JMIR Publications

ABSTRACT

Background:

Importance: The rapid expansion of mental health-related artificial intelligence (MH-AI) has outpaced regulatory frameworks, raising urgent questions about safety, accountability, and clinical integration. While federal oversight remains uncoordinated and inconsistent, state legislatures have begun to fill the regulatory void with far-reaching implications for mental health professionals.

Objective:

Objective:

To systematically analyze recent state-level legislation relevant to MH-AI, assess its implications for mental health professionals, and identify areas for policy engagement.

Methods:

Design, Setting, and Participants: A comprehensive review of AI-related bills introduced in U.S. state legislatures from January 2022 through May 2025 was conducted using Legiscan. Bills were screened and categorized using a custom four-tier taxonomy based on their applicability to MH-AI.

Results:

Main Outcomes and Measures: Frequency and content of bills with direct, indirect, or incidental relevance to MH-AI; identification of thematic domains, policy gaps, and clinician-related impacts via a custom tag-by-topic system.

Results:

Among 793 state bills reviewed, 143 were identified as potentially impactful to MH-AI: 28 explicitly referenced mental health uses, while 115 had substantial or indirect implications. Of these 143 bills, 20 were enacted across 11 states. Legislative efforts varied widely, but four thematic domains consistently emerged: (1) professional oversight, including deployer liability and licensure obligations; (2) harm prevention, encompassing safety protocols, malpractice exposure, and risk stratification frameworks; (3) patient autonomy, particularly in areas of disclosure, consent, and transparency; and (4) data governance, with notable gaps in privacy protections for sensitive mental health data.

Conclusions:

Conclusions and Relevance: Most states are actively shaping the regulatory future of MH-AI through legislation targeting AI in general or adjacent AI domains such as health care, with only a small minority attempting to address the unique challenges of regulating AI in mental health care. Clinician and patient engagement is urgently needed to ensure emerging policies are safe, ethical, and aligned with real-world clinical practice.