Artificial intelligence and digital technologies are rapidly reshaping the landscape of mental health research and clinical care. In recent years, interest in their potential to enhance psychiatric assessment, diagnosis, and treatment has grown exponentially. From predictive modelling and natural language processing to digital phenotyping and therapeutic chatbots, these innovations offer unprecedented opportunities to personalize interventions and extend access to care. At the same time, they raise critical questions about ethics, transparency, and the preservation of human connection in digitally mediated psychiatry.

The goal of this Research Topic is to explore how artificial intelligence and digital innovations can be used to advance mental health care while maintaining ethical integrity and human-centered values. Despite remarkable progress in predictive modelling, natural language processing, and digital monitoring, there remains a gap between technical capability and clinical applicability. It aims to bridge that gap by gathering interdisciplinary work on interpretable AI models, alongside studies addressing ethical, relational, and societal implications. By integrating perspectives from psychiatry, psychology, computer science, ethics, and health policy, this Research Topic seeks to highlight both opportunities and challenges in the digital transformation of mental health, with a specific focus on ethical clinical applicability. It specifically aims to encourage responsible innovation that enhances understanding, accessibility, and compassion within the evolving field of digital psychiatry.

The aim of this Research Topic is to highlight cutting-edge interdisciplinary research at the intersection of artificial intelligence, digital innovation, and mental health care. Topics may include:

• AI-driven diagnostics, prognostics, and personalized interventions for clinical care
• Human-AI interaction and the digital therapeutic alliance
• Ethical, legal, and social implications of AI in mental health care
• Explainable and trustworthy AI models for clinical decision support
• Implementation science and digital transformation in psychiatric services
• Computational and data-driven approaches to understanding psychopathology, with a focus on bridging the gap between digital innovation and clinical applicability.

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Artificial Intelligence in Mental Health Care: Toward Human-Centered and Clinically Grounded Innovation