The Role of Artificial Intelligence in Mental Health: A Comprehensive Review

Abstract

Artificial intelligence (AI) is rapidly transforming mental health care by enabling scalable, personalized, and timely interventions across diagnosis, treatment, and follow-up. This review explores the integration of machine learning, natural language processing, and conversational agents in mental health services between 2020 and 2025. Key applications include digital phenotyping, chatbot-assisted therapy, and clinical decision support systems, each offering new opportunities while raising concerns around equity, ethics, and transparency. Human-centered design and stakeholder engagement are emphasized to enhance usability and trust. The paper also examines ethical challenges such as data privacy, algorithmic bias, lack of clinical validation, and unclear accountability, particularly for underserved populations. Recommendations include robust regulatory frameworks, inclusive development practices, and continuous monitoring to ensure safe and effective deployment. Greater investment in open-access tools and training for clinicians is also advocated to reduce disparities and promote digital inclusion. Future directions call for the development of multimodal AI systems, cross-sector collaboration, and the establishment of field-specific ethical guidelines. While AI holds transformative potential, its success hinges on responsible implementation that complements rather than replaces-human empathy and clinical judgment in mental health care.