On Becker’s Healthcare Upside/Down podcast, Janus Health’s Amy Sebero and ECG Management Consultants’ Chris Ford discuss denial prevention, AI and the operational decisions that determine whether AI delivers measurable value.
Forty-two percent of health systems report deploying AI across multiple use cases. Just 4% achieved scaled implementation with measurable outcomes.¹
That gap opens a new episode of Healthcare Upside/Down, recorded live at the 2026 Becker’s Healthcare IT + RCM Conference in Chicago. Host Molly Gamm talks with Amy Sebero, 40-year revenue cycle veteran and Chief Growth Officer at Janus Healthcare, and Chris Ford, Associate Principal at ECG Management Consultants. They skip the debate over whether AI works and go to the harder part: the operational groundwork that decides whether AI ever shows up in the financials.
A few years ago, Sebero said, leaders mostly asked where AI could be used.
“Now it’s more about how can we put AI to work at scale, embed it into the way our teams are actually operating, and most importantly, how do we prove that it’s actually moving the financial needle?”
AI Can Scale a Process, But It Can’t Fix a Broken One.
Ford sees real value in reducing administrative work, from prioritizing work queues to agentic tools that can handle routine tasks such as calling a health plan. The trouble starts when AI is positioned as the entire solution.
“AI is great at scaling processes, finding those efficiencies, but it’s not going to fix poor processes.”
Sebero added a warning for systems that spent years layering point solutions onto siloed departments and now expect AI to clean up the fragmentation.
“If you’re not careful, it will actually reinforce it.”
Denial Prevention When Payers Have AI Too
Denials make the clearest test case. Health systems have invested heavily in people and technology to prevent and manage them, while payer behavior continues to change. Sebero points to another shift that revenue cycle leaders are watching closely: payers are also applying AI to their own processes.
“Payers are very effectively using AI.”
The harder question is who owns the fix. Ford’s clients often point to the revenue cycle team. He points further upstream, to registration, authorization and provider documentation, where most denials actually begin.
“While the revenue cycle certainly owns the scorecard,” he said, “we don’t own the outcomes by ourselves.”
The episode explores what that means for denial prevention, cross-functional accountability and the way health systems use denial data to understand where processes are breaking down.
Operations or AI: Which Gets in Budget First
A system with heavy denial volume and a thin margin has one pool of money, and operational redesign and AI investment both want it.
Ford offers his perspective on how health systems should sequence operational improvement and AI investment, drawing on what he has seen in organizations that continue to improve financial performance.
If you own a revenue cycle budget, that answer alone is worth the listen.
The discussion also looks at what happens to the revenue cycle leader as more transactional work becomes automated. Both guests push back on the idea that automation makes leadership less important. If anything, the role becomes more focused on performance, accountability and deciding where technology can have the greatest impact. For a broader look at how AI is changing the revenue cycle operating model, read Rethinking Revenue Cycle Strategy in the Age of AI.
Ford closes with a point that gets to the heart of the discussion:
“Not who automates the most, but who has the operational discipline combined with the technology to make it all work most effectively.”
Listen to the Full Healthcare Upside/Down Episode
Hear Amy Sebero and Chris Ford on Becker’s Healthcare Upside/Down, sponsored by ECG Management Consultants.
Sources:
¹ Giles Bruce, “11 health systems reporting measurable AI ROI,” Becker’s Hospital Review, September 11, 2026. The article cites April 2026 Qventus research based on a survey of more than 60 health system CIOs, chief AI officers, CMIOs and other senior IT leaders.