Across the industry, AI pilots are everywhere but sustainable success stories are far rarer. Many organizations have launched promising initiatives only to see them stall due to poor alignment, unclear ownership or lack of measurable impact. As a result, leaders are increasingly shifting their focus from adopting AI to building true AI maturity.

This session addresses one of the most pressing challenges facing hub and access organizations today: how to scale AI beyond isolated use cases and embed it into everyday decision-making. By examining real-world examples of organizations that have moved past the experimentation phase, this discussion helps attendees understand what maturity actually looks like from governance and culture to data and metrics. The takeaway is clear: AI delivers its greatest value when it’s treated as a long-term capability, not a short-term experiment.

What you’ll explore:

Through real industry case studies, this discussion examines:

• How organizations progressed from early AI tests to sustained, measurable improvements in patient experience
• Common pitfalls that stall AI initiatives, including misaligned expectations, poor data quality and lack of internal buy-in
• Tools to assess your current position on the AI maturity curve
• Strategies to align leadership, operations and frontline teams around AI adoption
• How mature AI programs can enhance empathy by surfacing deeper patient insights

Why this matters:

AI maturity isn’t just about better algorithms, it’s about culture, governance and strategy. This session provides a roadmap for building AI capabilities that last, scale and continuously improve patient outcomes.