Live Webinar

AI readiness in 2026: the infrastructure problem

January 29, 2026 | 10:00 am - 11:00 am PST

Why AI initiatives stall in real organizations, and what readiness across data, architecture, and human systems actually takes.

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The readiness gap blocking real AI impact

MIT Sloan Senior Lecturer Paul Cheek joins experts from Unwrap, Absolute Web, Simplesat, and Gladly for a candid conversation on why AI initiatives stall in practice — and what it takes to build the foundation AI needs to work.

This isn't about tools, hype, or demos. It's about the four places AI quietly breaks down: unrealistic automation expectations, fragmented customer data, architectural debt, and human operating models that were never redesigned. Learn why these failures compound, and what readiness across structure, data, process, and people looks like.

What you'll learn:
The four failures that stall AI initiatives

What breaks when AI automates undefined work, acts on incomplete context, hits architectural ceilings, or lands without clear human roles.

What "AI readiness" actually means

Not a phase — an operating environment. Structure, data, process, and people have to move together for AI to function.

Where this breaks in practice

Real examples from commerce, feedback systems, and CX — with specific fixes, not theory.

Speaking guests from

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Start building real AI readiness