Generative AI in Psychiatry: From Chatbots to Clinical Orchestration
Description
Generative AI is rapidly evolving from simple chatbot interfaces to multi-agent systems capable of supporting triage, workflow augmentation, and clinical decision-making in psychiatry. This presentation provides an overview of current and emerging perspectives on generative AI applications across clinical care, education, research synthesis, and quality improvement, highlighting both empirical findings and real-world implementation challenges. The session concludes with a staged, human-in-the-loop roadmap outlining assistive, collaborative, and semi-autonomous models of care for the responsible integration of generative and agentic AI into psychiatric practice, with a focus on safety, governance, and clinical accountability.
Learning Objectives
By the end of this session, participants will be able to:
Describe key principles of generative and agentic AI and their relevance to psychiatric practice.
Evaluate emerging applications of generative AI across clinical care, education, research, and quality improvement.
Identify risks related to misinformation, bias, hallucination, over-reliance, and regulatory considerations in mental health settings.
Apply a roadmap framework to guide safe and scalable integration of generative AI into psychiatric services.
About the Speaker
Venkat Bhat, MD MSc FRCPC DABPN is a psychiatrist, clinician-scientist, and Associate Professor of Psychiatry at the University of Toronto with cross-appointments at Unity Health and University Health Network. He leads the AI for Mental Health (AI-M) Program and serves as Mental Health Community of Practice Lead at T-CAIREM, advancing AI for mental health and at the interface of mental health and medical illness. He directs federally funded, interdisciplinary initiatives that bring stakeholders across Canada together in areas including wellness and resilience in the Canadian Armed Forces, depression, and PTSD, emphasizing the bidirectional relationship between AI and neuroscience and the safe, equitable, and scalable integration of AI into clinical care, education, and research.
