A VP of Marketing and I started working through why her AI deployment stalled. Six months in, she had real infrastructure: brand knowledge wired in, quality evaluation on every asset, automated workflows across four markets. Adoption was at 18%.

We worked through three questions together: Does the approval screen show reviewers what the system considered and where it was uncertain? When one region learns something, does it reach the other regions automatically? When one person builds a great workflow, does the team inherit it?

She already knew the answers. Three no's.

After watching this pattern repeat across dozens of deployments, I think I understand why. Enterprise AI has three problems that interact in ways nobody talks about: an infrastructure gap, an experience gap, and a coordination gap. Companies keep solving one and watching the other two erode the investment.

Infrastructure without coordination produces ghost systems. Coordination without good experience design produces rubber-stamping. Experience design without infrastructure produces beautiful screens with nothing flowing through them.

The leaders who break through work on all three simultaneously, in thin slices. One workflow at a time. Infrastructure, experience, and coordination wired together from the start. Then expand.

I wrote something longer about the compound and how to diagnose which interaction is stalling your deployment.

Full piece is on Substack. Link in comments.