Benefits, Convenience, Ethics, and Anxiety Shaping Indonesian Students’ Intentions to Adopt Generative Artificial Intelligence - Intan Ramadhani Hasbullah; Andi Imam Ardiansyah; Elma Nurjannah; Stephen Amukune (Artificial Intelligence in Lifelong and Life-Course Education, 2026)
Purpose – This study examines Indonesian university students’ behavioral intention to adopt generative artificial intelligence by extending the technology acceptance model with ethical concern and artificial intelligence anxiety. It evaluates how perceived usefulness, perceived ease of use, ethical concern, and artificial intelligence anxiety jointly shape adoption intention in higher education.Design/methods/approach – A quantitative cross-sectional survey was administered to 96 active undergraduate students at a public university in Indonesia. The extended model was analyzed using partial least squares structural equation modeling to estimate the predictive power and the significance of structural relationships among constructs.Findings – The structural model explained 64.5% of the variance in behavioral intention. Perceived usefulness was the strongest predictor, followed by ethical concern and perceived ease of use. Artificial intelligence anxiety did not significantly influence behavioral intention, suggesting that functional value and ethical awareness outweighed affective apprehension among experienced users.Research implications/limitations - Institutions should prioritize practical integration and clear ethical guidance for generative artificial intelligence use rather than focusing primarily on reducing anxiety. Generalizability is limited by the cross-sectional design, small sample size, and a sample dominated by science and technology disciplines.Originality/value - This study provides empirical evidence that ethical concern functions as a regulatory facilitator rather than a barrier in generative artificial intelligence acceptance, offering a refined lens for responsible adoption policies in Indonesian higher education.