On this episode, our hosts Nick Woo, Rehgan Bleile, and Brendan Kelly return for another audience Q&A episode, providing insight into the ethical implementation of AI systems within the enterprise.

The team dives into how to responsibly enhance model performance and evaluate the ROI from generative AI. We also discuss and address questions around automation inside the enterprise. Additionally, we focus on recent AI developments and how these may shape current and future conversations between leaders and their teams.

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On this episode, we welcome Scott Brown, an architect at Andelyn Biosciences. Scott has a focus on data flow enablement, operational excellence and innovation to serve analytics and AI.

We discuss the critical importance of human-in-the-loop oversight, the evolving role of evaluation frameworks for AI outputs, and the broader shift toward hybrid AI systems that blend generative and traditional machine learning techniques. From building early, low-risk use cases to preparing for more advanced agentic AI applications, we highlight actionable strategies for responsibly scaling AI across industries.

Scott Brown

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On this episode, we welcome Nan Li, an experienced AI and machine learning leader at Nationwide. Nan shares her insights from years of enabling AI and machine learning adoption within large enterprises, with a focus on workforce readiness, human-AI interaction, and operating model design.

We explore how enterprises are evolving to support AI adoption beyond technical teams, highlighting the shift from centralized innovation to more distributed, domain-embedded use. Additionally, we examine the emerging personas within an AI-enabled workforce—builders, users, and protectors—and the cultural and structural changes required to empower each group. From democratizing low-risk use cases to managing risk in high-impact workflows, we offer a practical look at how organizations can build an AI-ready workforce in a responsible, scalable way.

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