Lesson 09 of 20
Auditing a Services SOW Bundle: Feed, Chain, Report
Contract Review & Negotiation · Professional services (consulting)
Synthetic case data — evidence from real ChatGPT, Claude, Gemini and Copilot runs.
It's Wednesday. Your Procurement Director wants the Whitmore & Crane SOW signed by Friday. Supply-chain optimization, $285,000 fixed fee, three phases, clean formatting. She forwards you the folder: "Looks standard, just sanity-check it."
Four files, not one. The SOW itself, with tracked-change comments leaking into the text. A rate card. An excerpt of the master agreement. And a closed 2025 SOW somebody left in the folder.
This is the shape most contract reviews actually take. Not one clean document. A pile of related files where the risk lives in how they connect, and in what one document says versus what another one doesn't.
Three steps turn that pile into a decision your Director can act on by Friday:
- Feed the documents with explicit roles — which is the contract under review, which is the governing reference, which is a baseline for what changed, and which carries evidence of intent — so the AI reads them against each other instead of in isolation.
- Chain the problems — push past a flat list of single-clause findings into compound risks that name two or more clauses and narrate the failure that only happens when both fire.
- Report the decision — model the financial exposure in dollars and write a send-ready email with specific redlines.
You’ve read the free three. The other seventeen are where the misses live.
The first lessons show what a general-purpose AI catches on a procurement task. The rest show what it misses — the unit conversion that survives an expert prompt, the two clauses it lists but never connects, the table that contradicts its own arithmetic. That gap is the job.
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