The AI in Business Podcast AI Use Cases, Deployment, and Measuring Real-World ROI - with Ylan Kazi of Blue Cross Blue Shield of North Dakota
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Mar 10, 2026 
Ylan Kazi, Chief Data and AI Officer at Blue Cross Blue Shield of North Dakota, leads enterprise AI strategy in regulated healthcare. He discusses when to build versus buy, balancing in-house teams with vendor partnerships. He covers explainability and auditability, navigating regulation with human-in-the-loop controls, and prioritizing seamless, customer-focused AI that delivers measurable value.
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Decide Your Organizational AI Posture Early
- Align executives on whether your organization will lead, fast-follow, or wait before deciding build versus buy for AI.
- Create internal capability for sustainable AI (data scientists/AI engineers) while outsourcing only extremely resource-intensive pieces like foundational LLMs.
Keep Core AI Skills In House
- Build targeted in-house AI skills instead of fully outsourcing to control costs and ensure sustainability.
- Keep internal data science or AI engineering teams to integrate vendor tech and apply models across use cases.
Prioritize Use Cases By Real Value
- Prioritize use cases by expected value before applying AI to them.
- Avoid using AI where the impact is marginal; focus investment on high-value customer or operational problems.