A Strategic Look at What's Driving CMIO Decision Making
In this session, you'll hear what leading health system Chief Medical Information Officers discussed during our Spring 2026 in-person gathering in Carlsbad, CA — and we'll share our perspective on the key themes and what they mean for industry organizations that work with them.
Below are key takeaways from our in-person forum with Health System Chief Medical Information Officers, offering insights on their top-of-mind issues.
Key Themes Discussed
Precision medicine as a scale problem, not an interest problem: Why pilots "just don't work" — never large enough to matter, dependent on extraordinary measures, nearly impossible to measure — and why the near-term constraint is a financial and operating model, not clinical appetite
AI investment outpacing ROI accountability: Why failing tools rarely get retired, why operational AI (call center, supply chain) outperforms clinical AI yet stays underdeployed, and why informatics can't carry ROI accountability it was never resourced for
AI governance that extends beyond the approval decision: Why the harder work starts after a tool is live — inventorying what's already deployed, governing AI features that reach clinicians before organizational consent, and catching back-end model changes before clinicians do
The CMIO role expanding faster than its operating model: How accountability is being added faster than authority, staffing, or succession pathways are being redesigned — and why clinical informatics still has to prove its value every year
EHR governance debt compounding under AI: Why go-lives are the starting line, not the finish line, and why layering AI on top of ungoverned content makes years of deferred cleanup harder to ignore
"Your worst AI use case has a ~0% chance of being killed. Of 23 negative-ROI deployments, 74% are slated for increased investment. The typical AI portfolio only grows."
By the numbers: 82% of health systems are in early awareness or narrow pilots on precision medicine — none reported systematic integration into standard care. Of 23 AI deployments with confirmed negative ROI, 74% are slated for increased investment. Call center and supply chain AI show the strongest returns (67% and 43% positive ROI) yet remain underdeployed relative to clinical AI. One governance inventory surfaced more than 90 AI-enabled applications, some deployed outside informatics visibility. 83% of CMIOs report expanded accountability, while 43% describe their teams as under-resourced or strained. And 75% of health systems have been live on their current EHR for six years or more — plenty of time for governance debt to accumulate.
Why This Matters for Industry
For industry partners, these conversations reveal a buying environment defined by a credibility gap: AI portfolios that only grow, ROI that's rarely proven, and informatics teams carrying accountability they weren't resourced for. That's an opening for partners who show up differently — with hard ROI methodology that lets informatics keep credit for the value, deployment paths that don't add to a strained team's workload, and honesty about what should be decommissioned, not just what should be bought. Understanding the governance maturity gap, the operational-versus-clinical ROI divide, and the EHR foundation issues underneath every AI conversation is essential context for how you position your outreach and frame the value of your solutions.