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AI prompts for personal injury lawyers

Proving liability, causation, and the full measure of damages for an injured client. Every prompt on this page carries that emphasis. Pick a workflow and add only the details the assignment needs, using neutral labels where possible.

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A complete example prompt

The Personal injury — plaintiff lens adds this practice context to every template: This work product supports plaintiff's case: establishing liability, causation, and the full measure of the client's damages.

Here is one complete example: the “Build the treatment story from the records” workflow with medical records as the source. Run it on your own file in Ask your files, or copy it into an AI tool your firm approves.

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Build the treatment story from the records · Medical records

Synthetic example: Names, dates, organizations, and matter details are fictional placeholders, not a real case record.

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CONTEXT:
You are a litigation support analyst assisting plaintiff's personal injury counsel in a motor vehicle negligence claim matter. The attached production is the medical records of Alex Morgan. The incident at issue occurred on January 15, 2025. The injuries and conditions that matter are: fault; notice; causation; damages. This work product supports plaintiff's case: establishing liability, causation, and the full measure of the client's damages.

INSTRUCTIONS:
Build a complete treatment chronology covering every encounter in the production — visits, imaging, procedures, therapy sessions, and telephone encounters. For each encounter capture: provider and facility; date of service; presenting complaints in the patient's words where recorded; objective findings; diagnoses exactly as stated in the record (do not supply diagnoses or codes the record does not state); treatment rendered; medications; work or activity restrictions; and the next-step plan. Separately and explicitly:
1. Flag every gap in treatment longer than 30 days.
2. Flag every reference to symptoms, injuries, or treatment pre-dating January 15, 2025.
3. Collect every causation statement — any provider language attributing or declining to attribute a condition to the incident — verbatim.

In this engagement, additionally: Give particular weight to provider language on causation, permanency, impairment, and future care needs, and to consistent symptom reporting across providers over time.

TEMPLATE — format your output exactly as follows:
## Chronology
| Date | Provider / facility | Complaints | Findings | Diagnoses (as stated) | Treatment / meds | Restrictions | Cite |
|---|---|---|---|---|---|---|---|
## Treatment gaps (> 30 days)
| Gap | Last visit before (cite) | First visit after (cite) |
|---|---|---|
## Pre-existing / prior history references
| Date | Provider | Verbatim reference | Cite |
|---|---|---|---|
## Causation statements (verbatim)
| Date | Provider | Exact language | Cite |
|---|---|---|---|

## Permanency & future care language (verbatim)
| Date | Provider | Exact language | Cite |
|---|---|---|---|

EVIDENCE REQUIREMENTS:
For every entry, cite provider, date of service, and the page or Bates number of the source record. Record diagnoses and causation language exactly as written — never normalize, upgrade, or infer a diagnosis, and never supply an ICD code the record does not contain. If a record page is illegible or an encounter is referenced but missing from the production, list it under a final heading "Missing or illegible — request from provider" rather than guessing at its contents.

Unless a section above specifies its own marker, write "not found in the record" wherever the provided record does not support a requested finding. Do not infer or fill gaps from outside knowledge.
The scope is limited to the requested task, stated issues, and provided record. Do not introduce outside subjects or sources.
A human reviewer must verify every material statement and citation against the source record before relying on or sharing the output.

Every template in the library assembles like this with the Personal injury — plaintiff lens: open the builder and add only the assignment details needed, using neutral labels where possible, or read the Attorney's Guide to AI Prompting for the method behind it.

What this lens changes in each task

Extract from the record
Prioritize testimony establishing notice and fault, admissions about the mechanism of injury, and the human impact of the injuries — pain, limitations, and life disruption in the witness's own words.
Build a chronology
Give particular weight to provider language on causation, permanency, impairment, and future care needs, and to consistent symptom reporting across providers over time.
Find contradictions
Focus on locking defense witnesses into accounts that conflict with the physical evidence or their own documents, and note wherever a defense account has shifted between tellings.
Summarize the record
Surface testimony supporting each liability element and each category of damages, and flag favorable concessions prominently rather than burying them in sequence.
Draft from the record
Write toward a coherent narrative of fault and harm; specificity about the client's documented losses carries the persuasion — never adjectives.
Interrogate the file
Whenever an answer touches damages, state whether the record quantifies them and where; unquantified damages are follow-up work, so flag them.

Common questions

How can personal injury lawyers use AI for a medical chronology?

Personal injury lawyers and paralegals can use AI to draft a medical chronology that pulls causation, permanency, and future-care language verbatim from the records. Every entry should cite the provider, service date, and page or Bates number, and a person on the plaintiff’s team checks each entry before it supports a demand or an expert.

Can AI help draft the facts section of a demand letter?

Yes. AI can draft the facts section of a personal injury demand letter from the medical records, bills, and testimony, with a citation behind every sentence. Gaps in the record should be listed rather than filled in. The attorney verifies each cited fact and decides on tone, damages figures, and what the demand includes.

How do I find admissions in a defense deposition with AI?

Ask the AI to extract admissions from the defense witness’s deposition as verbatim question-and-answer pairs, each with a page:line cite, grouped by issue such as notice, fault, and mechanism of injury. In personal injury work, a paralegal or attorney then reads each cited exchange in context before treating it as an admission.

Worked examples for this practice

Each pairs one template with this practice’s emphasis, end to end.

More template guides

Read the general guide for each workflow below. To apply the Personal injury — plaintiff context to your own facts, use the builder actions above.