The implementation gap: Bridging AI promises and healthcare realities
Imagine AI tools that clinicians trust, workflows that actually improve care and governance that supports scale instead of slowing it down.
For many health systems, the reality looks different. AI pilots stall. Clinicians push back. Value is hard to quantify. Leaders are left wondering why promising technology fails to translate into everyday practice.
Based on a Becker's CEO + CFO Roundtable discussion, this report features insights from Northwestern Medicine, University of Iowa Health Care, SSM Health and Anumana.ai. Panelists explained why medical-grade AI demands a higher evidentiary bar, how governance and transparency shape adoption and why workflow integration determines success more than novelty.
Inside, readers will learn:
For many health systems, the reality looks different. AI pilots stall. Clinicians push back. Value is hard to quantify. Leaders are left wondering why promising technology fails to translate into everyday practice.
Based on a Becker's CEO + CFO Roundtable discussion, this report features insights from Northwestern Medicine, University of Iowa Health Care, SSM Health and Anumana.ai. Panelists explained why medical-grade AI demands a higher evidentiary bar, how governance and transparency shape adoption and why workflow integration determines success more than novelty.
Inside, readers will learn:
- Why health systems must treat clinical AI like any other regulated medical device
- How trust and governance function as core strategy
- Lessons from systemwide AI deployments that disrupted workflows
- How leaders define ROI from day one
- Why AI platforms, not point solutions, represent the future
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