A framework to integrate AI into clinical practice.
Let’s be honest: No one has clinical AI governance completely figured out yet.
Every institution is different. Every culture is different. As Avi Sharma, MD, CIIP, Director of AI Innovation at Jefferson Einstein, put it during a recent webinar: “Welcome to growing pains.”
He offered an inside look at what it really takes to scale AI governance across a complex, multihospital health system, and why the process is just as much about people and priorities as it is about platforms and tools.
Governance, he warns, is becoming a buzzword. However, the work behind it is very real.
At Jefferson Einstein, governance started small — with a local Imaging AI Committee — but as the network grew to include more than a dozen hospitals, that committee evolved into a larger, enterprise-wide steering structure.
With the emergence of generative AI, it’s now part of a broader Enterprise AI Steering Committee tasked with evaluating, coordinating and guiding AI efforts across departments and specialties.
“It’s a lot of demand, a lot of needs and a lot of people who want to start using AI yesterday,” Dr. Sharma said. “But they don’t always know where to start.”
So where do you start?
At Jefferson Einstein, that meant bringing everyone to the table — legal, IT, the C-suite and clinical champions from across the system — and putting pen to paper on what AI solutions must do to earn trust, ensure patient safety and comply with evolving regulations like Section 1557 of the Affordable Care Act (ACA), which holds health systems accountable for bias and failure in AI tools.
But setting guardrails is only step one.
The harder challenge? Taking inventory of every AI tool currently deployed across the system, both commercial and homegrown, and deciding what’s scalable, what’s redundant, what’s risky and what needs to be sunset. That includes asking hard questions:
Hear how Jefferson Einstein is approaching AI governance as a living process, not a checkbox, and why getting it right takes coordination, transparency and long-term thinking.
Watch the full webinar to see how leaders like Dr. Sharma are confronting the complexity of real-world AI governance, aligning stakeholders across departments, and building an enterprise framework that scales safely, equitably and sustainably.
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