Generative AI Adoption and Governance in African Higher Education: A Mixed-Methods Study of Ghanaian Universities
Abstract
Background and Aim: The rapid emergence of generative artificial intelligence (GenAI) in higher education offers transformative opportunities while creating substantial governance challenges, particularly in resource-constrained Global South settings. This study examined GenAI adoption, perceptions, and governance frameworks across Ghanaian higher education institutions, addressing limited empirical evidence concerning AI governance in Africa. Materials and Methods: A sequential explanatory mixed-methods design was employed. Structured surveys collected quantitative data from 1,235 students and 247 academic staff across 12 public and private Ghanaian universities. Semi-structured interviews with 28 administrators, policymakers, and academics generated qualitative evidence. Guided by the Technology Acceptance Model and institutional theory, the study applied descriptive statistics, inferential tests, and thematic analysis. Results: Regular GenAI use was reported by 67.3% of students and 54.3% of academic staff using ChatGPT and Microsoft Copilot. Perceived usefulness and ease of use significantly predicted behavioural intention, explaining 58% of its variance. Nevertheless, no participating Ghanaian university had a formal, publicly accessible AI policy, resulting in inconsistent assessment practices and concerns regarding fairness, transparency, and accountability. Five governance challenges emerged: inadequate policy readiness, disparities in digital literacy, infrastructure limitations, ethical and academic-integrity risks, and cultural relevance concerns. Conclusion: The study proposes a context-sensitive governance framework encompassing eight dimensions: academic integrity; ethical and responsible use; privacy and security; equitable access; GenAI literacy; integration strategy; human oversight and accountability; and institutional infrastructure. It provides evidence from an under-researched African context and practical guidance for policymakers, university administrators, and educational technologists pursuing responsible, equitable, and contextually appropriate GenAI integration.