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"A leading analyst just described the org structure of the AI era. I drew it in 1999 — before the cloud, before SaaS, before any of it existed. Here's the one condition his model still needs."

"Braum's bounded itself to a 300-mile circle, and the market calls it caution. It's the most disciplined growth decision in American retail — and the same law that governed a cotton exchange in 1931."

"I've had this conversation with CIOs for forty-three years. Last week I had it with an AI — and it made the same mistake."

"Strip the branding off a dozen AI maturity models and the skeleton is identical. Here's the one layer none of them measures."

"We've governed suppliers, couriers, and employees for decades. Then an AI agent enters the room — and somehow all the questions vanish. That's the entire mistake."

"'The AI said so' is not something you can defend to a board, a regulator, or an audit committee. This session is about what you say instead."

Here is the updated version with the corresponding graphic - by the way, this is for the Procurement Insights blog.

We didn't predict agentic AI. We built the model that agentic AI now has to live inside — twenty-seven years ago.

In January 2025 I asked whether any AI could tell me what time of day orders come in. One did — right after I told it order timing was the variable. That one-second gap, between answering a question and knowing which question to ask, is why adding an AI agent to an undiagnosed field doesn't build an intelligent ecosystem. It builds a faster version of the existing misalignment. Gemba walks one floor. The agent field has no floor.

Why IT keeps getting blamed for failures that were decided before the platform was ever chosen.

The companies everyone cites as proof that AI works were winning long before AI arrived.

Four firms. Four acronyms. Forty years. One diagnosis — and the failure rate never moved. Why?

"What really happens when your AI technology works — and nothing changes?"

From Ariba 2007 to Vertice 2026 — has the substrate misalignment that derails most initiatives finally been addressed?

When the CFO and the COO are the same person, what happens to the silos? I wrote about this in 2008. Brittany Bagley just embodied it in 2026.

"For twenty years we tried to eliminate maverick spend. The AI era is about to show us it was never the problem — it was the signal."

What do a Chief Data Officer and Chief AI Officer have in common?