AI companies developing autonomous clinical AI systems are increasingly advocating for a federal licensing framework rather than a state-by-state approach, arguing that a national licensure system would provide a more consistent regulatory pathway and reduce the burden of navigating different state medical licensing requirements.
The push for federal oversight comes as states take varying approaches to AI regulation. For example, Utah created an AI regulatory sandbox that allows an AI system to renew prescriptions without direct physician involvement. Other states, however, may be less willing to relax traditional medical licensing requirements, creating a fragmented regulatory landscape.
To address this patchwork of state laws, some policy experts have proposed a national framework. In the 2026 JAMA article, “A Licensure Framework for Autonomous Clinical AI,” the authors recommend establishing a federal licensing regime for autonomous clinical AI overseen by a new entity within HHS.
At the same time, questions are emerging about legal liability when AI systems are involved in patient care. Some AI companies are reportedly exploring ways to limit their responsibility by shifting liability to health care providers, or patients through informed consent agreements. As autonomous AI takes on an increasingly prominent role in clinical decision-making and patient care, questions arise regarding who should be held accountable for errors and how malpractice insurance models should be structured to address AI-driven care. Learn more about Utah’s prescription pilot. Read the JAMA article.
