For a long time, AI in legal felt like a thought experiment. Something that might one day help lawyers, once the tech matured and the risk was under control.
That day has arrived.
ChatGPT — and tools like it — are now part of daily workflows in in-house legal teams. When we surveyed in-house lawyers earlier this year, over 90 per cent told us they use these LLMs daily or weekly. They redraft clauses, summarize 40-page MSAs, identify risks, and prep legal summaries for non-lawyers in minutes.
But here’s the catch: the quality of the output depends entirely on the quality of the prompt.
This article brings together ChatGPT prompts that lawyers actually use — across contracts, compliance, research, knowledge sharing, and negotiation — and explains how Juro’s ChatGPT integration takes them even further by letting you ask those same questions of your live contracts.
Let's get into it.
What makes a great ChatGPT prompt for lawyers?
A good legal prompt isn’t magic — it’s input engineering. The more context you feed ChatGPT, the more precise and actionable the answer you get in return becomes.
Think of ChatGPT like a junior associate who’s eager but less informed: if you don’t brief it clearly, it’ll make confident but incomplete guesses. A great prompt eliminates that guesswork.
Here’s what that looks like in practice:
1. Set a clear goal
Start with an explicit instruction about what you want ChatGPT to do. Verbs like redraft, summarise, compare, highlight, explain, or structure create direction. ChatGPT is powerful, but not a mind reader. You still need to tell it what form the answer should take.
2. Give it context
Law isn’t one-size-fits-all. Include jurisdiction, contract type, and any commercial backdrop. This helps ChatGPT tune its output to the right risk profile. Without that, you’ll often get generic responses that don’t fit your use case.
That’s why we highly recommend setting up (and even automating) a contract playbook or contract management policy. This is where you can customize and refine the context ChatGPT needs and reduce the need to capture this in every prompt.
4. Define your format
Tell it how to present the output. Tables, bullet points, side-by-side comparisons, or email-ready summaries all change how the model structures information.
Ask yourself: how would I best like to receive this information? Then relay that request.
5. Layer your prompts
Legal questions often need nuance, so it helps to use iterative prompting — start broad, then narrow down with continuous feedback. This allows you to build context cumulatively and chunk the information to avoid overwhelming the answer engine and maintain focus at every stage.
6. Avoid ambiguity
Finally, remember that words like review, check, or assess can be too vague. Review against what? Assess which elements? Specify what to review for, what to check against, or what to assess. This will refine the output and the accuracy of the response you receive.
ChatGPT prompt library for lawyers
1. ChatGPT prompt for redrafting clauses
Prompt example
“Redraft this force majeure clause to exclude labour disputes involving the supplier’s own staff and include pandemics. Keep the tone formal, neutral, and compliant with English law drafting conventions. Return only the revised clause, formatted as a numbered subclause.”
Why it works:
- The outcome is clear (“redraft”).
- The constraints (tone, jurisdiction, format) stop ChatGPT from adding fluff.
- "Return only the revised clause” prevents unnecessary explanations.
2. ChatGPT prompt for contract review (with playbook)
Prompt example
“Review the following SaaS contract for compliance with our internal playbook. Focus on: (1) governing law, (2) limitation of liability, (3) IP ownership. Highlight non-compliant provisions in a three-column table: clause reference, issue identified, recommended fix.”
Why it works:
- The structured output (“three-column table”) makes it instantly actionable. - The narrowed scope (“focus on X, Y, Z”) prevents generic or overwhelming responses.
3. ChatGPT prompt for summarizing contracts
Prompt example
“Summarize this commercial contract in 10 concise bullet points. Include details on: parties, duration, renewal terms, fees, termination rights, governing law, liability, key obligations, and any unusual clauses or risks. Write the summary as part of a professional email addressed to an executive audience — use plain English, avoid legal jargon, and highlight what matters commercially rather than restating legal boilerplate.”
Why it works:
- The bullet-point structure creates scannability. - “Plain English” ensures business-readability, not legalese. - The output is scoped tightly around key business terms.
4. ChatGPT prompt for surfacing risks
Prompt example
“Review this contract and identify all clauses that present significant commercial or compliance risks.
