Executive Summary
Who this is for: Heads of product and ML platform, finance partners, and engineering directors running agent copilots and traditional models side by side.
A mid-market B2B operator ran an agent copilot and a pricing-assist model from the same central AI budget. When the board asked why spend rose 22% in a quarter while governed workflows grew only 9%, neither sponsor could explain the bill or replay a bad release. The models were fine. The organization had two scoreboards, one budget, and no shared production loop.
This composite case shows how the firm closed that loop: one deploy package for every change, segment-aware testing, live-input monitoring, and spend tied to named workflow owners. Agent autonomy stayed on hold until a one-step rollback worked under pressure. Illustrative composite; dollar figures and indices are teaching magnitudes, not audited client outcomes.