Health systems are not carving out separate AI budgets. Instead, CIOs told Becker’s AI is being absorbed into existing IT and operational spending and evaluated alongside other enterprise technology investments.
At Columbus-based Ohio State University Wexner Medical Center, that integration is intentional.
“We don’t have separate funding and governance streams for AI-specific decisions,” CIO Tom Bentley, BSN, RN, told Becker’s. “We really try to consider them in the full context of the technical solutions that we’re looking at, not just AI versus non-AI.”
That approach is not isolated. Across health systems, a consistent pattern is emerging: AI is not being treated as a discrete category of spend.
At University Hospitals in Cleveland, CIO Robert Eardley describes a similar model, in which AI is folded into enterprise IT and subjected to the same financial scrutiny as any other investment.
“Most AI-related costs are defined at the enterprise level and are part of our overall corporate IT expenses,” Mr. Eardley told Becker’s. “Each of these AI costs is part of a broader business case that gets reviewed before implementation.”
At Sacramento, Calif.-based Sutter Health, AI is likewise embedded within a broader digital budget — but with an added layer of structured oversight.
“We take a structured approach to AI governance. We register and assess each solution and align it with an appropriate monitoring strategy to support performance, safety and meaningful impact for employees, clinicians and patients,” Chief AI Officer Ashley Beecy, MD, told Becker’s.
But embedding AI into traditional budget structures creates a new challenge: CIOs are effectively operating with two different ROI models.
For AI revenue cycle use cases, the math is relatively straightforward.
“If it’s a revenue cycle-related ROI, it can be pretty cut and dry,” Mr. Bentley said. “It’s narrowly focused. It can save us a certain amount of money at a certain time.”
That model, however, breaks down quickly in clinical environments. When the goal shifts to reducing administrative burden, improving patient experience or making clinicians more efficient, traditional financial metrics become harder to apply.
“That ROI from a dollar perspective gets a lot harder to measure,” Mr. Bentley said. “Our true north is high-quality care and making it an efficient environment for caregivers to work in. If we feel that a solution can improve those elements, then that would be viewed as the business case for us.”
That notion is pushing some leaders to expand how value is defined.
“As healthcare organizations evaluate AI, it is important to look beyond traditional ROI alone,” Dr. Beecy said. “Value can also be measured in time returned to clinicians and staff, reduced administrative burden and cognitive load, improved professional satisfaction and a better overall experience for patients.”
At the same time, financial discipline has not disappeared. At University Hospitals, AI investments are still expected to demonstrate clear returns.
“In general, most have positive ROI within a three-year time frame,” Mr. Eardley said. “Given the nature of many of these, they can almost offer immediate return once enabled and scaled out for deployment.”
In many cases, that expected return is built directly into how projects are funded.
“Most AI initiatives are funded based upon the payback outlined in the ROI during the business case generation,” he said. “Therefore, these dollars are self-funding.”
That combination — embedded budgets and evolving ROI definitions — is also reshaping how CIOs make vendor decisions. Increasingly, the question is not just what an AI tool can do, but whether it fits into a scalable, supportable platform strategy.
At Ohio State, that has led to a deliberate pullback from standalone point solutions.
“There’s a lot of really innovative tools out there,” Mr. Bentley said. “But what we’re trying to consider is what is the long-term impact of trying to maintain that tool? What is the cybersecurity footprint over time if you add a lot of individual point solutions? What’s the supportability over time?”
The trade-off, he noted, is becoming clearer over time.
“You might get a little bit of a win with some early innovation, but can you really maintain that over the long haul?” he said.
That calculus is increasingly influencing long-term vendor alignment.
“It’ll really drive what partners we want to align with: Do they have platforms that are effectively leveraging AI?” Mr. Bentley said. “Those are the vendors we’re going to want to partner with.”
But that platform-first strategy is not absolute. At University Hospitals, for example, most AI spending sits at the enterprise level, but imaging AI tools in radiology are funded directly within the service line. The exception reflects both the maturity of radiology AI and the reality that not all use cases fit neatly into a single budget.
Budget structure and ROI thresholds shape how AI investments are evaluated, but they do not determine whether those investments succeed. Governance does.
“Organizations with mature AI governance are more than twice as likely to successfully scale AI and realize its value across the health system,” Dr. Beecy said. “Without that foundation, initiatives often remain siloed and may lack the oversight needed to support its responsible use.”
At Sutter, that governance model is deliberately multidisciplinary.
“Our core AI governance council brings together leaders from legal, compliance, regulatory and digital functions and works closely with experts across the system, including clinical leadership and research,” she said.
At University Hospitals, executive oversight is similarly embedded into the investment process.
“Technology-enabled investments are handled through a business case review process with our C-suite leaders, COO, chief strategy officer and CFO, analyzing the benefits and discussing the costs,” Mr. Eardley said. “AI-related investments get the same type of review as any other technology-related investment.”
Across these organizations, a consistent direction is emerging. AI is becoming a permanent part of the cost structure — one that CIOs are expected to justify not only through financial return, but through measurable improvements in operations, workforce efficiency and clinical performance.
“Clearly, these tools will accelerate spending as the maturity and adoption of these features continues to grow,” Mr. Eardley said. “But as with any investment, the benefits delivered need to offset any new costs.”
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