Podcast Short 2:04 September 2, 2026From Season 2, Episode 7

Why the Next Wave of RCM AI Is Predictive, Not Task-Oriented

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Christina Slemp·System Vice President of Revenue Cycle Financial Services, UNC Health
In this clip

Christina Slemp describes the arc of AI in revenue cycle: so far, organizations have used AI and RPA in task-specific, isolated ways. The next phase is interconnecting AI across every vertical from clinical to the back end, with governance on the front end and a focus on prediction. What UNC Health is moving toward is not reacting to claims that already denied but identifying what is likely to deny before claims go out, using payer behavior patterns and historical claim data. The goal is not to replace people but to give revenue cycle teams an intelligent partner that helps them work ahead of the problem. On the 5-year horizon, Slemp sees AI becoming as embedded in revenue cycle as automation is today.

Key Takeaway

The next wave of revenue cycle AI is predictive and interconnected, not task-specific. Organizations that wire AI across the full vertical and use it to stop denials before claims go out will thrive, while those treating AI as isolated point solutions will remain reactive.

“It is less about replacing people, but more about giving teams a really intelligent partner: let me help you work smarter and stay ahead of the problem so that you are not the hamster on the hamster wheel and that you are not getting frustrated.”

Christina Slemp, System Vice President of Revenue Cycle Financial Services, UNC Health

Agentic AIClaims Denial Management
From the full episode

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Christina Slemp
Season 2 · Episode 7 · 44 min

Rethinking Denials Management: AI-Driven Prediction, Sprint-Based Root Cause Resolution, and Trust as the Foundation of Revenue Cycle Change

Christina Slemp · System Vice President of Revenue Cycle Financial Services, UNC Health

Christina Slemp, System Vice President of Revenue Cycle Financial Services at UNC Health, brings a cross-systems perspective on claims denial management shaped by more than 25 years of leading revenue cycle operations across hospital systems, health plans, and payer contracting. She describes the multi-dimensional framework her teams use to approach denials, from six-week microtargeted sprint cycles with structured root cause analysis and cross-functional executive committee oversight, to the AI and RPA combination she considers best practice for automating appeals at scale. The conversation covers the organizational restructuring she guided at UNC Health, which consolidated professional and hospital billing under an enterprise AI and automation strategy, her view that predictive AI for anticipating payer behavior represents the next step beyond reactive denial management, and the emerging use of AI to analyze payer policy changes and quantify their financial impact before organizations fall behind. Christina closes with her perspective on the leadership behaviors that drive lasting change in revenue cycle, including why data alone does not move people and why trust is the only sustainable currency for change management.

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