Implications of the new US AI framework in medicine

Abstract

Artificial intelligence (AI) is entering medicine through diagnostic, administrative, and patient-facing applications, yet governance remains fragmented across medical product regulation, hospital oversight, privacy, civil-rights law, research ethics, and consumer protection. The March 2026 White House National Policy Framework for Artificial Intelligence is a set of nonbinding legislative recommendations to Congress that clarifies the current administration’s proposed direction for AI policy as pro-deployment, pro-infrastructure, and reliant on sector-specific oversight rather than a new central regulator. In international context, this approach differs from the European Union’s more horizontal, risk-based model and from ethics frameworks emphasizing consent, transparency, independent oversight, and protection of vulnerable populations. For medicine, the US framework may accelerate the development and uptake of AI tools by expanding data access, reducing infrastructure barriers, and supporting adoption, but it leaves unresolved a specific governance gap for clinically consequential tools that fall outside traditional Food and Drug Administration-regulated pathways. Addressing that gap will require stronger clinical governance, institutional accountability, transparency, consumer-protection mechanisms, and international interoperability. Medical AI is expanding faster than the governance systems that regulate clinical risk, transparency, and accountability. Here, we examine how the new US AI framework may accelerate adoption while leaving clinically consequential tools outside traditional regulatory pathways.