What does the “long tail” of AI really look like in a highly regulated industry? In this episode, Dave Wollenberg, VP of Enterprise Data & Analytics at Scan, breaks it down. From cautious experimentation to enabling non-technical users to build AI-driven POCs, Dave shares a grounded, practical perspective on AI adoption inside a Medicare Advantage organization.

You’ll hear why the real transformation isn’t just technical—it’s cultural. We talk about how to shift employee mindsets, educate business teams, and unlock self-service analytics while staying compliant. If you’re a tech or data leader trying to separate hype from real value, this one’s for you.

Key Takeaways:

The long tail of AI means rethinking roles—not just automating tasks

Real AI enablement starts with data quality, governance, and semantic clarity

Non-technical employees can (and should) build AI proof-of-concepts

Change management will make or break your AI strategy

In regulated industries, open source and secure deployment models matter

Timestamped Highlights:

00:55 – What Scan Health Plan does and why AI matters in healthcare

03:10 – From machine learning to generative AI: how use cases have evolved

08:15 – Three types of business users and how to upskill them for AI

12:40 – Shifting expectations: stakeholders want AI-powered insights, now

15:20 – Why self-service BI still falls short without a solid data foundation

18:35 – AI adoption isn’t just IT’s job—business users need to lead too

22:15 – Navigating AI in regulated industries: risks, rules, and realities

Quote of the Episode:

“It's not as if there's a certain amount of work in the world, and if AI takes some, there's nothing left to do. When you make people more powerful, they add more value—and you want more of them, not fewer.”

Pro Tips:

Host internal hackathons to build excitement and break down resistance

Use sandbox environments to safely encourage experimentation

Don't wait for technical users—give your business teams the tools to try

Call to Action:

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