Policy brief: AI-first Medicaid: how CMS can build a smarter safety net with Precision Benefits
Medicaid serves over 70 million Americans, yet barriers to consistent, high-quality care endure due to workforce shortages, fragmented service delivery, and administrative burden. Artificial intelligence (AI) offers not just operational efficiency but the potential to transform the Medicaid care experience. AI-powered digital assistants can deliver 24/7 multilingual voice or text support, expanding access to personalized, emotionally-intelligent assistance. Under existing workforce supervision, these agents can bridge critical gaps in behavioral health and community coordination through tools like therapy chatbots that reduce loneliness and improve engagement. As “embedded staff” in provider offices and community organizations, digital assistants can create a unified infrastructure for whole-person care. We introduce the concept of Precision Benefits: delivering the right support to the right person at the right time to prevent avoidable health and social deterioration. This aligns with administrative and eligibility reforms in H.R.1, which require states to improve efficiency and verification while fostering innovation and preserving state authority over AI regulation. Realizing this vision demands responsible AI development – addressing safety, bias, privacy, and trust – and modernization of infrastructure and payment models. Yet the opportunity is clear: AI can power a smarter and more equitable Medicaid system, one that puts everyone on an upward life trajectory.
Authors
- Roxana Daneshjou (ORCID: https://orcid.org/0000-0001-7988-9356)
- Nathan Favini
- Neil Batlivala
- Marko Mijic
Institutions
- Kaiser Permanente (US)
- Teledyne FLIR (United States) (US)
- Stanford Medicine (US)
- Berkeley Public Health Division (US)
- Spiria Medical (US)
- Carnegie Mellon University (US)
- University of California, Berkeley (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-11-28
- DOI
- https://doi.org/10.1038/s41746-025-02195-9
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00