CHAI Offers Guides for Responsible AI Use in Medicaid Eligibility

The nonprofit Coalition for Health AI (CHAI) has released two Best Practice Guides with the goal of helping states, developers, and implementers responsibly deploy AI in Medicaid eligibility workflows while preventing inappropriate coverage loss as new requirements take effect.

Co-chaired by the National Association of Community Health Centers (NACHC), Centene, HealthTech 4 Medicaid (HT4M), and Pair Team, the development of these guides was informed by experts representing more than 40 health organizations.

The guides focus on two use cases: enrollment and eligibility adjudication, some of the most operationally complex and high-stakes administrative demands. They provide practical, role-based recommendations for using AI responsibly to navigate Medicaid’s new community engagement requirements under H.R.1. 

The release comes ahead of the U.S. Department of Health and Human Services guidance deadline of June 1, 2026, and is intended as a practical resource for state agencies, vendors, and the broader Medicaid community as implementation begins. The guidance is designed to help organizations modernize eligibility operations while reducing the risk of procedural disenrollment and inappropriate coverage loss among eligible beneficiaries.

“We convened experts and organizations closest to this work – from community health centers to technology developers – because the people implementing these new Medicaid requirements needed clear and consistent guidance,” said Brian Anderson, M.D., CEO of CHAI, in a statement. “The guides reflect nearly a year of rigorous, cross-sector collaboration and provide a clear set of best practices grounded in our responsible AI principles, with patient access, fairness, and human oversight at the center.”

Community engagement requirements represent a significant operational shift for state Medicaid programs, moving from one-time eligibility determination to continuous compliance tracking across employment, training, education, volunteering, and exemption status. As states prepare for more frequent touchpoints, expanded documentation needs, and increased risk of procedural disenrollment, AI can play a meaningful role in reducing administrative burden. This can only be done by pairing it with strong oversight, transparency, and safeguards, CHAI said. 

"Community Health Centers (CHCs) are on the front lines of care for 52 million Americans, approximately 50% of whom rely on Medicaid. AI is becoming indispensable, especially for CHCs that need more to do more," said Kyu Rhee, M.D., M.P.P., president and CEO of NACHC and a Tiger Team Co-Chair, in a statement. "With roughly one in five CHCs already using generative AI and many more planning to adopt it, these guides underscore how AI can help cut administrative burden, navigate new Medicaid eligibility requirements, and strengthen revenue so more time and dollars go back into patient care."

The guides include use case examples, a catalog of community-developed AI interventions mapped to specific points in the workflow, and the multi-phase consensus methodology used to produce the guidance. Among the guides’ recommendations: a prohibition on fully automated eligibility denials and disenrollment; a human-in-the-loop requirement for adverse actions; explicit guardrails against “default-to-denial” logic when data is missing or conflicting; confidence thresholds and audit trails for high-stakes determinations; and accessibility, multilingual, and non-digital pathways aligned with WCAG 2.2 AA, ADA, and Section 508.