Hospitals are no strangers to automation. From claim scrubbers to EHR integrations, the industry has been layering in tech for decades. But now, AI agents are shifting the game entirely—offering not just automation, but real-time reasoning, adaptability, and workflow intelligence.
In an Office Hours episode, Stephanie Solich, VP, Revenue Cycle & Strategy at Infinx, shared how AI agents are being implemented across hospital revenue cycle operations to drive consistency, reduce rework, and improve financial predictability.
Tackling a Longstanding Challenge: Access to the Right Data
Ask any revenue cycle leader and they’ll tell you: getting timely, accurate data is one of the biggest hurdles in hospital operations. Multiple systems—EHRs, PMs, third-party billing tools—all need to talk to each other, but rarely do. According to Stephanie, that fragmentation has always made it difficult to keep revenue flowing smoothly.
“CFOs are expected to forecast cash flow without knowing when or how much they’ll get paid,” she said. “That’s nearly impossible when payer rules change constantly, and everything’s in a different system.”
AI agents help solve this by pulling together siloed data, applying payer-specific logic, and flagging issues before they reach billing. From prior authorization to claim submission, they bring transparency to processes that used to rely on tribal knowledge and manual effort.
A Less Tangible—but Just as Important—Benefit: Less Friction
While financial efficiency is the obvious win, Stephanie pointed out a more subtle advantage: less friction. Chasing denials, untangling payer rules, and reworking claims aren’t just time-consuming—they’re demoralizing.
“If an agent can find the issue, fix it, and move it forward, that’s huge,” she said. “It may not show up in a report, but it improves both staff satisfaction and patient experience.”
Getting Labor Efficiency Right
Hospital revenue cycle teams have always been resource-constrained. The traditional approach has been to throw more FTEs at problems like rising denial volumes or inconsistent follow-ups. AI agents flip that model.
Rather than hiring for rote tasks—like checking auth status or verifying modifier requirements—hospitals are now reallocating those roles toward exception handling and strategic work.
“The most effective approach we’ve seen is to have agents take on all the routine tasks,” Stephanie shared. “Then the human team focuses only on the outliers. Over time, the agents learn from those exceptions and improve even more.”
Why Predictability Matters More Than Ever
With labor costs climbing and reimbursement cycles growing longer, predictability is becoming a key performance metric. And it’s one area where AI agents shine.
“Humans are complex, and that’s a good thing,” Stephanie noted. “But we also have emotions, distractions, turnover. AI agents don’t. They’re consistent, 24/7 workers who don’t need to be retrained every few months.”
This level of predictability has enabled hospitals to better forecast collections, reduce cost-to-collect, and keep AR from spiraling. And since agents can also recognize and resolve common denial triggers before submission, they’re cutting down on the back-end fire drills that used to dominate staff bandwidth.
Balancing Complexity to Avoid Burnout
One insight Stephanie shared that many overlook: if AI handles all the simple tasks, the human team is left with only the hardest work. That’s not always a good thing.
“If everyone is stuck doing only the heavy lifting, it can lead to burnout,” she said. “You have to be thoughtful about the mix—give your teams a few quick wins during the day too.”
Her advice: start small, automate known wins first, and scale thoughtfully. Hospitals with limited bandwidth should look for partners who have pre-built automations, customizable workflows, and the ability to stand up AI agents without heavy IT lift.
Looking Ahead: AI as the New Standard
Stephanie compared the current moment to the early days of EHR adoption. “I used to file paper records in metal cabinets. Now that sounds crazy. In five years, we’ll feel the same way about manually checking claims or faxing auth requests.”
AI agents aren’t here to replace people. They’re here to take the burden off your teams, so they can finally focus on the work that really moves the needle.
As hospital finance teams look to do more with less—and keep up with ever-changing payer behavior—AI agents are no longer a futuristic idea. They’re fast becoming the new standard in how hospital revenue cycles run.
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