The AI vendor market has never looked like this. Health system CIOs are fielding pitches from dozens of startups on a regular basis, many genuinely capable but most unproven at enterprise scale, and the pressure to act is high while the tools for evaluating these companies remain limited.
Maria Sexton, senior vice president and CIO at University of Tennessee Medical Center in Knoxville, Tenn., has been navigating vendor decisions for three decades across industries ranging from hospitality and gaming to the federal government. She said the current AI cycle is moving faster than any technology shift she has encountered.
“We talked about cloud a few years ago and other innovative technologies, and this one is just unbelievable how fast it’s moving,” she said in a recent “Becker’s Healthcare Podcast” interview.
The issue is not whether AI tools can perform in a pilot; it is whether the company behind the tool will still be operating when a health system needs it most. Ms. Sexton is focused on rapid experimentation to keep the initial investment of time, money and people deliberately small, and then build an exit into the strategy from the start.
“Can we try things with a minimum amount of investment of money, time, and people, and see if they pay off?” she said. “And if they don’t, we move them back and try something else.”
The approach manages the downside risk but it doesn’t resolve the underlying issue with unproven companies and brand new startups that have to begin somewhere. In those situations, Ms. Sexton takes a calculated gamble, digging deep into the question of whether the technology has “stickability.”
Getting closer to an answer has required a willingness to act on incomplete information in a market with no established track record.
“That’s really new, for technology leaders, for CIOs to have almost a little bit of a leap of faith,” she said.
Ms. Sexton relies on her network for peer intelligence to reduce the uncertainty. She reaches out to CIO counterparts across the industry, shares what UT Medical is learning in real time, and vets startup relationships through those conversations. She’s seeing that a broader shift toward openness among IT leaders has made this kind of information-sharing possible.
Her team also asks startups direct questions, including about other organizations they are working with, and follows up on those claims independently. When enough peers have compared notes on the same vendor and arrived at similar conclusions, that consensus carries weight that no single evaluation can produce on its own. But it is not a bulletproof process.
“We don’t have it figured out here. I don’t know others that have it really figured out either,” she said.
What the approach produces is shared accountability rather than certainty. The vetting happens in conversation with peers, the decisions are made collectively and then the industry learns from all outcomes.
“We’ve done it together with eyes sort of wide open,” she said.
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