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There is no prompt that can guarantee an LLM will not invent or distort legal language. The practical safeguard is to limit what it may rely on, make every proposed clause traceable to authoritative material, and have a qualified person verify the text and its legal fit. Fluent wording is not proof that a clause exists, is current, or applies to your jurisdiction.
Why legal clauses need more than a plausible-sounding answer
Large language models generate likely text; they do not establish that a legal proposition is true. The National Center for State Courts’ AI Policy Consortium for Law & Courts puts it plainly: “LLM’s predictive nature generates text that sounds right rather than text that is right.” A model can produce language that resembles a contract term or legal rule while inventing it, omitting a condition, relying on outdated material, or drawing from the wrong jurisdiction. The consortium’s guide recommends checking citations, cases, statutes, rules, and claims, with verification effort matched to the risk.
This matters in court as well as in private drafting, but court rules are jurisdiction-specific. For example, the Federal Court of Australia says in its practice note that “The presentation of false or inaccurate information to the Court is unacceptable,” and directs users of AI-assisted court documents to check that cited authorities exist and support the stated proposition. That is guidance for the Federal Court of Australia’s context, not a universal rule for every contract or filing. Read the Federal Court of Australia’s Generative Artificial Intelligence Practice Note.
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The following workflow draws on legal-sector guidance from Singapore’s Ministry of Law and court guidance in several jurisdictions. It can reduce opportunities for unsupported language and make errors easier to spot; it cannot guarantee correct output.
- Define the task and legal context. State what you need drafted or reviewed, the relevant jurisdiction, and the date or period that matters. A request for a clause governed by one jurisdiction should not leave the model free to draw on rules from elsewhere.
- Supply authoritative materials. Give the model the statutes, regulations, cases, contract documents, or other sources it is allowed to use. Specify that it must not rely on material outside that set. If you do not have the relevant source, treat that as a research task for a qualified person—not permission for the model to fill the gap.
- Require traceable output. Ask the model to return each proposed clause separately, with the source name, exact supporting passage, and any assumptions or unresolved questions. Separate the draft wording from the explanation so you can check both.
- Require abstention when support is missing. Tell the model to mark a clause or proposition “unresolved” if it cannot find direct support in the supplied material. Do not ask it to invent a citation, supply a standard-sounding substitute, or make up language to complete a section.
- Verify against the original. Open each cited statute, decision, rule, or source document yourself. Check that it exists and that the cited passage actually supports the precise claim or wording. A real citation can still be irrelevant or fail to support the proposition.
- Review the whole document. Check definitions, exceptions, dates, cross-references, surrounding provisions, completeness, and jurisdictional fit. A source may support one sentence without supporting the clause as a whole or showing that it belongs in this document.
- Put a qualified person in charge. Have someone with appropriate legal expertise review the final text and remain responsible for it. If the document is for court, follow the relevant court’s own rules and practice directions.
Singapore’s Ministry of Law recommends qualified human verification, authoritative sources, citations where possible, completeness checks, and prompts that specify jurisdiction, time period, and source requirements. Its Guide for Using Generative AI in the Legal Sector, published March 6, 2026, covers legal research, drafting, and contract review.
Check both the citation and what it proves
Verification has two distinct questions: does the source exist, and does it support the exact proposition in the draft? Checking only a citation’s existence misses errors such as a source being misquoted, taken out of context, superseded, or applied to the wrong legal issue. Compare the generated wording with the original source and examine relevant surrounding text.
The Supreme Court of Victoria’s practice note says AI-assisted court content should be checked for currency, completeness, accuracy, and jurisdictional applicability. It also warns: “One AI tool cannot be used to confirm the content generated by another AI tool.” In other words, a second chatbot’s agreement is not independent verification. The note, issued May 14, 2026, also cautions against entering confidential or sensitive information into public tools. See SC GEN 25.
Other court guidance makes similar verification expectations within its own procedural setting. The Irish High Court’s practice direction requires independent checking of authorities, citations, quotations, and references used in court documents, and warns that fabricated or inaccurate material can mislead the court and other parties. Those requirements apply in that court’s context; they should not be treated as a universal contract-review rule. Read the Courts Service of Ireland’s practice direction.
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Protect confidential information before using an AI tool
Before entering a client document, negotiation position, personal data, or other sensitive material, check the tool’s settings and the terms that govern its use. Confirm how inputs and outputs are handled, whether they may be retained or used for other purposes, and what safeguards apply. If you cannot establish that the tool is suitable for the information, do not submit it; use an approved environment or have a qualified person work from an appropriately protected copy.
The Supreme Court of Victoria specifically flags privacy risks with public AI tools and cautions against entering confidential or sensitive information. The right safeguards depend on the tool, the information, and the applicable professional and contractual obligations.
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What a real court case shows—and what it does not
The Illinois Courts’ 2025 account of Mata v. Avianca describes a court filing containing six fictitious cases. It reports a $5,000 fine and a requirement for further legal education in that case. The account also notes that asking the AI whether its invented cases were real did not provide reliable verification. These are reported details of one case, not a measure of how often models invent legal material or a prediction of sanctions in another jurisdiction. Read the Illinois Courts’ account.
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- A proposed clause has no direct support in an authoritative source, or the cited passage does not support its exact meaning.
- The model cannot identify which jurisdiction or time period its wording reflects.
- The clause affects significant rights, obligations, liability, or court submissions and you cannot verify its implications yourself.
- Definitions, exceptions, cross-references, or surrounding terms are missing or inconsistent.
- You are unsure whether the AI tool is appropriate for confidential or sensitive material.
In these cases, treat the output as a lead or draft for review, not as ready-to-use legal language. Ask a qualified legal professional to resolve the issue using the applicable sources and rules.
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