Artificial Intelligence (AI) has become an integral part of students’ academic activities, yet the mechanisms driving its adoption remain insufficiently explained. This study examines how perceived usefulness and AI self-efficacy influence AI adoption, with attitude toward AI as a mediating variable. Using a quantitative approach, data were collected from 187 university students in Jakarta and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that both perceived usefulness and AI self-efficacy have significant positive effects on attitude toward AI, while attitude strongly predicts AI adoption. Mediation analysis confirms that attitude plays a central role in translating students’ evaluations and confidence into actual usage behavior. These findings suggest that AI adoption is not directly driven by perception or capability alone, but by how these factors shape students’ overall evaluation of AI. The study contributes to the literature by offering a mediation-based perspective that integrates cognitive, belief-based, and affective dimensions into a unified framework. Practically, the results highlight the importance of fostering positive attitudes and user confidence, rather than focusing solely on technical skills, to support effective AI integration in higher education.

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