With the rapid development of artificial intelligence (AI) technology, AI educators have become a reality. The advancement and increasing applications of AI technology in higher education not only provide more efficient tools for teachers in long-term and focused teaching, but also provide new active and independent spaces for sustainable self-motivated learning for college students. It is of great importance that the effects of AI educator design are understood to ensure the sustainable development and deployment of AI-driven courses at universities. This paper investigates the influences of AI educators’ autonomy design on students’ usage intentions by delving into how the artificial autonomy of AI educators satisfies students’ needs. Drawing on the uses and gratification (U&G) framework, we theoretically elaborate on how AI educator autonomy (i.e., sensing autonomy, thought autonomy, and action autonomy) influences students’ intentions to use an AI educator through the mediating effects of U&G benefits (i.e., information-seeking gratification, social interaction gratification, and entertainment gratification). By conducting an online survey (N = 673) on college students, we found that the sensing autonomy of AI educators is positively associated with usage intention due to the mediating effects of social interaction and entertainment gratifications; the thought autonomy of AI educators is positively related to usage intention, mediated by information-seeking and social interaction gratifications, and the action autonomy of AI educators is positively linked with usage intention through the paths of information-seeking and entertainment gratifications. Our findings provide both theoretical contributions and practical implications.