HHS Seeks Input on Speeding AI Adoption in Clinical Care

Released on Friday, the RFI asks stakeholders how HHS could leverage its regulatory and policy authorities to improve patient and caregiver experiences, reduce administrative burden on providers, enhance the quality of care, and lower healthcare costs.

The US Department of Health and Human Services (HHS) has issued a request for information (RFI) seeking industry input on how the department can accelerate the adoption of artificial intelligence across healthcare, including its use in clinical care settings.

Released on Friday, the RFI asks stakeholders how HHS could leverage its regulatory and policy authorities to improve patient and caregiver experiences, reduce administrative burden on providers, enhance the quality of care, and lower healthcare costs.

The department is also seeking detailed feedback on steps it could take to support faster and safer implementation of AI tools in clinical environments.

According to the RFI, HHS is evaluating how existing digital health and software regulations may need to evolve to accommodate AI-based tools. The department is also requesting input on simplifying payment and reimbursement mechanisms to encourage AI adoption, as well as identifying research and development investments that could establish best practices for clinical use.

The RFI was jointly issued by the HHS Office of the Deputy Secretary and the Assistant Secretary for Technology Policy (ASTP), along with the Office of the National Coordinator for Health Information Technology (ONC). The move builds on recent actions by the Trump administration aimed at promoting AI deployment across federal agencies, including the release of an HHS-wide strategy for using AI tools internally.

The Trump administration has largely pursued a deregulatory approach to artificial intelligence, arguing that excessive oversight could slow innovation and deployment. Earlier this month, President Donald Trump signed an executive order seeking to challenge certain state-level AI laws viewed as restrictive.

However, the limited federal oversight framework has raised concerns within the healthcare sector, where improper AI deployment could pose risks to patient safety. Challenges cited by experts include inaccurate or misleading outputs, biased training data, and performance degradation of AI models over time.

As a result, many health systems have so far prioritized AI tools for administrative and back-office functions, such as revenue cycle management, prior authorization processing, and clinical documentation. These use cases are generally viewed as lower risk compared to direct clinical decision support or patient-facing applications.

Through the RFI, HHS is now seeking guidance on how it can help expand AI use into clinical care while maintaining safeguards. The department said it aims to create a regulatory environment that is “well understood, predictable, and proportionate to any risks,” enabling rapid innovation while protecting patients and their health data.

HHS is also requesting feedback on reimbursement policy changes that could allow payers to promote access to AI-driven clinical interventions, increase competition among AI developers, and improve affordability and access to AI tools. In addition, the agency is exploring how public-private partnerships and cooperative research agreements could support broader AI adoption.

Comments are due 60 days after the RFI is published in the Federal Register on December 23.

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