Why clinicians walk away from AI tools they don't trust
When clinicians don’t trust clinical decision-support tools, they don’t just ignore them. They spend extra time verifying and correcting AI-generated recommendations undermining productivity and compromising the very quality-of-care gains these tools are meant to deliver.
At Becker's 16th Annual Meeting, clinical and digital leaders from University of Rochester Medical Center, Hackensack Meridian Jersey Shore University Medical Center, Bon Secours Mercy Health and Johns Hopkins unpacked why so many AI pilots stall and what separates the tools clinicians actually adopt
This report breaks down what these leaders learned:
At Becker's 16th Annual Meeting, clinical and digital leaders from University of Rochester Medical Center, Hackensack Meridian Jersey Shore University Medical Center, Bon Secours Mercy Health and Johns Hopkins unpacked why so many AI pilots stall and what separates the tools clinicians actually adopt
This report breaks down what these leaders learned:
- How "gray work" and alert fatigue quietly erode trust and ROI
- The governance structures that vet AI tools before they reach clinicians
- Why workflow fit determines whether a tool is adopted or ignored
- How to define success, set benchmarks and measure clinical impact
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