Responsible Governance of Generative AI in Higher Education: Integrating Ethics, Policy, and the REM Framework - Shrestha, Yugal (Apex Journal of Business and Management, 2026)
Amid the global surge of generative AI, Nepal’s higher education institutions are adopting AI at a pace that outpaces existing governance mechanisms, exposing ethical, pedagogical, and strategic vulnerabilities. Despite rapid adoption, there is no integrative framework ensuring AI adoption is aligned with ethical safeguards, institutional strategy, and learning outcomes. Existing approaches at both global and local levels often offer patchwork ethical solutions, lacking a holistic design that connects policy, pedagogy, ethics, and governance. This paper introduces the Responsible Expansion Model (REM), a conceptual architecture guiding institutions in the responsible, strategic, and ethically grounded adoption of AI. Drawing on global literature and insights from Nepal—including the government’s AI conceptual paper and rising digital literacy—REM treats the country as a living laboratory for higher education innovation. It situates local realities within global best practices, emphasizing stakeholder engagement, continuous monitoring, and iterative adaptation. By combining these pillars into a dynamic, co creative framework, REM provides a locally contextualized yet globally relevant roadmap, resonating with interdisciplinary and management perspectives such as dynamic equilibrium and adaptive management, and establishing empirically testable propositions for responsible AI adoption in higher education.