John Reynolds, CEO of the Franklin-based Bone & Joint Institute of Tennessee, told Becker’s that one of his earliest lessons in how to roll out AI platforms came at a quarterly all-staff meeting with the practice’s roughly 400 employees, where he outlined plans for growth and for using AI to support staff.
“I’m not intending to have AI platforms replace staff. I just want to enhance,” Mr. Reynolds recalled telling the group during an interview with Becker’s.
Shortly after the meeting, he learned some employees had heard the opposite.
“Fifteen minutes after the meeting was over, a doctor called me and said, ‘Oh, my staff just came back. Said you’re getting rid of them and you’re using AI to replace them.’ I’m like, ‘No, that’s not what I said,'” Mr. Reynolds said.
Mr. Reynolds, who has spent 33 years leading physician groups across the Southeast, said the episode reinforced the need to involve staff early and communicate clearly about what AI will and won’t do.
The push toward AI came from pressures familiar to most specialty groups. Payers are asking for more documentation and supporting data, reimbursement is under strain, expenses are climbing and more claims are being denied, Mr. Reynolds said. Physicians are spending more time on administrative work with each patient while trying to see more patients overall.
“Doctors are having to do more. It’s costing us more. They feel like they have to see more patients just to cover overhead,” he said.
After the all-staff meeting, Mr. Reynolds leaned harder into an approach he had always favored: involving people from across the organization from the start. He brought physicians, department managers and the frontline workers who would be expected to use the tools into the process, knowing adoption would not happen overnight.
“It’s always been my philosophy to get people in early from all walks of the practice,” he said.
The first visible win came in patient scheduling. The practice fields thousands of phone calls a day, and AI-assisted online scheduling now gives patients round-the-clock access to book appointments while easing pressure on the call center and its long hold queues. Mr. Reynolds said the practice’s high volume made scheduling the area that needed help most, and patients have largely adapted.
On the revenue cycle side, the practice uses AI for claims processing and denial management, targeting simpler, repeatable work so experienced staff can focus on more complex cases. The longer-term goal is to grow without growing headcount at the same pace.
“As we’re growing, the idea really is to use AI products to help us so that we’re not having to double in staff size,” Mr. Reynolds said.
Coding was a harder sell. Early on, some of the practice’s certified coders and providers challenged the AI’s output, and Mr. Reynolds doesn’t pretend the tools are infallible.
“We’ve had to build trust with these systems, and I tell people all the time, these platforms are not 100% correct,” he said. “So you’ve got to build trust in them, but I think the largest challenge was getting the entire team on board with it. Just the idea [of that] takes time.”
Mr. Reynolds has been championing AI internally for 18 to 24 months, and each of the practice’s platforms handles a different function. Rather than waiting for a single enterprise system, he has followed industry peers’ advice to choose vendors that do one thing well and layer them, while keeping an eye on overlap.
“The biggest thing I would say is just jump in. No systems are perfect. That’s just like when we all went to EHRs,” he said. “There’s no perfect system. You just have to find the one that works for you and do it. You may have to modify it along the way, and that’s OK.”
Jumping in only works, he said, if someone is willing to lead and bring the rest of the organization along.
“You have to get all parties aligned. From frontline employees to physicians to certainly the administrative staff, but someone has to have the vision, and someone has to be willing to promote that vision,” Mr. Reynolds said.
For him, that means experimenting openly and accepting that not every experiment will work.
“I try certain things. We may fail, but I’m OK with that. That’s how I learn,” he said. “I think it just comes down to being open-minded to it and jumping in.”
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