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

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"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?
Phase 0 isn't a readiness methodology. It's the mechanism for escaping forty years of accumulated technology debt.
A frontline agent is not an agent-based model. The difference is why your AI will fail.
It's time we stopped buying AI capability — and started committing to the outcomes it's supposed to produce.
Gartner calls it an adoption gap. The evidence — including Gartner's own — says it's an absorption gap. Knowing the difference decides whether you fix it.
Why would AI produce any better results than previous technologies?
We don't predict failure. We identify the conditions that produce it.
AI does not break broken clinical processes. It perfects them at machine speed.
"These four questions are critical, yet only 2 of them are ever answered."
"Effective SRM has little to do with QBRs and more to do with agent discipline."
"Vendor scorecards tell you whether your procurement function is ready. They do not tell you whether your enterprise is ready for what AI deployment will do to your procurement function."
"Capability acquisition is the easy part. Coherence has to be earned — and the methodology that earns it has been operating since 1998."
"Capability can be acquired. Coherence has to be earned."