Learning eXchange Track:

Business Analytics and AI: From Action to Insights

Partial List of Presenters

Overview
Discover how Business Analytics transforms data into actionable insights that drive informed decision-making in today’s organizations. This WITX track will explore essential analytical tools for identifying trends and making evidence-based choices, while highlighting the evolving role of AI in enhancing predictive accuracy and automating complex processes. Learn how the synergy between Business Analytics and AI  is shaping the future of business operations, enabling real-time, autonomous optimization.

Grounding Generative AI: Why Your Data and Analytics Stack Still Matters

Stuart, Will

Bill Stuart

Senior Manager - Data Science
nCino
Bill_Stuart@LinkedIn

  • Bio: Bill leads data science and analytics at nCino, a SaaS company serving financial institutions. His team is part of the product organization, focused on building capabilities that help customers get smarter about numbers, drive efficiency, and strengthen relationships.

    A proud UNCW Seahawk with a graduate degree from UNC Charlotte, Bill has spent his career across multiple industries helping organizations make better decisions with data and AI.

  • Session Details: Generative AI is powerful but unreliable. It hallucinates, drifts from your business context, and confidently delivers answers that are plausible but wrong. Meanwhile, traditional analytics and machine learning are precise and trustworthy but lack flexibility and struggle with unstructured problems. Neither is sufficient on its own.

    This session explores how traditional data and analytics practices provide the guardrails generative AI needs—and how generative AI unlocks new interfaces for your existing data investments. We'll cover how structured data and retrieval systems keep generative outputs grounded in reality, where predictive models outperform (and can validate) generative suggestions, why data quality and architecture determine whether your AI assistant is helpful or dangerous, and how to design systems where generative and traditional AI hand off to each other seamlessly.

    Through a practical example, we'll demonstrate what happens when generative AI works alone versus when it's supported by a solid data foundation. Generative AI gets the headlines, but the unsexy work of data management might be what makes it actually useful.

Learning eXchange Business Analytics Track Coordinators: Megan Martin and Manoj Vanajakumari