Understanding and Modeling Technology Adoption in a New Era: A Cross-Sectional Study on Higher Education Teachers’ Adoption and Use of Generative Artificial Intelligence

The rapid advancement of generative artificial intelligence (GenAI) has been discussed as offering both opportunities and challenges in education. With the widespread adoption and distinctive technological characteristics of GenAI, there is a growing need for research examining whether existing technology adoption models adequately explain its use in higher education contexts. This cross-sectional study addressed this need by investigating higher education teachers’ (n = 128) adoption and use of GenAI in their teaching practices. A conceptual model based on the extended UTAUT framework for AI tools was developed and tested using Partial Least Squares Structural Equation Modeling. The results indicated that teachers’ perceptions of GenAI error rates significantly predicted their performance expectancy, and in turn, positively influenced both adoption and frequency of use. Contrary to expectations, perceived ease of use and social influence did not significantly affect adoption or use. Overall, the findings highlight the importance of adapting traditional information systems adoption models to account for the distinctive characteristics of GenAI technologies.