HMN 2025: What is the realistic vision for the future of AI in mental health care

A new analysis examines a potential turning point for artificial intelligence in mental health care. The article, “Feasible but Fragile”: An Inflection Point for Artificial Intelligence in Mental Health Care, reflects on the November 18, 2025 United States House Energy and Commerce Subcommittee hearing on AI chatbots and features an interview with John Torous, MBI, MD, Director of Digital Psychiatry at Beth Israel Deaconess Medical Center and Associate Professor of Psychiatry at Harvard Medical School.

Dr. Torous, who provided expert testimony at the hearing, describes it as a rare early instance of congressional oversight in digital mental health and sees it as signaling the end of “AI exceptionalism“—treating AI tools as unique and therefore outside the standards applied to other clinical innovations. He emphasizes that whether AI fulfills its promise in mental health will depend on decisions made now about oversight, research, and patient safety.

Ending the race to the bottom

The article highlights Dr. Torous’s concern that much of the current AI landscape measures success by user engagement rather than safety or efficacy. Drawing on lessons from mental health apps, he warns that focusing on engagement alone is a “race to the bottom” that neither improves safety nor effectiveness.

To address this, Dr. Torous identifies three essential shifts:

• Shifting Incentive Structures: Regulation must move companies away from optimizing for engagement and toward measurable benchmarks for privacy, safety, and efficacy.
• Transparency Over Marketing: Stakeholders must collaborate and conduct transparent, open, rigorous research and develop enforceable standards that safeguard well-being while facilitating innovation: Substance over marketing.
• Patient-Centered Benchmarks: Patient needs and perspectives must be centered in the research conducted and the standards adopted. The article highlights MindBench.ai, a new collaboration between Dr. Torous’s team and the National Alliance on Mental Illness (NAMI). This initiative aims to develop dynamic, patient-centric benchmarks that bring the voices of real users to the forefront of AI evaluation.

Beyond traditional therapy

Dr. Torous sees significant positive potential for AI tools. By integrating personalized data—including physiological, environmental, and emotional information—AI could generate new insights and approaches to mental health care. Provided safety risks are mitigated, AI has the potential to help us move beyond merely replicating existing treatments to a new era of “personalized insights” that could redefine mental health nosologies and create entirely new therapeutic models.

He stresses that this future is “feasible but fragile,” dependent on trust, oversight, and collaboration among clinicians, patients, researchers, regulators, and developers.

The paper is published in the Journal of Medical Internet Research.

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JMIR Publications

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