AI costs and savings

Most AI dashboards give you one number. Nobody believes it, and usually the person who printed it does not believe it either. The problem is not the arithmetic, it is that a single figure hides which parts somebody checked and which parts a model estimated at some point.

So this splits three ways. AI estimates are what the model worked out from what it could see. Team-confirmed are the ones somebody on your team looked at and said yes, that is right. Unpriced is the work we can see happening and cannot honestly put a number against.

The unpriced column is the one that makes the other two usable. A tool that quietly folds everything into one total is asking you to trust it completely or not at all. A tool that shows you the edge of what it knows is one you can take into a finance meeting and defend line by line.

The claims are capped on purpose. A credited run counts at the manual cadence it replaced: an hourly job that took over a weekly chore credits one run a week, not 168. And hours spent rebuilding something never turn into dollars at all; work that is new rather than replaced shows up as new capacity delivered, not as savings.

Our own cost is on the same page, split into AI, integrations, and sandboxes, and the report prints the subtraction literally: saved minus cost equals net. What you pay your AI vendors directly is excluded and the report says so, rather than leaving you to notice.

Underneath that is the plain spend. What each operation costs per run, which integrations are drawing the most, how long things take, and the last things that ran. The expensive thing is usually not the thing you assumed.

All of it prints to a PDF you can forward to finance. No AI computes any figure in the report; every number derives from the audit log and your confirmed baselines, so it prints the same today and tomorrow.