Health systems are fielding more requests for AI than ever, but ask their technology leaders which department is generating the loudest demand, and the answer has less to do with the function itself than with how ready that team already is to use it.
At Chicago-based Rush University System for Health, revenue cycle and supply chain outpace every other department because of the foundation they’re built on.
“A lot of other departments might make requests, but their data is unstructured, their processes aren’t standardized, the leadership doesn’t really understand, doesn’t think technology first when they think about their business, and in rev cycle and supply chain, they do,” said Jeff Gautney, senior vice president and CIO.
Radiology and cardiology show the same pattern on the clinical side, he said. “Those are areas where there are pretty good protocols that have been FDA-approved that you can implement, and you’ve got a bunch of clinicians that always think technology first,” Mr. Gautney said.
Much of the demand from revenue cycle is also coming from the top down rather than from IT. Rush’s revenue cycle chief, who took over the department about a year ago, pushed his team to look for AI-driven fixes to the threats and opportunities he inherited before IT proposed anything, Mr. Gautney said.
“He really took a hard look at where his threats were and where his opportunities were, and then has been a great partner in going out and looking for, first, can I do this with Epic or Experian — which are our two big pillar partners in rev cycle — and if not, what’s the best available point solution I can stick in there,” Mr. Gautney said.
One result: automating the abstracting process for a clinical registry let Rush eliminate an outsourced vendor that cost nearly $1 million a year, Mr. Gautney said, calling it an easy business case to justify. Supply chain has followed a similarly disciplined path, he said.
“They are very methodical about where AI can help, and not just looking for sort of a bag of magic beans,” Mr. Gautney said, “hoping that’ll be a beanstalk.”
At New York City-based Hospital for Special Surgery, the most AI asks come not from a department, but clinicians themselves.
“For years, healthcare IT has been pushing technology out to clinicians,” said Ashis Barad, MD, executive vice president and chief digital and technology officer. “Now our doctors and frontline teams are pulling. This is a seismic shift and I hope it’s a sign of regaining trust,” he said.
To keep pace with that demand without slowing down good ideas, the organization built an internal intake tool it calls Agora.
“Anyone at HSS can submit a request or idea, refine it with an agent, and have it routed to the right team. That gives us a practical way to prioritize the growing demand without slowing down good ideas,” Dr. Barad said.
At Minneapolis-based Allina Health, human resources leads the way.
“We’re seeing a combination of requests for additional ERP [enterprise resource planning] automations but also HR team member access to advanced gen AI models and agentic tools,” said David Ingham, DO, chief digital and information officer. “I’m finding HR to be remarkably AI-forward in their thinking and approach.”
That marks a shift from where the excitement was concentrated even a year ago, when much of the momentum centered on generative AI embedded directly in the EHR to draft clinical messages and notes. Dr. Ingham said the results there have disappointed many clinicians, whose preferred tone the tools couldn’t match.
“Feedback has been mixed at best, with most clinicians disappointed at the one-size-fits-all ‘voice’ that the AI is using, particularly when drafting medical message responses,” he said. “The EHR drafts are all the same personality and style which really limits usefulness.”
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