use, maintaining academic rigour, and building institutional capacity. They establish clear policies on Gen-AI adoption across teaching and research, including curriculum integration, standards for disclosure and authorship, approaches to plagiarism, and guidance on data protection. The guidelines also provide a tiered disclosure framework and embed capacity-building initiatives to support AI literacy among staff and students. Discussion This case study demonstrates how a higher education institution in the Global South can translate national AI policy into actionable institutional governance while addressing contextual challenges such as resource constraints, digital divides, and multicultural considerations. By framing Gen-AI as an enabling tool rather than a threat, the UKZN model offers a replicable pathway for other African and Global South universities seeking to integrate AI responsibly, enhance academic productivity, and prepare graduates for an AI-driven future.

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Publication Details

Journal
Frontiers in Political Science
Published
2025-12-09
DOI
https://doi.org/10.3389/fpos.2025.1666661
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Generative AI governance in higher education: a case study from Africa

Siyabonga Dlamini, Anil A. Chuturgoon, Wayne Hugo, Reginald Gerald Govender et al.
Frontiers in Political Science
Artificial Intelligence in Healthcare and Education
article

Generative AI governance in higher education: a case study from Africa

Siyabonga Dlamini, Anil A. Chuturgoon, Wayne Hugo, Reginald Gerald Govender, Hafizah Y. Chenia, Nyna Amin, André Vosloo, Donrich Willem Thaldar, Neil A. Koorbanally, Marietjie Botes, Sinegugu Evidence Duma, Abdulbaqi Badru, Janet Bruce-Brand
article en

Abstract

Introduction The rapid rise of generative artificial intelligence (Gen-AI), particularly large language models (LLMs), is reshaping the higher education landscape. Yet, there is limited empirical documentation of how African universities are integrating Gen-AI into teaching, learning, and research. This study presents a case study of the University of KwaZulu-Natal (UKZN), one of the first African institutions to develop and implement comprehensive academic guidelines for the responsible use of Gen-AI, aligned with national policy priorities and global debates on academic integrity, transparency, and innovation. Methods Adopting a qualitative, single-institution case study design, this research draws on process tracing, comparative policy analysis, institutional records, and the authors’ direct involvement as members of the AI Task Team. The guideline development process was documented and analysed, from inception and internal deliberation to external peer review, institutional consultation, and final adoption. Results The resulting UKZN AI Academic Guidelines are based on four foundational principles: encouraging innovation, ensuring ethical and responsible use, maintaining academic rigour, and building institutional capacity. They establish clear policies on Gen-AI adoption across teaching and research, including curriculum integration, standards for disclosure and authorship, approaches to plagiarism, and guidance on data protection. The guidelines also provide a tiered disclosure framework and embed capacity-building initiatives to support AI literacy among staff and students. Discussion This case study demonstrates how a higher education institution in the Global South can translate national AI policy into actionable institutional governance while addressing contextual challenges such as resource constraints, digital divides, and multicultural considerations. By framing Gen-AI as an enabling tool rather than a threat, the UKZN model offers a replicable pathway for other African and Global South universities seeking to integrate AI responsibly, enhance academic productivity, and prepare graduates for an AI-driven future.

Frontiers in Political ScienceVol. 7
The University of Texas at Austin (US), University of KwaZulu-Natal (ZA)
Openalex Percentile: Top 66%
Artificial Intelligence in Healthcare and Education
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