Artificial Intelligence for Mental Health Monitoring: A Solution for Digital Behavioral Health Care and Education—An Umbrella Review

Background: The global burden of mental health disorders continues to escalate, placing immense strain on healthcare systems already challenged by workforce shortages and systemic barriers. As traditional models struggle to meet rising demands, artificial intelligence (AI) has emerged as a promising tool for enhancing the detection and monitoring of psychological distress. Aim: This umbrella review aimed to synthesize high-level evidence on how AI is employed in mental health monitoring and assess its potential to support digital behavioral health care and education. Methods: Following PRISMA 2020 guidelines, the review integrated findings from 29 systematic reviews, scoping reviews, and meta-analyses published between 2013 and 2025. Studies were selected using a rigorous, multistage screening process and evaluated through the Joanna Briggs Institute appraisal tools. Thematic synthesis was applied to extract and organize recurring insights from diverse digital and clinical contexts. Results: The results revealed that AI technologies, including machine learning, natural language processing, wearable sensors, and chatbots, enhance diagnostic accuracy, predict crises, and improve access to care. AI's adaptability across mobile platforms, educational settings, and telehealth environments was particularly evident, showing promise for underserved and stigmatized populations. However, concerns around data privacy, algorithmic bias, and user trust were recurrent themes that demand ethical safeguards and transparent governance. Conclusion: AI is redefining how mental health care is delivered by enabling proactive, personalized interventions. While challenges remain, the responsible and inclusive deployment of AI offers a transformative pathway toward accessible, real-time mental health support that bridges gaps in traditional care systems.