HFMA Rev Cycle Conference 2026
Arlington, TX: More than 500 attendees gathered at the Arlington Convention Center in Arlington, Texas this week for the annual Revenue Cycle Conference hosted by the Healthcare Financial Management Association. The conference draws senior revenue cycle leaders at hospital health systems across the U.S., as well as revenue cycle technology and services vendors eager to pitch their solutions to health system attendees.
Panels featured insights from senior leaders acknowledged as transformative leaders in healthcare revenue cycle operations strategy; breakout sessions targeted more niche topics in areas like rural healthcare access; and keynotes included a moderated conversation with healthcare industry experts and observers.
Here’s three top takeaways from the event:
1. Conversations about AI dominated conference programming.
Organizers dedicated a pre-conference workshop to AI applications in RCM, while the afternoon keynote address on Thursday bore the title “Why AI is the first smash hit for revenue cycle.”
“It’s the big buzz,” I overheard one attendee tell another as they prepared to depart. “It’s all ‘AI this’ and ‘AI that.’” Her voice contained equal parts frustration and wonder.
The buzzing from vendors and event programmers was certainly loud. Yet while attendees seemed more or less convinced that AI was sure to bring changes to healthcare revenue cycle management, the jury was still out on just what that might look like in practice.
One thing, however, seemed certain: On the provider side, AI had already proven itself in the realm of provider dictation tools for clinical documentation generation, a fact that may be responsible for the reduction in burnout rates since the 2021 pandemic-era peak.
Speakers and attendees expected additional efficiencies to emerge for RCM teams across the revenue cycle, but seemed to agree that no clear winners had emerged.
2. Payers are winning the AI race—for now.
During a keynote conversation, Christina Farr of Manatt Health observed that payers are raking in the lion’s share of private investment cash for technology development in the healthcare sector. Providers have noticed the results of these investments in the form of elevated denial rates, which Farr attributed to AI technologies that have increased the frequency of automated payer denials.
Larger provider organizations have also begun to experiment with AI-powered denial management software, resulting in what many have called a “battle of the bots.” Such a battle, Farr noted, may be an improved state of affairs for RCM teams who can afford the tech: Humans appealing claims will eventually give up, she said, but bots have endless patience to continue pressing claims against payer bots that will just as aggressively find ways to continue denying them.
The horizon of such a battle, she noted, can only be stalemate. Payers will continue to have the advantage, she predicted, but the principal loser in the battle of the bots would be a healthcare system that can’t find a better way to resolve this friction.
3. AI advances will require new skillsets in revenue cycle management.
As HFMA’s Director of Perspective and Analysis Shawn Stack said from the stage, “Skillsets in revenue cycle are changing.” Stack went on to elaborate that rank and file coding and billing team members would no longer be functioning like “assembly line workers,” because many of the tasks they perform today will be automated in the near future. Instead, he said, “we’ll likely see RCM teams operating with less staff, at a higher level.”
His remarks reminded me of a comment I’d heard earlier that day from a RCM leader at a large health system based in Texas. Coders understandably fear their jobs will be replaced by AI, she told me, and are resisting new technologies. But that’s only because they can’t quite yet imagine what kind of jobs their skills will equip them to do. Instead of poring over records and completing rote reviews, she said, “They’ll get to operate at the top of their license.”
At Chata, we believe the same thing: When AI reviews 100% of your charts for coding accuracy, payer compliance, and clinical documentation integrity, your RCM staff can take on the higher-order work of handling exceptions, performing human-in-the-loop review of edge cases, and translating chart review data into process improvements that increase revenue performance and improve care delivery.