Reimagining Healthcare Infrastructure with Agentic AI and Cloud Computing: Toward Scalable, Ethical, and Personalized Systems

Most AI in healthcare remains limited to pilots and demonstrations. This session will present a production-ready blueprint for deploying agentic AI as a safe and effective teammate in clinical care. The architecture is event-driven across EHR, imaging, devices, and claims, anchored by a provenance graph that records every transformation and decision for auditability. Agents operate under signed contracts that define scope, permitted tools, PHI access, and cost, with zero-trust validation at every call. Retrieval extends beyond standard Retrieval-Augmented Generation (RAG) to a causal framework that links evidence to effects and generates counterfactuals that clinicians can accept or reject. Compact models handle the majority of tasks, while larger models are routed selectively by policy and service level objectives. A cost governor manages token budgets and caching, and an equity budget prevents rollouts that exacerbate subgroup disparities. Human-in-the-loop review, correction, and feedback are built into continuous learning and evaluation pipelines. Attendees will leave with a clear architecture, tested safety patterns, and a practical rollout plan to improve triage, documentation, prior authorization, and follow-up—delivering workflows that are faster, more affordable, and fully auditable end-to-end.