Beyond conventional adoption: new insights into AI facilitators in Higher Education Institutions

Guided by the self-regulation theory and the technology acceptance model, this study tests the major drivers of AI facilitators’ usage in higher education (HE) by incorporating self-regulation, academic buoyancy, trust, and agentic engagement to predict the continuance usage intention of AI facilitators. Primary data were gathered from HE students in Oman. Employing PLS-SEM, the results revealed that self-regulation and academic buoyancy positively impact usefulness and ease of use, which positively affects their trust and agentic engagement, leading to the continuance usage intention of AI facilitators. Additionally, academic buoyancy significantly mediates the connection between self-regulation and continuance usage. Theoretical and managerial contributions are outlined. © 2025 The Author(s)