For each risk, provide: 1. The issue — clearly describe what the clause says and why it’s risky. 2. The potential impact — explain how it could affect the business (financially, operationally, or reputationally). 3. A proposed mitigation or redline — suggest practical wording or negotiation strategies to reduce the risk.
Present your analysis in a Markdown table with the following columns: Clause / Topic | Issue | Potential Impact | Proposed Mitigation / Redline
Use plain, business-friendly language, and focus on commercial relevance rather than legal technicalities.”
Why it works:
- It forces ChatGPT to reason, not just label. - The “impact” column pushes it to think in business terms. - Markdown format makes it copyable for documentation.
5. ChatGPT prompt for generating negotiation positions
Prompt example
“Provide five well-reasoned negotiation arguments to justify excluding indirect or consequential losses from a SaaS supplier agreement governed by English law.
For each argument:
1. Explain the commercial rationale — why the exclusion is fair and reasonable. 2. Reference any relevant legal or market practice principles under English law. 3. Suggest a fallback position the supplier could offer if the customer pushes back (e.g. limiting indirect loss exclusions to specific categories, or capping liability).
Rank the arguments by commercial strength, starting with the most persuasive. Write in plain, executive-friendly language, focusing on risk allocation and fairness, not legal jargon.
Why it works:
- Adds prioritisation (“rank them”) to turn insight into actionable strategy. - Trains ChatGPT to blend legal reasoning with persuasion, mirroring how lawyers argue commercially. - Builds negotiation depth by layering rationale, law, and fallback options. - Anchors outputs in English law and market norms, boosting credibility.
6. ChatGPT prompt for creating a compliance checklist
Prompt example
“Create a detailed GDPR compliance checklist tailored to a UK-based SaaS company. Cover the key obligations under Articles 5–30, including:
1. Core principles (lawfulness, fairness, transparency, etc.) 2. Data subject rights and how to operationalize them 3. Controller and processor responsibilities 4. Documentation and record-keeping requirements (e.g. RoPA, DPIAs, DPA clauses)
For each requirement, include: Article reference, Obligation summary, Practical action needed, Evidence or documentation required.
Present the output as a Markdown table that can double as a working compliance tracker. Use clear, business friendly language suitable for legal, ops, and product teams.”
Why it works:
- Anchoring to legal sources (“Articles 5–30”) narrows scope. - Adds detail and traceability, avoiding vague compliance lists. - Outputs double as an internal compliance tool, not just a summary.
7. ChatGPT prompt to simplify legislation
Prompt example
"Summarise the key obligations under the UK Data Protection Act 2018 that apply to employers handling employee data. Write for an HR manager with no legal training — use plain, practical English, avoiding legal jargon.
Include:
1. The main data protection principles and what they mean in an HR context. 2. The lawful bases most relevant to employee data. 3. Guidance on transparency, retention, security, and data subject rights. 4. Common risks or mistakes employers should avoid.
Structure the response with clear headings or bullet points so it can be used as a quick reference guide."
Why it works:
- Defines the audience, tailoring tone and depth to a non-legal HR reader. - Limits scope to obligations that truly affect employers for increased relevance. - Translates complex statutory rules into everyday HR actions and outputs.
8. ChatGPT prompt for comparing clause versions
Prompt example
“Compare the two indemnity clauses below. Identify which version favours the supplier and explain why. Present your analysis in a side-by-side Markdown table with the following columns:
Clause text | Risk level (Low/Medium/High) | Explanation
Focus on:
1. Scope of indemnity (e.g. who is protected and for what types of loss) 2. Trigger events and any limitations or carve-outs 3. Reciprocity or imbalance between supplier and customer
End with a one-line recommendation on which clause the customer should prefer and why. Use plain, commercial English, not legalese.”
Why it works:
- The explicit comparative format creates structured analysis. - “End with a one-line recommendation” forces conciseness. - Encourages legal interpretation with explanation, not bare conclusions
The Juro + ChatGPT advantage: live, contextual, and secure
Until now, getting AI to help with contracts meant juggling tabs, copying sensitive clauses into ChatGPT, and hoping no data leaked into the void. That era is over.
