Where AI Goes Next: Rethinking Revenue Cycle Work
Not every revenue cycle workflow needs artificial intelligence, and applying it where rules-based automation already works can add unnecessary cost and complexity. This webinar explains how healthcare finance and revenue cycle leaders can determine which work is best suited for traditional automation, agentic AI, or human expertise. Presenters will examine how to identify appropriate use cases, design effective handoffs and oversight, measure operational and financial value, prepare teams for changing responsibilities, and establish the controls and evidence needed to expand AI responsibly.
Learning Objectives:
- Differentiate rules-based automation, agentic artificial intelligence, and human expertise based on the revenue cycle work each is best suited to perform
- Identify workflows where variability, exceptions, incomplete information, or multi-step reasoning may justify an agentic approach
- Define the respective roles of technology and revenue cycle professionals within an artificial intelligence-enabled operating model
- Evaluate potential use cases based on operational value, cost, risk, measurability, and organizational readiness
- Determine the measures, controls, and evidence needed to expand an artificial intelligence-enabled workflow responsibly
Presenters
Sanjay Kumar
Chief Technology Officer
XiFin, Inc.
Rob Carfogno
VP, Radiology Operations
XiFin, Inc.
