Ethical Governance of Generative AI in Higher Education in the Absence of Binding Law

Abstract The rapid diffusion of generative artificial intelligence in higher education has outpaced the development of empirical and regulatory understanding of how such technologies are adopted and ethically governed. While existing research emphasizes early-stage acceptance or technical impacts, limited attention has been given to post-adoption contexts where Generative AI use has become routine and institutionally pervasive. This study addresses this gap by examining the distinct mechanisms underlying Generative AI adoption and ethical engagement among students and lecturers in Indonesian higher education. Using survey data from 311 respondents and partial least squares structural equation modeling, the findings show that behavioral intention is driven by habit, hedonic motivation, and social influence, while traditional acceptance factors are no longer salient. This indicates normalized academic use. Although behavioral intention remains a significant predictor of actual use, ethical behavior follows a different logic. Ethical generative AI behavior does not emerge from use itself but depends decisively on institutional governance and normative clarity.