In 2025, Juro became the first CLM to integrate directly with ChatGPT, as reported byThe Lawyer and Fox40.
This integration means lawyers can now ask questions of their contracts directly, safely, and instantly — without ever leaving Juro. It isn’t just another AI feature, it’s a meaningful shift in the way legal teams interact with their contracts.
With Juro’s ChatGPT integration, you can now ask natural-language questions about your agreements and get precise, compliant answers in seconds, drawn from the live contract data inside your secure workspace.
Imagine being able to ask:
“Which of our customer contracts renew in Q2?”
“What’s the highest liability cap across all supplier agreements?”
“Summarize the notice periods in our top 20 deals.
And seeing instant, structured results — no manual review, no external data risk, no wasted hours to manual data extraction and review.
To see Juro's ChatGPT integration for yourself, hit the button below.
The golden rule of generative AI still holds: what you get out depends entirely on what you put in.
For legal teams, that means two things — understanding what ChatGPT can do, and recognising where its limits begin.
When used well, it’s an accelerator: drafting clauses, summarising contracts, surfacing risks, and translating legal complexity into business clarity. When used carelessly, it’s a liability: incomplete, outdated, or context-blind outputs can create new risks faster than they remove old ones.
To get consistent value, lawyers need to:
Engineer prompts like briefs. The more structure and context you give, the better the output.
Know where AI should stop. Use it to inform judgment, not replace it.
Work within trusted systems. Tools like Juro’s ChatGPT integration let you harness AI safely, using live contract data without ever leaving your secure workspace.
And if you’re ready to build on what you’ve learned here, check out these next steps:
Sofia Tyson is the Senior Content Manager at Juro, where she has spent years as a legal content strategist and writer, specializing in legal tech and contract management.
Sofia has a Bachelor of Laws (LLB) from the University of Leeds School of Law where she studied the intersection of law and technology in detail and received the Hughes Discretionary Award for outstanding performance. Following her degree, Sofia's legal research on GDPR consent requirements was published in established law journals and hosted on HeinOnline, and she has spent the last five years researching and writing about contract processes and technology.
Before joining Juro, Sofia gained hands-on experience through short work placements at leading international law firms, including Allen & Overy. She also completed the Sutton Trust’s Pathways to Law and Pathways to Law Plus programs over the course of five years, building a deep understanding of the legal landscape and completing pro-bono legal volunteering.
Sofia is passionate about making the legal profession more accessible, and she has appeared in several publications discussing alternative legal careers.
For a long time, AI in legal felt like a thought experiment. Something that might one day help lawyers, once the tech matured and the risk was under control.
That day has arrived.
ChatGPT — and tools like it — are now part of daily workflows in in-house legal teams. When we surveyed in-house lawyers earlier this year, over 90 per cent told us they use these LLMs daily or weekly. They redraft clauses, summarize 40-page MSAs, identify risks, and prep legal summaries for non-lawyers in minutes.
But here’s the catch: the quality of the output depends entirely on the quality of the prompt.
This article brings together ChatGPT prompts that lawyers actually use — across contracts, compliance, research, knowledge sharing, and negotiation — and explains how Juro’s ChatGPT integration takes them even further by letting you ask those same questions of your live contracts.
Let's get into it.
What makes a great ChatGPT prompt for lawyers?
A good legal prompt isn’t magic — it’s input engineering. The more context you feed ChatGPT, the more precise and actionable the answer you get in return becomes.
Think of ChatGPT like a junior associate who’s eager but less informed: if you don’t brief it clearly, it’ll make confident but incomplete guesses. A great prompt eliminates that guesswork.
Here’s what that looks like in practice:
1. Set a clear goal
Start with an explicit instruction about what you want ChatGPT to do. Verbs like redraft, summarise, compare, highlight, explain, or structure create direction. ChatGPT is powerful, but not a mind reader. You still need to tell it what form the answer should take.
2. Give it context
Law isn’t one-size-fits-all. Include jurisdiction, contract type, and any commercial backdrop. This helps ChatGPT tune its output to the right risk profile. Without that, you’ll often get generic responses that don’t fit your use case.
