Legal AI Prompting Best Practices

Two of the top promises of Artificial Intelligence (AI) integration are that it offers superior accuracy and speed. With interfaces that require prompting, however, both factors depend on how well a user can engineer (a.k.a., create) the right prompt for the job. 

Skillful prompts generate more efficient and defensible results for research, review, drafting, and discovery workflows. They also help manage compliance and reduce risk for law firms and corporate legal departments. 

Let’s take a look at legal AI prompt engineering best practices that can help improve both the quality and efficiency of your AI use. 

TL;DR

• Legal prompt engineering is the art of crafting AI instructions to fit legal needs
• Effective prompts produce accurate, compliant, and reproducible results
• Prompts must never include privileged data or PII 
• It’s best practice to include a request for citations within prompts and incorporate human review of them
• Consider standardizing prompt templates and audit logs
• Select zero-retention, compliant AI tools

What Is “Legal Prompt Engineering”?

The more tailored the prompt, the more effective the output will be. When you enter a query into an AI interface, you are creating a prompt. As such, prompt engineering is the art of crafting AI instructions. Doing so within the practice of law is referred to as legal prompt engineering. 

Legal prompt engineering has unique best practices that differ from generic prompting. These practices require consistency and reliability, particularly in the handling of legal documents. Namely, you must consider: 

• Jurisdiction – Identify specific jurisdictions or sets of court rules to adhere to or consult.
  
• Privilege – Privacy and privilege must be protected even at a prompt level, and even if an AI system claims to be zero retention (i.e., does not include client input for machine learning). There should be no personally identifiable information (PII) or privileged information included in prompts.
  
• Evidence handling – AI can turn around results that include evidentiary connections and patterns, as well as provide hyperlinks and tags to call out potential evidence or evidentiary issues.

With all of this in mind, the objective for legal prompt engineering is to produce results that are: 

• Accurate
• Explainable
• Repeatable

Core Best Practices 

From how to start drafting a prompt to eventual audit needs, there are a few basic best practices to follow for legal prompt engineering.

Frame the Task Precisely

Use clear language, simple clauses and sentences, and specific directions when you write a legal prompt. Specify:

• Role of the AI (e.g., direct it to act as a “legal counsel” or “contract analyst,” etc.)¹
• Desired jurisdiction(s), both regional and specific court domain
• Format of desired results, such as a deposition summary, outline, or table
• Citation requirements

Consider this before-and-after prompt example from ContractPodAI²:

Before (Weak Prompt): “What are the requirements for patent infringement?”

After (Strong Prompt): “Provide a structured analysis of the elements required to establish direct patent infringement under 35 U.S.C. § 271(a) as interpreted by Federal Circuit decisions from 2022–2025. Include the standard of proof, distinguish between literal infringement and the doctrine of equivalents, and cite three recent leading cases that have refined the analysis.”

Using clear language in prompt engineering guides AI to produce more specific results. 

Privacy and Privilege by Default

One factor that differentiates AI from simpler software is the ability to learn over time and adapt based on new input and information. The downside is the potential for your data to be used for training AI systems that travel outside of your firm’s domain. 

Even with the assurance that you’re accessing a fully secure system with zero data retention, it’s best to avoid the use of any identifiable or privileged data. You can do this by: 

• Redacting names 
• Using pseudonyms
• Avoiding all client identifiers other than names

Verify and Document

Verifying sources is particularly important. This practice ensures that sources are appropriate and timely, and confirms that the AI has interpreted and recorded data correctly. To do this: 

• Include a prompt demand that all facts are cited with hyperlinked sources
• Add a human review step to double-check citations and align results
• Keep an issues log of any citing errors

Human Validation Still Matters

Even the most sophisticated legal AI doesn’t get a free pass from human oversight. In fact, pairing AI-generated outputs with attorney review isn’t just a nice-to-have—it’s an essential safeguard to ensure accuracy, context, and defensibility.

AI can rapidly summarize, classify, or draft, but it doesn’t possess real-world judgment, intuition, or the ability to spot when something just feels off. A human reviewer acts as the final filter, catching subtle misinterpretations, outdated citations, or reasoning leaps that might slip through algorithmic cracks.

To make human validation a core part of your legal AI workflow:

• Cross-check citations and case law for accuracy, relevance, and jurisdictional fit.
• Assess tone and nuance, especially for client-facing or adversarial communications.
• Confirm factual coherence, ensuring the output aligns with the matter’s context and goals.
• Flag hallucinations or overconfident conclusions—AI can sound authoritative even when it’s misguided.

Risk and Compliance Must-Dos

It’s especially important for law firms to ensure security and data protection when employing legal AI strategies. For legal prompting, a few risk and compliance essentials include: 

• Keeping a “do-not-enter” data list (e.g., PII, PHI, sealed/privileged content)
• Confirming the software’s data retention settings and policy
• Reviewing access controls
• Ensuring auditability requirements 

Ready-to-Use Prompt Templates 

Having a template vs. starting from a blank page helps with consistency, compliance, and efficiency. Consider preparing prompt templates for common use cases such as: 

• Deposition summaries of various types (e.g., page-line, topical, narrative, etc.)
• Document review and issue tagging
• Contract clause extraction

Each template should incorporate: 

• Goals
• Inputs
• Required citations
• Acceptance criteria

Enter the Future of Legal AI with Confidence

The bottom line is that prompts created within wisely constructed policies and workflows lead to a defensible process that reduces risk related to AI use. Instruct your team on core AI safeguards and best practices, use caution around risk and compliance issues, create firm-wide prompts, and log and track results over time.

Another best practice? Carefully vet and commit to AI-forward vendors. 

Reach out to U.S. Legal Support to explore how we leverage AI and data security throughout our comprehensive litigation support solutions. 

Sources: 

1. Volody. Legal AI Prompting: Best Practices. https://www.volody.com/resource/prompts-for-legal-ai-compliance/
2. ContractPodAI. Mastering AI Prompts for Legal Professionals in 2025. https://contractpodai.com/news/ai-prompts-for-legal-professionals/

Julie Feller

Julie Feller is the Vice President of Marketing at U.S. Legal Support where she leads innovative marketing initiatives. With a proven track record in the legal industry, Juie previously served at Abacus Data Systems (now Caret Legal) where she played a pivotal role in providing cutting-edge technology platforms and services to legal professionals nationwide.