Stop Piloting, Start Scaling: What Healthcare Really Needs from AI

The potential of AI in healthcare is undeniable. It enhances early disease detection, supports informed clinical decision-making, fosters patient engagement, and alleviates administrative burden. The opportunity extends far beyond workflow optimization, touching everything from imaging to population health to care coordination.

This perspective reflects insights recently shared by healthcare leaders who have implemented AI across their organizations—leaders who understand what works, what doesn’t, and why governance and trust make all the difference.

Ainsley MacLean, MD, FACR, Founding Partner at Ainsley Advisory Group, emphasizes that AI should ultimately simplify healthcare, rather than adding complexity. She encourages leaders to focus first on practical use cases, such as documentation, coding, and impression generation. These areas within radiology workflows quickly build trust because they deliver visible, measurable results.

Listen to Dr. MacLean share where she has experienced healthcare AI create the biggest impact with the least amount of risk.

Matt Zawalich, Chief Innovation Officer at Yale New Haven Health, underscores that AI success isn’t about chasing the newest model or running endless experiments. It’s about committing to programs that deliver clear, measurable value for patients, clinicians, and the organization. That means defining the problem upfront, agreeing on what success looks like, and ensuring the right operational leaders are held accountable.

He emphasizes that the real inflection point occurs when AI moves beyond isolated pilots and into the fabric of day-to-day operations. His team focuses on use cases that can scale across sites and service lines, supported by governance, ongoing monitoring, and a plan for iteration as workflows evolve. That practical, forward-thinking approach can make all the difference. 

In the clip below, Matt shares how his team decides which AI projects move forward, and what it takes to turn a promising proof of concept into a durable, system-wide program.

And as leaders increasingly realize, the language we use shapes the mindset we adopt. It is time to start talking about AI programs, rather than pilots. Programs with defined KPIs, operational ownership, and the ability to scale.

To explore these ideas in more depth, watch the full webinar and hear the complete discussion on how leading organizations are moving from AI pilots to real, scalable impact.