Agentic Healthcare: The New Operating System for Medicine

Healthcare's workflows, from prior authorization and referral chains to claims adjudication and clinical decision support, are being fundamentally rewritten by AI agents. Yet as autonomy scales, the risks shift from software bugs to critical patient safety events. A misconfigured agent acting on stale context isn't just a technical failure; it's a clinical one. This session introduces the platform layer built for healthcare that enables agents to act with speed and intelligence while remaining governed, auditable, and secure. We explore how conversational prior authorization, where decisions are resolved in real time, becomes possible only by solving the foundational challenges of identity, context, and trust.

In this session we take a pragmatic look at the real-world application of agents and AI across healthcare (for providers, payers, medtech, and life sciences) drawing on examples from both highly regulated markets and emerging digital health ecosystems globally. We explore the intersection of interoperability, standards like FHIR and HL7, agentic enablers such as MCP and context graphs, and foundational constructs like Agent ID, and how they come together to make healthcare AI safe and scalable. We anchor this in the broader regulatory momentum, from CMS-0057-F's prior authorization API mandates in the U.S. to equivalent interoperability and data-sharing directives taking shape across the EU, UK, and Asia-Pacific, and demonstrate why an healthcare native, identity-first approach with scoped context is the only way to scale autonomous AI in healthcare with confidence.