Generative AI’s expanding role in healthcare may warrant a new regulatory framework — one modeled after how physicians and nurses are licensed, according to researchers from the Philadelphia-based Penn Leonard David Institute of Health Economics.
In an viewpoint article published Nov. 17 in JAMA Internal Medicine, the researchers argue that the FDA’s current oversight of clinical AI tools is designed for static, single-manufacturer software — not the complex, fast-evolving AI now being adopted in hospitals. To close the accountability gap, the article’s authors propose a federal AI licensure model featuring defined scopes of practice, supervised “residency”-style pilots, and ongoing performance monitoring.
Under the proposal, a federal board would issue licenses, while health systems would serve as local credentialing bodies, able to revoke AI privileges if safety thresholds are not met. State medical boards could also take part in oversight, with digital boards tracking complaints and enforcing discipline.
The authors compare today’s AI risks — including hallucinations and performance drift — to 19th-century concerns about unregulated medical practice and argue that licensing could help ensure innovation advances alongside accountability.
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