Governing Artificial Intelligence in Higher Education: Policy Implications for Faculty Professional Competence

Abstract

This study investigates how artificial intelligence (AI) is governed in higher education institutions and examines the implications of institutional AI governance policies for faculty professional competence. A qualitative policy analysis approach was employed. Data were collected through document analysis of institutional AI-related policies, including academic integrity guidelines and faculty development regulations, as well as semi-structured interviews with faculty members and academic leaders involved in AI governance and implementation. The data were analyzed using thematic analysis guided by an AI governance framework encompassing pedagogical, governance, and operational dimensions. The findings reveal that higher education institutions have increasingly formalized AI governance through institutional policies. However, these policies are largely regulatory in orientation, with a strong emphasis on ethical compliance, academic integrity, and risk mitigation. Explicit pedagogical guidance and systematic support for faculty professional competence development are limited. As a result, faculty members experience uncertainty in applying AI in teaching and assessment practices and rely predominantly on self-directed or informal learning, leading to uneven levels of AI-related professional competence. The study suggests that AI governance in higher education should move beyond compliance-oriented regulation toward an integrative, capacity-building approach. Institutional AI policies need to be aligned with structured faculty development frameworks that incorporate pedagogical guidance, ethical awareness, and operational support to enable responsible and effective AI integration in academic practice.