Generative and agentic AI are reshaping revenue cycle work faster than most teams can vet. The harder question isn’t whether to adopt, it’s where to invest and how to scale without breaking day-to-day operations.
In this discussion, revenue cycle and applications leaders from Penn Medicine and Stanford Health Care cut through the hype to share what’s delivering financial results.
They get specific about which use cases are ready for AI-driven autonomy and which still need a human in the loop.
You’ll hear how leading teams are:
- Driving measurable financial impact instead of chasing pilots
- Increasing output and redistributing staff to higher-value work
- Aligning revenue cycle, IT and operations around shared priorities
- Making scalable, data-driven investment decisions