The impact of artificial intelligence on the diagnosis and treatment of mental disorders: A review of current research

Mental disorders constitute a major global public health challenge, affecting more than one billion people worldwide and contributing substantially to disability, reduced quality of life, and increased healthcare costs. In recent years, artificial intelligence (AI) has emerged as a promising tool for improving the diagnosis, monitoring, and treatment of psychiatric disorders. This review aims to examine current research on the application of AI in mental health care, with particular emphasis on its role in diagnostic assessment, treatment planning, patient monitoring, and digital therapeutic interventions. A narrative review of recent literature published between 2020 and 2026 was conducted using major scientific databases and peer-reviewed publications. The reviewed studies focused on machine learning algorithms, natural language processing, predictive analytics, AI-assisted clinical decisionmaking, and conversational agents used in psychiatric settings. The findings indicate that AI technologies demonstrate significant potential in enhancing diagnostic accuracy, identifying early signs of mental disorders, predicting treatment outcomes, and supporting personalized care. Machine learning models have shown promising results in the detection of depression, anxiety disorders, schizophrenia, and bipolar disorder through the analysis of speech, behavioral, neuroimaging, and electronic health record data. Furthermore, AI-powered chatbots and digital mental health platforms may improve access to psychological support and facilitate continuous patient monitoring. Despite these advantages, important challenges remain, including concerns regarding data privacy, algorithmic bias, transparency, ethical governance, and clinical validation. The successful integration of AI into psychiatric practice requires robust regulatory frameworks, interdisciplinary collaboration, and continued research to ensure safe, equitable, and effective implementation in mental health care.