AI and Suicide Prevention: A Cross-Sector Primer
Emily Saltz, Claire R. Leibowicz
TLDR
This primer maps challenges and solutions for safely integrating AI chatbots into suicide prevention, highlighting the urgent need for cross-sector standards.
Key contributions
- Provides an overview of clinical best practices for suicide prevention.
- Analyzes how frontier AI systems detect and respond to suicide and NSSI queries.
- Maps challenges of general-purpose AI chatbots across model, product, and policy layers.
- Identifies priority areas for urgent cross-industry alignment in AI and mental health.
Why it matters
AI chatbots are already used for mental health support, including crisis situations, despite lacking clinical validation. This paper provides a crucial cross-sector reference point, identifying urgent areas for alignment to ensure AI tools safely and effectively prevent suicide and promote well-being.
Original Abstract
AI chatbots already function as de facto mental health support tools for millions of people, including people in crisis. Yet, they lack the clinical validation, shared standards, and coordinated oversight that their societal role demands. This primer was developed in conjunction with a multistakeholder workshop hosted by Partnership on AI in 2026, convening AI labs, mental health practitioners, people with lived experience, and policymakers, to provide a common cross-sector reference point for the current state of the field of AI and suicide prevention. It begins with an overview of clinical best practices, then turns to how frontier AI systems (as of winter 2026) detect and respond to suicide and non-suicidal self-injury (NSSI) queries. Together, these provide insight into what it would take to design and implement AI tools that not only better prevent suicide and NSSI, but also promote overall well-being. Drawing on clinical literature, publicly available AI lab policies, an emerging landscape of evaluation frameworks, and conversations with leaders across the AI and mental health fields, we map challenges posed by general-purpose AI chatbots for mental health across model, product, and policy layers, ultimately highlighting priority areas where cross-industry alignment is both urgently needed and achievable.
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