A newly published Request for Information (RFI) offers a glimpse into the ways the Centers for Medicare and Medicaid Services (CMS) is envisioning using artificial intelligence in the Medicare program across both digital and voice channels. 

The RFI, which has a response deadline of March 31, 2026, notes that current tools used by CMS rely primarily on static comparison tables and documents that can be difficult to navigate, particularly for beneficiaries with limited health literacy, language barriers, or cognitive challenges. During peak enrollment periods, wait times at the call center may be longer as call center representatives must explain the varying amount of coverage options and health plan types orally over the phone. 

CMS seeks to leverage emerging AI technologies to provide personalized, claims-informed plan recommendations based on individual health needs, medications, provider preferences, and actual utilization patterns and offer real-time conversational AI support through chatbots, virtual assistants, and AI voice advisors that are available 24/7.

This would involve using predictive analytics to match beneficiaries with plans that are likely to meet their needs and translating complex plan information and Medicare documents into accessible, plain-language explanations.

On the call center front, it would automate routine call center inquiries while seamlessly escalating complex cases to human customer service representatives and enable 100% call quality assurance through AI-powered call analysis and sentiment detection.

Stressing that the RFI is not a solicitation for proposals, CMS said its goals are to identify vendors with production-ready, Medicare-specific AI/ML capabilities for healthcare decision support and call center automation and to understand the current state of commercial AI solutions for Medicare plan selection and beneficiary support.

CMS said it also wants to gather information about AI approaches to plan recommendation, conversational support, predictive analytics, and call center intelligence and learn about privacy-preserving AI techniques that are suitable for sensitive beneficiary data.

The agency also is asking solution providers to describe implementation methodology and timeline for a phased rollout strategy from pilot to national scale and the required data and integration points.