RESPONSIBLE GOVERNANCE OF GENERATIVE AI IN HIGHER EDUCATION: ORGANISATIONAL READINESS, FACULTY TRUST, AND ADMINISTRATIVE PERFORMANCE

Abstract

Generation AI is being introduced in higher education via teaching, assessment, research, student services, communication, admissions, quality assurance, and administration. The institution-level approaches are centred around the concerns about academic malpractice or the adoption of tools. However, the management of GenAI use requires a more comprehensive approach, as universities need to establish a legitimate framework for the selection, regulation, oversight, and modification of its use. The proposed integrative conceptual review seeks to develop a responsible governance framework for GenAI that includes governance maturity, organisational readiness, faculty trust, responsible adoption, and administrative effectiveness. Based on the technology-organisation-environment framework, the literature on the development of institutions' AI policy, and theories of trust, six governance domains are identified: purpose of governance, decision-making, data and privacy, academic and research integrity, capability and inclusion, and assurance and accountability. Governance is seen as a means of fostering innovation by minimising uncertainty and coordinating resources; however, overly restrictive or fragmented governance may prevent learning and encourage the use of GenAI behind the scenes. The faculty trust is interpreted as balanced trust in the technology and institutional management. Five propositions describe the impacts of governance maturity, readiness, involvement in governance, role clarity, and environmental pressure. Mixed-methods research, including policy content analysis, surveys, interviews, and administrative indicators in universities, is proposed. The paper makes a contribution to the area of higher education management by considering GenAI adoption beyond the classroom and treating it as an institutional problem of capability and accountability.