Most health systems have governance in place and pilots running — but only 4% have scaled AI with measurable outcomes. Our second annual CIO report, based on a survey and 1:1 interviews with more than 60 health system technology leaders, reveals what’s driving that gap and what it actually takes to close it.
The pressure to operationalize AI has never been higher.
65% of health system technology leaders rate that pressure at 7 or higher on a 10-point scale. Razor-thin margins, a worsening workforce crisis, and sweeping cuts to federal healthcare funding mean the cost of waiting is no longer abstract. 94% of leaders say delays in operationalizing AI would put their organization at a competitive disadvantage — and 77% say even a one-to-two year delay would mean meaningful lost savings and efficiency gains.
The full report includes detailed findings on EHR dependency, agentic AI adoption, vendor consolidation strategies, and five concrete recommendations for CIOs navigating these decisions in 2026.
"The decisions we're making about AI right now are among the most consequential we've faced — and the margin for error is razor thin. Getting the strategy wrong doesn't just slow you down, it can set you back in ways that are hard to recover from."
Jim Whitfill, MD
SVP & Chief Transformation Officer, HonorHealth
“You may have one specific, compelling solution — that's not what we're looking for. We're looking for things that have enterprise impact — a partnership that is collaborative and long term.”
Matthew Anderson, MD
Chief Medical Information Officer, HonorHealth
“In 2025 we put a lot of functional tools out the door. 2026 builds on that by improving user experience and expertise.”
Joseph Sanford, MD
Associate Vice Chancellor and Chief Clinical Informatics Officer, UAMS
Beyond the Pilot is Qventus’ second annual report on how health system technology leaders are adopting and scaling AI. The findings are based on a survey and 1:1 interviews with more than 60 CIOs, Chief AI Officers, CMIOs, and other senior IT leaders at medium and large U.S. health systems. The research covers AI operationalization strategies, ROI measurement, EHR dependency, vendor consolidation, and agentic AI adoption.