TLDR: The Centers for Disease Control and Prevention (CDC) has announced that its generative AI tools have saved agency workers an estimated 41,000 hours, yielding a more than 500% return on investment. This success was highlighted by CDC’s acting chief AI official, Travis Hoppe, at FedScoop’s FedTalks, as the Department of Health and Human Services (HHS) begins its own department-wide deployment of ChatGPT.
The Centers for Disease Control and Prevention (CDC) has achieved significant efficiencies through its adoption of generative artificial intelligence, with agency workers saving an estimated 41,000 hours. This impressive figure, alongside a reported 500% return on the agency’s initial investment in the technology, was revealed by Travis Hoppe, CDC’s acting chief AI official, during a fireside chat at FedScoop’s FedTalks on Thursday, September 18, 2025.
Hoppe noted that the CDC’s approximately 10,000 workers have engaged in 1.2 million chats with the agency’s existing generative AI offerings. This success comes as the Department of Health and Human Services (HHS) initiates its own department-level deployment of ChatGPT, a move Hoppe described as ‘exciting.’
Long before the recent HHS rollout, the CDC was a pioneer in the federal government, being the first agency to make ChatGPT available to all its workers back in 2023. Furthermore, the CDC developed the first generative AI guidance, which was subsequently shared with and utilized as a model by other federal partners, including the Department of Commerce and the Office of Personnel Management.
The agency is set to report a doubling of AI use cases in its upcoming annual public inventories of the technology. Last year’s inventory included around 50 submissions, a number expected to significantly increase this year. Current AI applications at the CDC include ‘FluSight,’ a tool that analyzes hospital data to predict flu outbreaks, and ‘TowerScout,’ a computer vision project that uses satellite imagery to identify cooling towers, potential sources for Legionnaires’ disease outbreaks.
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Hoppe also underscored the critical role of data in AI initiatives, highlighting the ‘1CDC data platform’ as a key effort to unify data and dismantle ‘data silos.’ He emphasized that data modernization and interoperability are foundational to enabling advanced AI projects.
