Reimagining psychiatric care with agentic AI: promise, challenges, and a roadmap forward

Area of Science:

• Clinical Informatics
• Artificial Intelligence in Psychiatry
• Digital Mental Health

Background:

• Agentic artificial intelligence (AI) signifies a move beyond static clinical decision support tools.
• Psychiatry presents unique opportunities and challenges for agentic AI due to its focus on subjective experience, trust, and longitudinal care.
• Agentic systems offer potential benefits like enhanced documentation, personalized care, continuous monitoring, and expanded access.

Purpose of the Study:

• Define agentic AI specific to psychiatry, differentiating it from decision-support and autonomous systems.
• Synthesize existing evidence on agentic AI applications in psychiatric care.
• Propose potential roles for agentic AI, including assistive, collaborative, and semi-autonomous functions.
• Outline a strategic roadmap for the responsible implementation of agentic AI in psychiatry.

Main Methods:

• Literature synthesis and evidence review.
• Conceptual framework development for agentic AI roles in psychiatry.
• Analysis of potential benefits and risks associated with agentic AI in mental healthcare.

Main Results:

• Agentic AI in psychiatry involves systems that reason, adapt, and act collaboratively with clinicians.
• Potential benefits include improved efficiency, personalized treatment, and extended reach of psychiatric services.
• Key risks identified include algorithmic bias, lack of explainability, privacy concerns, and potential impact on the therapeutic alliance.

Conclusions:

• Agentic AI holds significant promise for transforming psychiatric care delivery and support.
• Responsible implementation requires careful consideration of ethical implications, including bias mitigation and transparency.
• A phased approach, starting with assistive and collaborative roles, is recommended for integrating agentic AI into psychiatric practice.