A Practical Contract Review Checklist You Can Run With ChatGPT

Most weak AI outputs happen because the model never gets the commercial context. Before you paste a clause, add the transaction type, your client objective, and the risk tolerance. This alone changes the quality of the analysis.

For example, a startup raising cash may accept broader assignment language than a mature buyer in an M&A deal. Same words, different risk posture.

Ask for output in a fixed format: issue, why it matters, severity, fallback language, and negotiation note. That format keeps output usable when you are triaging 10+ agreements in one afternoon.

A practical add-on: ask for one 'business impact sentence' per issue (timeline risk, revenue risk, compliance risk). It helps legal and commercial teams align faster.

After first-pass review, run a second prompt focused on negotiation strategy: what to push, what to trade, and what to accept only with compensating terms.

This mirrors how experienced counsel works in practice: identify legal risk first, then package it into a realistic negotiation path.

Use AI to draft, not decide. Final legal judgment still sits with counsel. Build a short verification checklist for governing law, enforceability, and client-specific business realities before anything goes out.

ABA guidance on generative AI reinforces this point: competence, confidentiality, and supervision obligations still apply even when AI speeds up drafting.

Use these as policy and workflow inputs, not as substitutes for jurisdiction-specific legal analysis.