Extending the UTAUT model to explore the acceptance and use of generative AI: the roles of generative AI identity and trust

Abstract

Introduction Generative AI (GenAI) technology has been rapidly integrated into diverse domains, including education. It has fundamentally reshaped the global learning landscape, exerting a significantly positive influence on students’ learning experience. However, the factors influencing adult learners’ behavioral intention to use GenAI have not yet been fully understood. Therefore, this study aims to explore key factors influencing the behavioral intention to use GenAI among adult learners from central Taiwan. Based on the unified theory of acceptance and use of technology (UTAUT) model, this study integrated two constructs—GenAI identity and trust—to extend the model. Methods A structured questionnaire survey was performed to collect data from 718 adult learners who were aged 50 or above and from central Taiwan. Partial least squares (PLS) and Partial least squares-Multi-group analyses (PLS-MGA) were employed for data analysis. Results The following results were obtained: (1) social influence and facilitating conditions are significant antecedent factors influencing adult learners’ behavioral intention to use GenAI—conversely, performance expectancy has a negative influence on such intention; (2) GenAI identity and trust are key predictive variables of performance expectancy and effort expectancy; (3) different gender groups exhibit significant differences in most structural paths of the research model. Discussion These findings provide theoretical support for context-sensitive strategies in adult learning and the educational application of GenAI.