AI utilization, enjoyment, trust and instructor competence as predictors of intercultural communication competence among Chinese students

International students in China navigate both linguistic and cultural adaptation demands in classrooms increasingly infused with artificial intelligence (AI). Guided by the broaden-and-build theory of positive emotions, this study tested whether AI-mediated learning enjoyment channels the impact of AI-mediated interaction utilization on communication competence in intercultural contexts, and whether trust in AI recommendations and instructor AI pedagogical competence strengthen this indirect effect. Survey data from 427 students in Wuhan, Xi’an, and Hangzhou were analyzed using PLS-SEM. Results revealed a significant direct effect of AI utilization on intercultural competence (β = 0.292) and a complementary enjoyment-mediated pathway (β = 0.051). Both trust and instructor competence amplified the indirect link. The model explained 34.7% of the variance in intercultural competence, offering empirical guidance for AI-rich, globally connected campuses.