Mapping the landscape of AI governance in higher education

Abstract

The rapid adoption of Artificial Intelligence (AI), particularly Generative AI (GenAI), has accelerated the need for robust governance in higher education. This study provides a comparative analysis of AI governance frameworks adopted by universities worldwide. A qualitative document analysis was conducted on 43 publicly accessible AI governance documents collected from 35 universities through official institutional websites. Using thematic analysis, the study examined governance principles, scope, institutional structures, implementation strategies, and future-oriented governance practices. The findings reveal increasing convergence around core ethical principles, particularly fairness, transparency, and accountability, alongside a shift from reactive regulation to proactive governance that supports responsible AI adoption. Universities are increasingly establishing formal oversight structures, integrating AI governance into existing institutional processes, and adopting adaptable ‘living’ policies to respond to technological change. Despite variations in implementation, the findings highlight growing international alignment and underscore the need for collaborative, flexible, and context-sensitive AI governance frameworks that promote innovation while safeguarding ethical and institutional values.