Utilization management has been digitized, but it has not yet been fully transformed. Many organizations still rely on episodic reviews, broad work queues and disconnected escalation processes-- making it difficult to identify risk early enough to change the outcome. AI creates an opportunity to move beyond simply automating existing tasks and instead redesign UM as a continuous, connected decision process.

In this session, clinical, health system, and healthcare technology leaders will examine what it takes to build an AI-enabled UM operating model that delivers results. The discussion will explore how continuous case analysis can bring together clinical evidence and payer-specific risk, deliver explainable insights at the point of action and direct limited clinical expertise toward the cases where intervention can have the greatest impact.

Using the development of Phare Utilization Management as a real-world example, the speakers will address the technical and operational considerations behind this model, including data integration, organizational calibration, human oversight, AI governance, workflow orchestration and adoption. Attendees will leave with a practical framework for evaluating whether an AI solution is merely producing another score, or meaningfully improving how decisions are made across the patient stay.