As health systems accelerate artificial intelligence adoption, many are finding that the hardest work is not launching pilots, but deciding which ones deserve to move forward and which should stop.
At Cincinnati-based Christ Hospital Health Network, leaders deliberately chose to embed AI pilots and proof-of-concept work into the system’s enterprise governance structure rather than treating AI as a standalone innovation effort. The approach has helped the organization reduce noise, prioritize initiatives more clearly and normalize early exits from projects that fail to deliver value.
Joy Oh, chief information and digital transformation officer at Christ Hospital Health Network, began shaping the strategy when she joined the organization a bit over a year ago.
“When I first arrived, everybody was trying to do everything at once. There was always this shiny new technology that was going to change the world and cure cancer and also find your missing socks,” said Ms. Oh. “The team was just always scrambling and trying to do something, and then products would be put into the environment and maybe deliver less than stellar results.”
That pace created churn and growing technology debt, with limited follow-through on whether initiatives ultimately worked. Instead of adding more tools or standing up a separate innovation function, Christ Hospital leaders stepped back to focus on how decisions were being made. They revised the governance process to prioritize the work they’re doing aligned with strategic goals of the organization and delivering measurable, tangible return on investment.
The ROI wasn’t always hard dollars, but sometimes aligned with patient satisfaction or staff experience goals. The governance model now serves as a single front door for digital, technology and AI initiatives. Leaders must articulate expected outcomes before work begins and return after implementation to assess whether those outcomes were achieved, a step that is often missing in healthcare technology deployments.
“Because I think, honestly, that’s the hardest part. It’s easy to say a project’s going to deliver $3 million in value, but how often are we going back six months later, a year later to say, OK, did they really deliver?” she said.
As interest in AI accelerated, Christ Hospital resisted creating a parallel approval track. Instead, AI review and risk assessment were embedded into the same governance structure, with particular attention to patient-facing use cases.
“Because we didn’t want to have multiple prioritization initiatives running through our organization, but the AI being newer, we were trying to understand how do you prioritize AI and how do you manage the risk of AI, especially in the context of patient care?” she said.
A defining feature of the model is the way pilots and proof-of-concept work are handled. Rather than isolating innovation from operations, Christ Hospital embedded pilots directly into governance, ensuring operational leaders remain involved from the start and share responsibility for outcomes.
That structure has made it easier to stop projects and shifted that decision away from IT alone. The CIO and IT leaders aren’t the ones saying “no” to projects anymore; instead it’s the operational leaders who are critically thinking about the ROI and value of the input versus output and deciding whether to move forward.
“That’s been really satisfying,” said Ms. Oh.
The same discipline now shapes Christ Hospital’s AI strategy. The system typically has multiple AI initiatives in pilot mode at any given time, with the expectation that many will not scale. Some pilots have delivered clear clinical value, while others have surfaced safety or accuracy concerns that prompted leaders to move on quickly.
One project the health system worked on was using AI to draft patient responses to patient queries. The results were “not great,” Ms. Oh said. The AI at times recommended drugs that were no longer FDA approved or had other issues, and gave incorrect medical advice.
“It wasn’t speaking on behalf of the doctor even though the AI was prompted that they were supposed to be drafting it on behalf of the provider,” she said. “We learned very quickly that these kinds of patient interactions, especially when there’s a message from a patient that could have multiple questions in it as well as statements and concerns, in a field as complicated as healthcare and medicine, the AI really struggled.”
Those experiences reinforced a core lesson for the organization: technology alone does not create value without redesigned workflows and operational ownership. Christ Hospital’s leadership team now views governance not as a brake on innovation, but as an enabler, helping the system move faster by focusing attention where it matters most.
As financial pressure, workforce constraints and AI hype continue to collide across healthcare, Christ Hospital’s approach reflects a broader shift among health systems toward more disciplined, outcomes-driven technology adoption and greater comfort saying no.
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.