That’s why we highly recommend setting up (and even automating) a contract playbook or contract management policy. This is where you can customize and refine the context ChatGPT needs and reduce the need to capture this in every prompt.
4. Define your format
Tell it how to present the output. Tables, bullet points, side-by-side comparisons, or email-ready summaries all change how the model structures information.
Ask yourself: how would I best like to receive this information? Then relay that request.
5. Layer your prompts
Legal questions often need nuance, so it helps to use iterative prompting — start broad, then narrow down with continuous feedback. This allows you to build context cumulatively and chunk the information to avoid overwhelming the answer engine and maintain focus at every stage.
6. Avoid ambiguity
Finally, remember that words like review, check, or assess can be too vague. Review against what? Assess which elements? Specify what to review for, what to check against, or what to assess. This will refine the output and the accuracy of the response you receive.
ChatGPT prompt library for lawyers
1. ChatGPT prompt for redrafting clauses
Prompt example
“Redraft this force majeure clause to exclude labour disputes involving the supplier’s own staff and include pandemics. Keep the tone formal, neutral, and compliant with English law drafting conventions. Return only the revised clause, formatted as a numbered subclause.”
Why it works:
- The outcome is clear (“redraft”).
- The constraints (tone, jurisdiction, format) stop ChatGPT from adding fluff.
- "Return only the revised clause” prevents unnecessary explanations.
2. ChatGPT prompt for contract review (with playbook)
Prompt example
“Review the following SaaS contract for compliance with our internal playbook. Focus on: (1) governing law, (2) limitation of liability, (3) IP ownership. Highlight non-compliant provisions in a three-column table: clause reference, issue identified, recommended fix.”
Why it works:
- The structured output (“three-column table”) makes it instantly actionable. - The narrowed scope (“focus on X, Y, Z”) prevents generic or overwhelming responses.
3. ChatGPT prompt for summarizing contracts
Prompt example
“Summarize this commercial contract in 10 concise bullet points. Include details on: parties, duration, renewal terms, fees, termination rights, governing law, liability, key obligations, and any unusual clauses or risks. Write the summary as part of a professional email addressed to an executive audience — use plain English, avoid legal jargon, and highlight what matters commercially rather than restating legal boilerplate.”
Why it works:
- The bullet-point structure creates scannability. - “Plain English” ensures business-readability, not legalese. - The output is scoped tightly around key business terms.
4. ChatGPT prompt for surfacing risks
Prompt example
“Review this contract and identify all clauses that present significant commercial or compliance risks.
For each risk, provide: 1. The issue — clearly describe what the clause says and why it’s risky. 2. The potential impact — explain how it could affect the business (financially, operationally, or reputationally). 3. A proposed mitigation or redline — suggest practical wording or negotiation strategies to reduce the risk.
Present your analysis in a Markdown table with the following columns: Clause / Topic | Issue | Potential Impact | Proposed Mitigation / Redline
Use plain, business-friendly language, and focus on commercial relevance rather than legal technicalities.”
Why it works:
- It forces ChatGPT to reason, not just label. - The “impact” column pushes it to think in business terms. - Markdown format makes it copyable for documentation.
5. ChatGPT prompt for generating negotiation positions
Prompt example
“Provide five well-reasoned negotiation arguments to justify excluding indirect or consequential losses from a SaaS supplier agreement governed by English law.
For each argument:
1. Explain the commercial rationale — why the exclusion is fair and reasonable. 2. Reference any relevant legal or market practice principles under English law. 3. Suggest a fallback position the supplier could offer if the customer pushes back (e.g. limiting indirect loss exclusions to specific categories, or capping liability).
Rank the arguments by commercial strength, starting with the most persuasive. Write in plain, executive-friendly language, focusing on risk allocation and fairness, not legal jargon.
Why it works:
- Adds prioritisation (“rank them”) to turn insight into actionable strategy. - Trains ChatGPT to blend legal reasoning with persuasion, mirroring how lawyers argue commercially. - Builds negotiation depth by layering rationale, law, and fallback options. - Anchors outputs in English law and market norms, boosting credibility.
