HHS is moving to accelerate the use of Artificial Intelligence in clinical care while trying to define the guardrails for safe and effective adoption. The department opened a request for information to gather feedback from clinicians, patients, developers, health systems, and the broader public on how Artificial Intelligence is being used, where it is falling short, and what barriers are slowing adoption. The effort follows broader federal guidance directing agencies to improve public services with Artificial Intelligence while maintaining safeguards for civil rights, civil liberties, and privacy.
Inside the department, HHS has already been building its own Artificial Intelligence strategy and extending large language model tools to employees. In parallel, officials are trying to understand how Artificial Intelligence will affect healthcare delivery more broadly. The department sees promise in tools that reduce administrative burden, including ambient documentation, scheduling support, billing, and prior authorization workflows. HHS also pointed to patient-facing use cases, especially support for behavior change in chronic conditions, where providers want more sustained engagement than traditional care models can easily deliver. Additional areas of interest include maternal health, support for an aging population, and accessibility tools for people with disabilities.
Trust and privacy remain central to the department’s approach. HHS is emphasizing what it calls data liquidity, meaning the ability for patient data to move securely between providers and patients in ways that reduce duplication of care and improve coordination. Officials highlighted TEFCA, the Trusted Exchange Framework and Common Agreement, as a nationwide interoperability network designed to let different healthcare systems exchange data securely. The aim is to build trust into the network from the start so patients and providers can be confident that exchanged information is accurate, secure, and matched to the right individual.
HHS expects the public comments to shape what comes next across the department and its agencies, including CMS, FDA, and CDC. Themes from the responses are expected to inform future policy actions tied to regulation, reimbursement, and research and development. The department signaled that stakeholders should expect broad change over the next years from feedback and as this technology advances. The central challenge is no longer whether Artificial Intelligence will influence clinical care, but how to guide its use so it improves patient outcomes, lowers burden, and preserves trust.
