Exploring the Factors Influencing AI Adoption Intentions in Higher Education

This study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI) and the Technology-Organization-Environment (TOE) framework was proposed and tested using data collected from 367 higher education students, faculty members, and employees. The findings reveal that Compatibility, Complexity, User Interface, Perceived Ease of Use, User Satisfaction, Performance Expectation, AI introducing new tools, AI Strategic development, Availability of Resources, Technological Support, and Facilitating Conditions significantly impact AI adoption intentions. At the same time, Competitive Pressure and Government Regulations do not. Demographic factors, including major and years of experience, moderated these associations, and there were large differences across educational backgrounds and experience. The SPSS Amos 24 was used for SEM to choose the best-fitting model that proved to be more efficient than traditional multiple regression analysis.