How To Measure Healthcare AI ROI

Why Rapid AI Adoption Doesn’t Guarantee Immediate Returns in Clinical Settings 

Even when AI produces real gains, proving a direct financial return in the short term can be difficult. 

“Clinical outcomes — such as reduced readmissions, earlier diagnoses and lower mortality — play out over long horizons and require enough patient volume to be statistically meaningful,” explains Atif Chaughtai, global vice president of strategic ecosystem sales at Strategy.  

Chaughtai points out that when AI reduces the time a provider spends on paperwork, that only translates into a financial return if it’s converted into more visits or less overtime. “Relief from burnout is valuable, but it rarely appears as a line item,” he says.

Whether workers actually adopt the technology is another critical factor impacting ROI. If physicians and other providers weren’t included in discussions about which AI tools would be most helpful, for instance, and a new platform doesn’t integrate well with existing workflows or causes alert fatigue, then workers might not use it.

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How Healthcare Leaders Should Calculate AI ROI

A strong data governance infrastructure is vital for tracking data over time to prove healthcare AI ROI. Establishing a baseline before deployment will help IT and medical leaders demonstrate how an AI tool is creating a benefit over months and years.

In the short to mid-term, leading indicators — such as documentation time per encounter, error rates, after-hours charting and clinician adoption — “let us judge whether an investment is on track early and decide whether to scale it,” says Chaughtai, explaining that true ROI then comes from monitoring lagging outcomes, such as cost per patient case and worker retention.

Healthcare leaders can also move beyond financial ROI to demonstrate AI benefits for both the organization and the communities it serves. Alex Sushko, an account executive for regulated industries at Glean who specializes in AI integration, suggests connecting AI use cases with the health system’s stated goals.

“Map every AI use case to a goal,” he says. “For instance, how can we use AI to better monitor heart failure patients so they don’t end up in the emergency room? Measuring ROI by hours saved or costs cut is important, but why are you taking these steps? What is it all leading to? Tie ROI into the hospital’s overall mission.”

Promising Tools for Healthcare AI Investment 

AI tools that support revenue cycle automation, documentation and security can have a tangible, positive financial impact. Here are a few examples of how healthcare organizations can achieve measurable AI ROI:

• AI systems that help investigate and appeal denied insurance claims can drive substantial revenue growth, given that fewer than 1% of denials are appealed despite more than 80% of prior authorization appeals succeeding. 
• “St. Luke’s University Health Network uses Microsoft Security Copilot agents to speed up phishing alert triage and generate incident reports in minutes instead of hours, saving nearly 200 hours per month,” Harper says.
• Sushko notes that after deploying Glean across the organization, providers at DaVita Kidney Care reported 108 million minutes saved and more face-to-face time with patients. 
• Chaughtai points to a health insurer that’s using AI to help generate quotes for employer groups: “Speed matters commercially because the carrier that responds first with an accurate quote is better positioned to win the business.”  

How To Present AI ROI to Healthcare Boards and Stakeholders

When proposing an AI investment to your organization’s boards and stakeholders, “lead with understanding the business problem you are trying to solve and the outcomes you’re looking for,” advises Chaughtai. “AI is a tool that can then be applied to solve the problem.”

Addressing how long-term cost savings from AI could be reinvested into the organization is another strategy. For example, AI tools may help reduce hospital-acquired infections, which the CDC says cost U.S. hospitals billions of dollars each year. “When you optimize patient care, improve safety and automate such things as onboarding,” Sushko says, “those savings can support growth, such as opening new research centers, creating new lines of service or accepting more medical students.” 

Harper says IT and medical teams should be prepared to answer questions about the value the AI tool may create, the potential risks posed by the technology and how exactly success will be measured. He adds that framing how AI will play a major role in healthcare financial sustainability is another point to emphasize, especially as organizations manage ongoing workforce shortages and rising demand.

“The organizations that realize the greatest long-term benefit are typically those that use AI to augment their workforce and redesign processes rather than simply automating isolated tasks,” Harper says. “Ultimately, AI ROI should reflect cost savings and improved financial integrity alongside improvements in care quality, workforce sustainability and patient outcomes.”