AI for Law Firms: Where It Helps, Where It Does Not, and How to Start

Most firms now have someone asking whether the practice should be using AI. The honest answer is yes for some work and no for other work, and the difference matters more than which tool you pick. Used well, AI takes hours of drafting, summarizing and admin off a busy team. Used carelessly, it produces confident mistakes with the firm's name on them.

This guide covers where AI genuinely helps an injury practice, where it should not be trusted, what the ethics rules expect, and a sensible way to start.

What AI is good at in a law firm

Today's AI tools are strongest at work that involves reading, summarizing and producing a first draft that a person then checks. In an injury practice that includes:

• Summarizing medical records. Turning a long stack of records into a treatment timeline that a case manager reviews against the source. The guide to medical records retrieval covers getting the records in the first place.
• First drafts. Demand letters, client letters, routine correspondence and discovery responses, written from the firm's own templates and facts and then edited by a lawyer. The guide to personal injury demand letters covers what a strong demand needs.
• Intake support. Capturing the details of a new enquiry, flagging missing information and helping staff follow up quickly, with a person still making the decision on the case.
• Admin and marketing work. Meeting notes, internal summaries, website and article drafts, and answers to routine questions from staff.

Where AI should not be trusted on its own

AI writes fluently whether or not it is right. That is the core risk. Keep a qualified person responsible for:

• Legal research and citations. General AI tools can invent cases and quotes that look real. Courts have sanctioned lawyers for filing briefs with citations that did not exist. Check every authority against a primary source.
• Case valuation and strategy. AI can organise the facts, but deciding what a case is worth and how to run it is a lawyer's judgment.
• Anything sent to a court, an insurer or a client without review. Nothing leaves the firm until a person has read it.
• Final decisions on whether to take a case. Screening help is useful; the decision stays with the firm.

The ethics rules that apply

The ABA addressed generative AI directly in Formal Opinion 512 in July 2024, and many state bars have issued their own guidance. The themes are consistent and they are existing duties applied to a new tool:

• Competence. Understand what the tool does and its limits well enough to use it responsibly.
• Confidentiality. Know where client information goes when you type it into a tool, whether it is stored, and whether it is used to train anything. Some uses need client consent.
• Supervision. Lawyers remain responsible for work produced with AI, including work done by staff using it.
• Fees. Bill fairly for time actually spent, and be clear about how AI costs are handled.
• Candor. Anything filed with a court must be accurate, however it was drafted.

Check your own state bar's guidance before rolling anything out, since some states go further than the ABA opinion.

How to choose a tool

Start with the problem, not the product. Pick one task that eats staff time today, then ask any vendor:

• Where is our data stored, who can see it, and is it used to train the model?
• Does it work with the case management and CRM systems we already use?
• Can it show where an answer came from, so staff can check it against the source?
• What happens to our data if we stop using it?

Tools built for legal work usually answer these questions better than general consumer chat tools. The guide to personal injury case management and the guide to law firm CRMs cover the systems an AI tool needs to fit into.

A sensible way to start

1. Write a short policy. Which tools are approved, what client information may go into them, and the rule that a person reviews everything before it leaves the firm.
2. Pick one task and one team. Medical record summaries or first-draft correspondence are common first choices.
3. Measure before and after. Time spent per file, errors caught in review and how staff feel about it. The guide to law firm KPIs covers setting up the numbers.
4. Train the team. Show people what good use looks like and what mistakes to watch for.
5. Expand only what works. Add the next task once the first is reliable.

Common mistakes

• Pasting client information into a consumer tool without checking how it handles data.
• Trusting citations or quotes without checking the source.
• Buying a platform before deciding what problem it should solve.
• Rolling out to the whole firm at once with no policy or training.
• Expecting AI to fix a process that was already broken, such as slow intake follow-up.

The short version

AI is useful for law firms when it drafts, summarizes and organises work that a qualified person then checks. Keep research, valuation, strategy and anything that leaves the firm under human review, follow your bar's guidance on competence and confidentiality, and start with one task, one team and a clear policy. Expand what works, and drop what does not.