The Future of Artificial Intelligence and Emerging Technologies in Mental Health: Prospects, Challenges, and a...

Artificial intelligence (AI), alongside emerging digital and neurotechnologies, is increasingly incorporated into mental health care, psychosomatic medicine, and psychotherapy. However, the clinical value of these tools cannot be judged by technical performance alone. These fields are characterized by diagnostic heterogeneity, reliance on language-based and self-reported information, complex biopsychosocial pathways, and substantial interindividual variability in treatment response. Clinically meaningful progress therefore requires integrating technological progress and biological markers with patients' lived experience, personal history, and social context to catalyze person-centered precision assessment, decision-making and intervention.

This review examines how AI and emerging technologies may contribute to mental health care across diagnostic assessment, biomarker development, treatment selection, personalized neuromodulation, adaptive interventions, and conversational agents. We argue that AI should support and improve, not replace, clinical assessments and care by integrating complex biopsychosocial data into precision person-centered decision making and intervention. Realizing this potential will require careful attention to clinical validation, safety, equity, commodification and governance.

The clinical value of AI and emerging technologies will depend on their responsible integration into context-sensitive, person-centered mental health care. AI has the potential to strengthen diagnostic assessment, inform treatment selection, and expand therapeutic options while preserving the centrality of the human therapeutic alliance. Successful implementation requires combining computational precision with clinical judgment, ethical oversight, and demonstrated clinical benefit to improve clinical outcomes and quality of life.