In a landmark decision announced on May 16, 2025, the U.S. Food and Drug Administration is rapidly accelerating its adoption of artificial intelligence to transform how it evaluates new medical products and therapies.
FDA Commissioner Martin A. Makary has directed all FDA centers to begin AI deployment immediately, with full integration required by June 30, 2025. This aggressive timeline follows the successful completion of a generative AI pilot for scientific reviewers.
The pilot program demonstrated significant efficiency gains in the scientific review process. "I was blown away by the success of our first AI-assisted scientific review pilot," Makary stated in the announcement. "We need to value our scientists' time and reduce the amount of non-productive busywork that has historically consumed much of the review process."
The technology's impact on workflow efficiency has been dramatic. "This is a game-changer technology that has enabled me to perform scientific review tasks in minutes that used to take three days," said Jinzhong Liu, deputy director at the Office of Drug Evaluation Sciences in FDA's Center for Drug Evaluation and Research.
By the end of June, all FDA centers will operate on a common, secure generative AI system integrated with the agency's internal data platforms. The agency plans to continue expanding use cases, improving functionality, and adapting to each center's evolving needs after the initial implementation.
The agency-wide rollout is being coordinated by Jeremy Walsh, FDA's newly appointed chief AI officer, and Sridhar Mantha, who recently led the Office of Business Informatics in the Center for Drug Evaluation and Research. Walsh previously led enterprise-scale technology deployments across federal health and intelligence agencies.
This initiative marks a notable shift from theoretical discussions around AI adoption in government to concrete, agency-wide implementation. The FDA's commitment to modernizing its processes represents a significant step forward in public health administration that could serve as a model for other regulatory bodies.