Someone has to own the AI decisions before the org can justify a full-time title. That is the gap this fills.
AI That Pays for Itself is blunt about the mid-market problem: most firms do not have a tooling gap. They have a decision gap.
A ranked portfolio of AI opportunities tied to workflows, metrics, owners, and readiness — not whoever shouted loudest after the last demo.
Ideas that are interesting but not ready: no data owner, no metric, no sponsor, no path to payback.
Pilots that hit the kill criterion. Sunk cost is not a ranking criterion.
Score readiness, pick one workflow, map where the work goes, name the sponsor and owner, and agree the metric before tool selection.
Build the boring, bounded pilot with an error log and human gate before go-live.
Measure honestly, run error analysis on real traces, and redesign the workflow around what changed.
Scale, adjust, or stop. Set the quarterly re-validation cadence before attention drifts.
A CEO, COO, managing partner, or operator has a real workflow problem, an executive sponsor, and enough discipline to measure value before expanding.
You want someone to sprinkle AI over a broken process, pick tools before metrics, or run a transformation theatre project with no owner. Plenty of people sell that. I try not to.