This study explores the critical role of artificial intelligence (AI) enabled transformation among employees in higher education institutions, a shift essential for enhancing operational efficiency and educational outcomes. The primary aim was to investigate the impact of self-efficacy and technology innovativeness on the acceptance of AI, with attitude as a mediating factor, thus extending the Technology Acceptance Model to understand the dynamics of AI adoption better. Data were collected using a structured survey distributed via email, targeting a purposive sample of employees across various institutions, resulting in 422 valid responses for analysis. The Partial Least Squares Structural Equation Modeling (PLS-SEM) technique was employed to test the hypotheses, providing robust insights into the relationships among variables. Results revealed that both self-efficacy and technology innovativeness significantly influence acceptance, with attitude playing a crucial mediating role. Specifically, self-efficacy contributes positively to forming favourable attitudes, while perceptions of innovativeness substantially enhance the acceptance of AI technologies. These findings highlight the need for higher education institutions to invest in training programs that boost employees' confidence and demonstrate the tangible benefits of AI innovations. For future studies, it is suggested that research could expand on demographic variables and explore the longitudinal impacts of AI exposure. Furthermore, the role of organizational culture and leadership in shaping technology perceptions warrants further investigation. The implications of this study are twofold: theoretically, it extends the TAM framework by integrating new dimensions pertinent to AI adoption, and practically, it provides actionable insights for institutions to facilitate successful AI integration by addressing employee readiness and cultural adaptation. Overall, the study underscores the transformative potential of AI in educational settings and the strategic measures needed to harness it effectively.
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