AI investment is surging, and nearly every enterprise claims to be “AI-ready.” But many organizations are hitting a wall, not because of models, talent, or cost, but because their data can’t keep up.

Based on Semarchy’s global survey of 1,000 C-suite executives, this session explores the growing divide between companies successfully scaling AI and those quietly stalling due to fragmented data, delays, and rising risk.

Join Scott Taylor, The Data Whisperer, alongside leaders from Elsevier, Brown-Forman, and Semarchy for a candid discussion on what it really takes to operationalize AI in 2026.

In this session, you’ll learn:

• Why data management, not cost or talent, is now the #1 barrier to AI at scale

• What separates organizations delivering measurable AI outcomes from those stuck in pilot mode

• How leading companies are using MDM, DataOps, and a data product mindset to accelerate AI adoption

• What agentic AI changes and why it raises the stakes for data governance

• Practical steps to move from AI ambition to reliable, production-ready results