The association between generative AI acceptance and college students’ career preparation: the serial mediating role of AI trust and career confidence and the moderating role of intrinsic motivation

Against the backdrop that artificial intelligence (AI) is reshaping the labor market and occupational ecosystem, how college students build career preparation amid technological uncertainty has become a pressing question. Integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with Social Cognitive Career Theory (SCCT), this study constructs a research model in which AI acceptance is associated with career goal setting through AI trust and career confidence, and it examines the moderating role of intrinsic motivation. This study surveys undergraduate students in Chinese universities, obtaining 539 valid responses. The results show that (1) both performance expectancy and effort expectancy are positively associated with AI trust, with a stronger association for performance expectancy; (2) AI trust is positively associated with career confidence; (3) career confidence is positively associated with career goal setting; (4) AI trust and career confidence play a serial mediating role between performance expectancy, effort expectancy and career goal setting; (5) intrinsic motivation positively moderates the relationship between AI trust and career confidence, such that this association is stronger at higher levels of intrinsic motivation. These findings reveal how AI acceptance relates to college students' career preparation and offer evidence for universities to implement AI literacy education and career counseling.