Key points are not available for this paper at this time.
Mental health challenges among college students have become a growing global concern, placing increasing pressure on higher education systems to provide effective, scalable, and equitable mental health education and support. This narrative review examines the opportunities, challenges, and strategic responses associated with integrating artificial intelligence (AI) into college students' mental health education. To improve conceptual clarity, it distinguishes educationally oriented AI applications from adjacent domains, including prevention-oriented support, early detection and screening, and supportive quasi-clinical intervention. The review identifies three main opportunity domains: personalized support for self-regulation and mental health learning, AI-assisted early awareness and prevention, and expanded accessibility and institutional reach. It also highlights key challenges related to ethical governance and privacy, accuracy and reliability, and digital divide and inclusivity issues. In response, the review emphasizes the need to strengthen ethical frameworks, improve system reliability and cultural responsiveness, and promote digital and AI literacy within higher education. Overall, current evidence suggests that AI can serve as a valuable complement to professional services and human-centered educational practices. However, the evidence base remains largely short-term and context-dependent, underscoring the need for longitudinal research, stronger institutional governance, and more inclusive implementation strategies. Responsible AI integration therefore requires a balanced, education-centered approach aligned with equity, student well-being, and institutional responsibility.
Wang et al. (Mon,) studied this question.