Becker's Hospital Review

60 RCM LEADER AI will transform, not replace, RCM jobs By Madeline Scheetz M any hospital and health system revenue cycle leaders have pushed back on a consistent fear surrounding artificial intelligence: that it could eliminate jobs. e common thought process from executives across the country is that AI will reshape how RCM leaders conduct their jobs and not do away with them entirely. However, technology can best deliver on that promise when healthcare organizations use it as an operating model change, not a plug-and-play solution. e "set it and forget it" misconception Paul LePage, vice president of revenue cycle for Sacramento, Calif.- based UC Davis Health, told Becker's that the largest myth in RCM AI is that it functions as a "set it and forget it" solution, with the ability to automatically fix cash flow, denials and underpayments. "In reality, AI in RCM augments human expertise; it surfaces patterns in denials, prioritizes work queues and automates low-complexity tasks, but it does not replace payer strategy, contract interpretation or escalation judgment," Mr. LePage said. Mr. LePage said without ongoing governance, retraining and monitoring, the technology can work against organizations through performance degrades and increased revenue leaks. Drew von Eschenbach, vice president of enterprise revenue cycle for Seattle-based UW Medicine, echoed Mr. LePage, and told Becker's that there is no home run "turnkey solution." "ere is considerable planning, building, testing before executing and a fair amount of maintenance to ensure AI functions as design," he said. "As well as when it comes to leveraging AI that works as middleware between payer and providers, it becomes a game of pitch and catch. Both sides need to work together to be effective, and we all know that is not always the case." Denials don't start at billing Other leaders pointed to a certain misunderstanding about where AI should be deployed in the revenue cycle. Michelle Myers, senior director of revenue cycle management for Boulder Care in Portland, Ore., told Becker's that many organizations are zeroing in on the wrong end of the problem. "It is easy to think of denials as a billing issue that begins when a claim is submitted," she said. "Most denials are set in motion much earlier, oen during scheduling, intake or documentation." Ms. Myers said this is where AI can commonly be misapplied, with organizations deploying the tool to prioritize accounts receivable or automate appeals, while the main issue remains untouched. She pointed to incomplete eligibility checks, incorrect payer selection, missing prior authorization and unclear medical necessity language as culprits that can "seal a claims fate" before it's touched by billing. Instead, the real opportunity is prevention rather than immediate reaction. "By identifying patterns in payer behavior and feeding those insights back into intake workflows, authorization triggers, and documentation practices, AI becomes a front-end guardrail rather than a back-end rescue tool," she said. "Denials are not simply billing outcomes. ey are system signals, and AI is most powerful when it helps the system correct itself early." Broken processes, intensified One recurring theme amongst revenue cycle leaders was how AI can expose an organization's operational weaknesses, instead of masking them. "e biggest myth, by far, is that AI will replace clinicians," Laura Elliott, vice president of revenue cycle for Brooks Rehabilitation in Jacksonville, Fla., told Becker's. "While AI can identify patterns, predict risk and prioritize work, it cannot fix broken processes, unclear accountability, poor data integrity or weak payer strategy. AI is at its most powerful when it is paired with governance, cross- functional alignment, [key performance indicator] discipline and leadership accountability." Jennifer Armendariz, vice president of revenue cycle and managed care for Madera, Calif.-based Valley Children's Healthcare, echoed Ms. Elliot. She said that while AI can offer stronger insight into root causes at an organization, it cannot automatically resolve issues like contract and policy misalignment, payor accountability gaps, poorly designed workflows and weak governance. "AI could be an incredible catalyst to improve the entire healthcare ecosystem, but only if payers and providers are willing to engage and align incentives to drive efficiency and outcomes across the industry," Ms. Armenzariz told Becker's. Heather Dunn, senior vice president of revenue cycle for Winston- Salem, N.C.-based Novant Health, agreed, and told Becker's that an organization's success will be measured by its ability to spearhead accountability, rework decision making and zero in on strong operations. "Another misconception is that AI replaces humans," she said. "e future is human-centered intelligence, where AI amplifies judgment, operational excellence and patient experience. Organizations that succeed do not just "implement AI," they redesign how care is delivered, financed and experienced. When applied thoughtfully, the impact is very real." Ms. Dunn said Novant is already seeing strong results in certain areas through utilizing AI, like generating appeal letters for insurance denials and contributing to the recovery of millions of dollars, freeing up employees to focus on higher-value tasks. Elevate staff, don't replace them On the topic of workforce, leaders consistently highlighted how AI can shi the nature of RCM tasks toward higher-judgement ones, rather than cutting roles entirely. Keisha Downes, vice president of mid-revenue cycle for Cambridge, Mass.-based Beth Israel Lahey Health, told Becker's that the technology can help increase professional development when thoughtfully executed. "AI can be used to accelerate expertise development in novice staff by surfacing learning opportunities, flagging gaps in real time and providing a continuous feedback loop that traditional training can't

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