AI Contract Review: How Lawyers Can Use LLMs Safely

Where LLMs genuinely help

A language model does not replace a lawyer, but it handles high-volume, repetitive work well:

• Clause extraction: parties, subject matter, term, price and payment terms, liability, termination, jurisdiction, governing law.
• Risk flags: finding wording your practice considers problematic — unilateral termination, unlimited liability, auto-renewal, uncapped penalties.
• Template comparison: which clauses the counterparty changed, removed or added compared to your standard version.
• Client summaries: a short plain-language overview of key terms.
• Drafts: versions of a disagreement protocol or alternative wording.

The final legal assessment and the position on risks stay with the lawyer.

How to frame the task

A generic "review this contract" produces a generic answer. Specific instructions work.

Extraction into a table

Ask for a structure with the clause number and a verbatim quote for every field. The quote lets you quickly confirm the model did not fill in gaps.

Extract the following terms from the contract. For each, return:
- the value;
- the clause number;
- a verbatim quote.
If a term is absent, write "not found". Do not draw conclusions beyond the text.
Fields: parties, subject matter, term, price, payment terms,
liability, termination grounds, jurisdiction.

Risk flags from your checklist

Do not ask the model to "find all risks" — give it your own list with a description of what counts as a problem. That makes the output predictable and aligned with your practice or company policy.

Comparing against a template

For precise comparison, run a regular document comparison tool (redline) first, then use the LLM to explain what the changes mean: "clause 7.2: contractor liability is capped at the contract value; the template had no cap".

How to verify the output

Models fail in different ways, and some failures look convincing:

• missing a term that is spread across several clauses or hidden in an appendix;
• wrong clause number references;
• invented statutes or case law;
• mixing versions when several drafts were uploaded to the same chat.

Verification rules:

1. Check every extracted term against its quote and clause in the original.
2. Verify legal references in official sources, not in the model's answer.
3. No flag does not mean no risk — the model's checklist does not replace a full reading of critical sections.
4. Split long contracts with appendices into parts and confirm the model saw the full text.
5. Keep a log: which document, which model and which prompt were used.

Confidentiality of client documents

This is the key question. A client's contract is confidential information and sometimes covered by legal privilege.

In addition:

• anonymize documents where possible: replace party names, amounts and bank details with placeholders;
• check whether your client agreement, professional ethics rules or personal data law require consent to use external services;
• set rules in an internal policy: which services are allowed, which documents must never be uploaded, who is responsible for review;
• restrict access to prompt history and set retention periods.

Common mistakes

• Uploading a client's signed contract to a personal chat account.
• Trusting statute references without checking.
• Treating the model's answer as a finished legal opinion.
• One prompt for a document hundreds of pages long without checking completeness.