Artificial intelligence (AI) is reshaping university education by offering personalized teaching assistance tailored to each student’s cognitive needs. Despite its global rise, AI’s adoption in higher education in developing nations like Bangladesh is sparse. This study, gathering 363 responses from Bangladeshi universities, employed PLS-SEM, ANN, and fsQCA to identify key antecedents influencing students’ intentions to use AI teaching aids. Findings highlight that interactivity, positive attitudes towards AI, hedonic motivation, perceived benefits, and compatibility significantly drive students' adoption intentions. In contrast, facilitating conditions, social identity, and self-efficacy showed no significant effect. This research provides a roadmap for integrating AI in teaching, emphasizing the need for stakeholder engagement to foster AI adoption in environments lacking personalized instruction. The multi-method analytical approach not only bolsters the study’s predictive accuracy but also sets a precedent for future AI adoption research in education. The results are particularly relevant for developing countries, offering strategies to overcome educational constraints and improve learning outcomes.