Abstract: As the core force of the future teaching workforce, pre-service teachers′ acceptance of artificial intelligence technology is crucial for its practical application and sustainable development in the teaching field. Based on this, the UTAUT model is employed to explore the factors influencing their acceptance of AI technology. Empirical analysis shows that performance expectancy, effort expectancy, social influence, facilitating conditions, and AI literacy have significant positive effects on behavioral intention, whereas perceived risk takes a significant negative effect. Social influence bears the most prominent predictive effect on behavioral intention; AI literacy, performance expectancy, and other variables show significant positive effects, while perceived risk shows a significant negative effect. Gender, major, and proficiency level play moderating roles in the paths of "AI literacy → behavioral intention" and "effort expectancy → performance expectancy." Based on attribution analysis, targeted strategies to enhance pre-service teachers′ acceptance of AI technology can be proposed from three dimensions namely environment, perception, and individual-shaping positive norms and improving supporting conditions, enhancing utility perception and reducing risk perception, and stimulating endogenous motivation and cultivating sustained willingness to use.

Key words: pre-service teachers, artificial intelligence, AI technology, technology acceptance, UTAUT model