Health systems invest years of effort and hundreds of millions of dollars to implement electronic health records. Yet, despite this enormous commitment, a large share of that investment stays untapped. Two healthcare CIOs now argue this gap is not just a wasted expense. It may be the most critical factor shaping how ready a health system is for artificial intelligence.
The EHR Utilization Gap
Most Systems Use Only 60% of EHR Features
Muhammad Siddiqui, CIO of Reid Health in Richmond, Indiana, estimates that most health systems actively use just 60% to 70% of their EHR’s full capability. Importantly, this figure goes beyond a single metric. It reflects what features are switched on, what staff genuinely adopt in daily workflows, how consistently those workflows run as designed, and how much manual work still happens outside the system.
“There is a real difference between owning functionality and realizing value from it,” Siddiqui told Becker’s.
Michael Archuleta, CIO of Mt. San Rafael Hospital and Clinics in Trinidad, Colorado, places operational maturity at a similar level. He points to what he calls the central misconception in healthcare IT.
“Buying an EHR does not mean you are capturing its value,” Archuleta said. “The gap is not usually access to technology. The gap is optimization.”
What 60% Usage Really Means
Live Features vs. Genuine Clinical Adoption
Many health leaders confuse technical activation with real-world adoption. A feature being switched on is not the same as clinicians using it effectively. Archuleta draws a clear line between these two states.
If a capability is live but clinicians bypass it, if workflows still feel fragmented, or if documentation burdens remain unchanged, then organizations have not truly realized value from that tool. Moreover, the EHR is rarely the problem. As Siddiqui explains, the barrier is usually internal.
“Health systems have not had the time, operational discipline, governance, or change capacity to fully standardize what is already there,” he said. “Local exceptions, legacy habits, and competing priorities all slow that work down.”
Categories of Underused EHR Capability
Where the Gaps Are Hiding
Both leaders point to similar areas where EHR value goes unrealized. These include advanced clinical decision support, workflow automation, scheduling and access tools, patient engagement and self-service features, interoperability functions, and analytics. Each of these represents a meaningful opportunity. Together, they represent a significant gap between investment and return.
Why the Gap Persists
Competing Priorities Block Optimization Work
Health systems do not ignore EHR optimization out of negligence. Instead, they face a crushing set of simultaneous demands. Staffing shortages, cybersecurity threats, regulatory obligations, financial pressures, platform upgrades, and daily patient care all compete for attention. Consequently, optimization work rarely rises to the top of the priority list.
“Optimization work rarely feels urgent in the moment, which is exactly why it gets delayed,” Archuleta said. “Over time, organizations normalize inefficiency while sitting on platforms capable of much more.”
The AI Readiness Risk
Fragmented Workflows Undermine AI Investments
The stakes grow even higher when artificial intelligence enters the picture. Both Siddiqui and Archuleta warn that deploying AI on top of poorly optimized EHR environments creates new risks rather than solutions.
“AI can be useful,” Siddiqui said. “But if the underlying workflow is fragmented, AI often just helps you move faster through the mess.”
Archuleta goes further. Inconsistent documentation practices, weak governance, and low platform adoption do not disappear when AI arrives. Instead, AI scales those problems.
“Adding AI on top of that environment simply accelerates the underlying problems,” he said. Furthermore, the organizations best positioned to lead in AI are not necessarily the fastest movers. They are the ones that have already optimized workflows, strengthened governance, improved adoption, and built trust in their data.
Optimization as Strategic Infrastructure
EHR Optimization Is AI Preparation
Both leaders reframe EHR optimization as something far more significant than routine maintenance. It is strategic infrastructure. Specifically, it is the most important AI preparation work a health system can do right now.
“Maximizing the value of your EHR is not maintenance work,” Archuleta said. “It is strategic infrastructure.” Health systems that do this foundational work well position themselves to extract genuine value from AI. Those that skip it risk adding another costly layer on top of existing friction.
In short, the path to successful AI adoption runs directly through EHR optimization. Health systems that treat these as separate priorities do so at their own risk.
