"AI project failure"

Most measurement approaches look at the wrapper around the work, not the work itself.

A program that started with the team, not the tool, shifted the outcome.

Instead of disconnected AI projects, you get a prioritized roadmap built on organizational reality.

That gap between the impressive demo and real business change is the cost that most finance teams won’t be able to measure.

The failure is not in the technology. It is in the operating model surrounding it, and it shows up in three interconnected places.

Where execution breaks down is in the tension I’ve been calling FOMO (fear of missing out) versus FOMU (fear of messing up).

To reduce risk from your AI program, address the gaps in your legacy infrastructure.

AI doesn't create the complexity tax, but it makes the bill impossible to ignore.