The Food and Drug Administration (FDA) holds a dual role with respect to artificial intelligence: it regulates AI/ML-enabled medical devices, and it deploys AI internally for agency operations including drug and device review. As a regulator, the FDA's approval pipeline determines which clinical AI reaches patients, connecting it to Healthcare — AI Deployment.
As regulator
As of 2025, the FDA had cleared more than 500 AI/ML-enabled Software as a Medical Device (SaMD) products. Since 2021 the agency has maintained an Action Plan for AI/ML-based SaMD, a framework intended to address continuous-learning AI in clinical settings.
A senior FDA official signaled, in remarks reported July 2, 2026, that the agency will soon seek public input on AI that can practice medicine, after clearing one such product through the 510(k) pathway and engaging with a company pursuing the more stringent de novo pathway (Source: insideaipolicy.com).
The agency's draft agreement on Medical Device User Fee Amendments (MDUFA) reauthorization, cleared by the Office of Management and Budget on July 8, 2026, includes most digital-health priorities stakeholders sought, including health-technology sandboxes and a streamlined pre-submission process (Source: insideaipolicy.com).
AI uses and deployments
The FDA began publicly documenting internal AI deployments in 2025. On May 8, 2025, it announced completion of its first AI-assisted scientific review pilot, alongside an agency-wide AI rollout timeline ("FDA Announces Completion of First AI-Assisted Scientific Review Pilot and Aggressive Agency-Wide AI Rollout Timeline," FDA press release), marking the first time the agency used AI to assist in actual drug and device regulatory review. On June 2, 2025, the FDA launched an agency-wide internal productivity tool ("FDA Launches Agency-Wide AI Tool to Optimize Performance for the American People," FDA press release).
On April 29, 2026, the FDA announced a pilot it described as first-of-its-kind, using cloud computing and AI for real-time clinical drug trials. FDA Chief Artificial Intelligence Officer Jeremy Walsh said the pilot could lead to reductions of 20–40% in overall clinical trial duration (Source: nextgov.com). The same day, the Mayo Clinic disclosed its REDMOD system, an AI tool that flagged subtle changes in routine CT scans 475 days before a pancreatic-cancer diagnosis (Source: bloomberg.com).
On June 4, 2026, the FDA extended the pilot's public comment period by a month, following industry requests for operational detail on how the real-time, AI-assisted trials process would run (Source: insideaipolicy.com).
Policy positions and oversight
On April 24, 2026, HHS Secretary Robert F. Kennedy Jr. argued that the FDA's expanding use of AI tools had accelerated drug reviews and could eventually replace human reviewers and enable personalized medicine, framing AI as something that could make the FDA "irrelevant" (Source: insideaipolicy.com).
Acting Commissioner Kyle Diamantas's first public outline of agency priorities, which became public on July 21, 2026 following the departure of former commissioner Marty Makary, emphasized AI and digital tools to compete with foreign nations, improve nutrition, and protect medical products from shortages (Source: insideaipolicy.com).
Two cross-cutting concerns appear in commentary on the FDA's AI adoption. Tyler Cowen has argued that improved drug discovery does not accelerate availability if FDA review timelines remain slow (Why I Think AI Take-Off Is Relatively Slow (Cowen)); the agency's own AI adoption may speed review, which raises a separate concern about AI-assisted approval errors in a life-critical domain. Separately, Lancet Endoscopist Deskilling Study (2025) reports that clinical AI may erode practitioner skill; the FDA does not currently regulate for deskilling as a risk category.
Relationships
- regulated-by: Congressional oversight; HHS.
- related: Healthcare — AI Deployment, Lancet Endoscopist Deskilling Study (2025), AMA Physician AI Sentiment Report (2026), California AB 3030 (Healthcare AI Disclosure), Why I Think AI Take-Off Is Relatively Slow (Cowen), Government AI Procurement, Federal AI Adoption — Patterns and Tensions.