6. ChatGPT prompt for creating a compliance checklist
Prompt example
“Create a detailed GDPR compliance checklist tailored to a UK-based SaaS company. Cover the key obligations under Articles 5–30, including:
1. Core principles (lawfulness, fairness, transparency, etc.) 2. Data subject rights and how to operationalize them 3. Controller and processor responsibilities 4. Documentation and record-keeping requirements (e.g. RoPA, DPIAs, DPA clauses)
For each requirement, include: Article reference, Obligation summary, Practical action needed, Evidence or documentation required.
Present the output as a Markdown table that can double as a working compliance tracker. Use clear, business friendly language suitable for legal, ops, and product teams.”
Why it works:
- Anchoring to legal sources (“Articles 5–30”) narrows scope. - Adds detail and traceability, avoiding vague compliance lists. - Outputs double as an internal compliance tool, not just a summary.
7. ChatGPT prompt to simplify legislation
Prompt example
"Summarise the key obligations under the UK Data Protection Act 2018 that apply to employers handling employee data. Write for an HR manager with no legal training — use plain, practical English, avoiding legal jargon.
Include:
1. The main data protection principles and what they mean in an HR context. 2. The lawful bases most relevant to employee data. 3. Guidance on transparency, retention, security, and data subject rights. 4. Common risks or mistakes employers should avoid.
Structure the response with clear headings or bullet points so it can be used as a quick reference guide."
Why it works:
- Defines the audience, tailoring tone and depth to a non-legal HR reader. - Limits scope to obligations that truly affect employers for increased relevance. - Translates complex statutory rules into everyday HR actions and outputs.
8. ChatGPT prompt for comparing clause versions
Prompt example
“Compare the two indemnity clauses below. Identify which version favours the supplier and explain why. Present your analysis in a side-by-side Markdown table with the following columns:
Clause text | Risk level (Low/Medium/High) | Explanation
Focus on:
1. Scope of indemnity (e.g. who is protected and for what types of loss) 2. Trigger events and any limitations or carve-outs 3. Reciprocity or imbalance between supplier and customer
End with a one-line recommendation on which clause the customer should prefer and why. Use plain, commercial English, not legalese.”
Why it works:
- The explicit comparative format creates structured analysis. - “End with a one-line recommendation” forces conciseness. - Encourages legal interpretation with explanation, not bare conclusions
The Juro + ChatGPT advantage: live, contextual, and secure
Until now, getting AI to help with contracts meant juggling tabs, copying sensitive clauses into ChatGPT, and hoping no data leaked into the void. That era is over.
In 2025, Juro became the first CLM to integrate directly with ChatGPT, as reported byThe Lawyer and Fox40.
This integration means lawyers can now ask questions of their contracts directly, safely, and instantly — without ever leaving Juro. It isn’t just another AI feature, it’s a meaningful shift in the way legal teams interact with their contracts.
With Juro’s ChatGPT integration, you can now ask natural-language questions about your agreements and get precise, compliant answers in seconds, drawn from the live contract data inside your secure workspace.
Imagine being able to ask:
“Which of our customer contracts renew in Q2?”
“What’s the highest liability cap across all supplier agreements?”
“Summarize the notice periods in our top 20 deals.
And seeing instant, structured results — no manual review, no external data risk, no wasted hours to manual data extraction and review.
To see Juro's ChatGPT integration for yourself, hit the button below.
How lawyers can get the most value from ChatGPT
The golden rule of generative AI still holds: what you get out depends entirely on what you put in.
For legal teams, that means two things — understanding what ChatGPT can do, and recognising where its limits begin.
When used well, it’s an accelerator: drafting clauses, summarising contracts, surfacing risks, and translating legal complexity into business clarity. When used carelessly, it’s a liability: incomplete, outdated, or context-blind outputs can create new risks faster than they remove old ones.
To get consistent value, lawyers need to:
Engineer prompts like briefs. The more structure and context you give, the better the output.
Know where AI should stop. Use it to inform judgment, not replace it.
Work within trusted systems. Tools like Juro’s ChatGPT integration let you harness AI safely, using live contract data without ever leaving your secure workspace.
And if you’re ready to build on what you’ve learned here, check out these next steps:
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