HHS seeks public input on AI use and regulation in US clinical care
TL;DR
On December 19, 2025, the US Department of Health and Human Services issued a request for information (RFI) seeking public comment on how to accelerate adoption and use of artificial intelligence in clinical care. The RFI focuses on AI regulation, reimbursement, and research and development, following HHS’s earlier release of an internal AI strategy on December 4.
About this summary
This article aggregates reporting from 1 news source. The TL;DR is AI-generated from original reporting. Race to AGI's analysis provides editorial context on implications for AGI development.
Race to AGI Analysis
HHS asking the field how to govern and pay for AI in clinical care is a sign that healthcare AI is moving from pilots to something closer to infrastructure. By centering the RFI on regulation, reimbursement, and R&D, the agency is implicitly acknowledging that current rules and payment mechanisms weren’t designed for systems that can continuously learn, generate recommendations, or even draft clinical documentation. Before AGI ever shows up in hospitals, the bottleneck will be how we certify, monitor and pay for increasingly autonomous decision support. ([aha.org](https://www.aha.org/news/headline/2025-12-19-hhs-seeks-information-ai-adoption-use-clinical-care))
Strategically, this matters because US healthcare is both a massive market and a high-stakes proving ground for advanced models. If HHS lands on frameworks that enable safe deployment of diagnostic and workflow-support AI systems, it will unlock real-world data and revenue streams that can fund further model development. Conversely, overly restrictive or ambiguous rules could slow adoption, creating room for other jurisdictions to set de facto global norms. For the AGI race, healthcare is one of the first domains where we’ll see how societies respond when AI systems can meaningfully influence life-and-death decisions.
The competitive implications go beyond health-tech startups. Frontier-model providers, cloud platforms, and EHR vendors all have a lot at stake in how HHS defines acceptable use, accountability, and evidence standards for clinical AI.
