Healthcare CIOs see AI integration as a competitive necessity

There's a significant execution gap for generative artificial intelligence in healthcare, thanks largely to electronic health record dependencies and the proliferation of third-party software integrations.

That's according to a new report from Qventus, an artificial intelligence company. Meanwhile, other recent research, sponsored by EBSCO Clinical Decisions, a developer of decision-support technologies, finds that autonomous A tools could risk patient trust.

WHY IT MATTERS
The Qventus report, "Beyond the Pilot: How CIOs are Operationalizing AI across Health Systems in 2026," released Thursday, aims to document the shift from AI pilots to full-scale AI integration within large-scale health systems.

Researchers on behalf of Qventus surveyed and interviewed more than 60 senior healthcare IT leaders, including chief information officers, chief AI officers, chief medical information officers and other senior IT leaders at medium and large national health systems for the study.

A quarter of these respondents reported that they lacked a clear process for benchmarking AI performance, while 42% said their organizations were actively deploying AI across multiple use cases. Only 4% said that they have scaled AI implementation with measurable outcomes, while 45% cited "difficulty scaling pilots."

Further, EHR vendor dependency – cited as a top execution barrier by 74% of respondents – may be slowing progress on AI. In addition to waiting on AI feature rollouts, respondents said that managing multiple third-party AI implementations created its own bottleneck.

The way healthcare leaders measure success is also changing. 

They are looking at tangible outcomes like revenue generation (62%) and hard dollar cost savings (59%). Half said agentic and automated care platforms that handle scheduling, patient flow and care gaps tasks with minimal human intervention hold the potential for higher returns.

Dr. Deepti Pandita, CMIO and CAIO at UCI Health, said that governance is evolving to allow for this shift. 

"Today's governance is still human-in-the-loop, but tomorrow's may not include human-in-the-loop with advancements in autonomous AI," said Pandita in the Qventus report. 

The costs of inaction on AI will also be high, according to the research. 

Delaying AI deployment creates a competitive disadvantage, according to 94% of the healthcare leaders surveyed. It will also worsen clinician burnout, 68% said.

Compounding these technical challenges, federal spending cuts, workforce shortages and the number of Americans aged 65 or older, estimated to increase by 42% by 2050, will press the healthcare system.

"2040 may look worse than 1940 in terms of relative deprivation of access," Dr. Joseph Sanford, associate vice chancellor and chief clinical informatics officer at the University of Arkansas for Medical Sciences, said in the report. "And we need to solve for that."

Thus, health leaders are increasingly looking at unified platforms that can handle multiple AI use cases. 

The majority of clinicians trust evidence-based AI tools, according to a separate report, "Clinician-Patient Trust Dynamic in the Era of AI-Powered Clinical Decision Support," shared with Healthcare IT News. 

Of the 1,000 clinicians surveyed this past December for the study by EBSCO, most said that they saw the adoption of AI-powered clinical decision support (CDS) as a standard fixture in modern medicine, with the majority using such tools multiple times per patient encounter. 

However, the researchers also surveyed 1,000 U.S. health consumers. 

While 89% of clinicians said AI-driven CDS leads to better patient outcomes, 64% of consumers would still prefer to see a professional who does not use AI at all.

THE LARGER TREND
Health systems can transition from small-scale AI pilots to high-speed, unified rollouts that meaningfully improve patient outcomes, according to a presentation last month at HIMSS26.

"There aren't many case studies that have been actually published that we can all reflect on, certainly at a scale that Sutter Health has deployed, where you can point to the real value of AI, the benefits, the learnings," said Dr. Jason Wiesner, chair of the health system's imaging service line. 

By maintaining three key guardrails, validating efficacy using the health system's own real-world data and patient population and using a common AI infrastructure, Sutter Health moved beyond an AI pilot to enterprisewide implementations.

"You can't integrate with 10, 15, 20 different point solution companies, separate vendors, and integrate them into your health system in a scalable and safe way," Wiesner said.

ON THE RECORD
"If you make a wrong bet on a technology, you can blow your entire margins," Dr. James Whitfill, chief transformation officer at HonorHealth, said in the Qventus report. "Healthcare makes grocery stores look like they have excellent margins."