AI-Driven Behavioral Insights for Personalized Mental Health.

Mental health disorders are a growing global concern, with existing treatments often hindered by limited accessibility, subjectivity in diagnosis, and lack of personalization. This paper explores how Artificial Intelligence (AI) technologies—such as Machine Learning (ML), Natural Language Processing (NLP), and wearable devices—can transform mental health care by enabling early diagnosis, personalized interventions, and continuous monitoring. We highlight recent advancements in digital biomarkers, predictive analytics, and AI-driven teletherapy tools, supported by real-world case studies. Furthermore, the paper addresses key ethical concerns, including data privacy, algorithmic bias, and the importance of transparent and inclusive AI systems. Through a multidisciplinary lens, we advocate for hybrid care models that balance AI innovations with human empathy and outline future directions for research, including explainable AI and multimodal sensitivity analysis. This review underscores the transformative potential of AI in making mental health care more accessible, proactive, and equitable.