Can AI reshape genomic research and clinical decision making - and what safeguards are needed to ensure these tools are trustworthy, accurate, and effective? A National Academies' Roundtable on Genomics and Precision Health public workshop in October 2025 explored current and future applications of AI in genomics and precision health from translational research to clinical applications.
Discussions covered a range of topics from how scientists use AI for translational genomics research, to how clinicians, patients, and caregivers use AI in health settings. With these emerging uses of AI, the workshop also examined the potential future uses of AI while considering the social, ethical, and policy challenges associated with its implementation. Challenges for clinicians include reliance on incomplete electronic health record data, interoperability barriers, genomic nomenclature issues, and inconsistent implementation of clinical guidelines that complicate data exchange and interpretation. Participants emphasized the need for robust information architecture, harmonized standards, representative training datasets, and rigorous evaluation to ensure validity, reliability, and fairness in AI-enabled tools. Patient and caregiver perspectives further illustrated shifting expectations in care, as individuals increasingly use AI to diagnose themselves and manage complex conditions. This shift raises questions about how to integrate AI into clinical settings, and arrive at the right balance of rapid access to information while still navigating the health care system. Ethical and governance considerations were central, with speakers underscoring privacy risks, transparency in model development and use, appropriate regulatory oversight for generative AI, and the importance of human-in-the-loop architectures in clinical decision making.