AI Legal Research for Criminal Defense Attorneys

Legal research is one of those tasks that can eat an entire afternoon. You're looking for cases on a suppression issue in Pennsylvania, you find something promising, you follow the citations, you realize half of them are from circuits that don't bind you, you circle back, and an hour later you have three good cases and a headache.

AI doesn't fix the law. But it's getting genuinely useful at cutting down that kind of research time — if you know how to use it and what its limits are.

I've been paying attention to how criminal defense attorneys are actually using AI for research, and there are a few patterns worth knowing about.

What AI Is Actually Good At Here

Let me be direct about this, because a lot of what gets written about AI and legal research is either overblown hype or dismissive hand-waving.

AI language models — ChatGPT, Claude, Gemini — are good at a specific kind of task: summarizing and synthesizing text they've been trained on. That makes them useful for:

Getting oriented fast. If you're handling a charge you don't work with every day — say, a federal gun charge or a drug trafficking conspiracy — you can ask an AI to explain the elements, the key defenses attorneys typically raise, and the major cases in that space. You get a working map of the territory in ten minutes instead of forty-five.

Finding angles you might not have thought of. Ask an AI "what are the strongest arguments for suppression in a stop-and-frisk case in Pennsylvania?" and it will pull together a range of theories — Fourth Amendment standing issues, particularity problems, good faith exceptions and their limits — that you can then go verify. It's like brainstorming with a well-read research assistant who never gets tired.

Drafting initial research memos. If you want a starting framework for a brief section, AI can produce a rough draft based on the legal framework you describe. You'll rewrite it. But having something to react to is faster than starting from a blank page.

Explaining complex doctrine in plain terms. When you need to explain Brady obligations or the specifics of a Miranda issue to a client in writing, AI is good at generating plain-language summaries you can then adapt.

What AI Is Not Good At

This part matters more.

AI makes up cases. This is the big one. If you ask ChatGPT to find Pennsylvania Supreme Court cases on a particular suppression issue, it will sometimes produce citations that look real — case name, reporter citation, everything — but don't exist. This is called hallucination, and it's a known problem with all current AI models.

If you use an AI to find cases and you don't verify every single citation in an actual legal database, you will eventually cite a fake case. That has happened to attorneys who didn't know to check. Don't be one of them.

AI's knowledge has a cutoff. Most general AI tools don't know about cases decided in the last year or two. If you're researching a developing area of law — challenges under Bruen, post-Dobbs implications, recent Fourth Amendment decisions — you need a live legal database, not a language model.

AI doesn't know your jurisdiction's quirks. It knows broad federal doctrine and general state law patterns, but it doesn't know that Judge Martinez in Philadelphia Criminal Term runs his suppression hearings a certain way, or that Montgomery County's local rules have a specific wrinkle that matters for your case. That local knowledge lives in your head, your colleagues' heads, and the actual court records.

The Tools That Are Purpose-Built for Legal Research

General AI tools like ChatGPT are useful for orientation, but there are AI-powered tools built specifically for legal research that solve the hallucination problem.

Westlaw AI and Lexis AI — both of the major legal databases now have AI features built directly into their platforms. When you ask them a research question, they pull from their verified case law databases and cite real cases. The answers are grounded in actual sources you can click through immediately. If you already have a Westlaw or Lexis subscription, this is the safest place to start using AI for legal research.

Casetext/CoCounsel — Acquired by Thomson Reuters and now integrated into Westlaw, CoCounsel was one of the early AI tools built specifically for lawyers. It's good at drafting research memos, reviewing documents, and deposition prep.

Harvey — More enterprise-focused, used by larger firms, but worth knowing about as the space evolves.

The pattern with all of these: they're grounded in verified legal databases, so you don't get the hallucination problem the same way you do with general AI tools.

How I'd Actually Use AI in a Criminal Defense Practice

Here's a practical workflow that makes sense for a small criminal defense firm in Pennsylvania:

Step 1: Use general AI to get oriented. Before you open Westlaw, spend ten minutes with Claude or ChatGPT. Describe the case, describe the issue, ask for a framework. "My client was stopped at a SEPTA checkpoint. No reasonable suspicion. Evidence was seized. What are the strongest suppression arguments and what's the key doctrine I should be researching?" You'll get a map. You still need to verify everything, but you know where to look.

Step 2: Use a legal database for actual research. Westlaw, Lexis, or Google Scholar (free, but less comprehensive) for finding real cases. If your database has AI features, use them — but still click through to the actual opinions.

Step 3: Use AI to draft the framework. Once you have your cases, describe the issue and the key cases to Claude or ChatGPT and ask for a draft of the argument. You'll rewrite it heavily, but the structure helps.

Step 4: Verify everything before it goes out the door. Every citation, every quote, every characterization of a case's holding. AI is a research assistant, not a research service. The professional obligation to verify stays with you.

This workflow cuts research time without cutting corners. The orientation step alone — getting a map of the legal territory before you start digging — saves a surprising amount of time.

The Schatz & Stancu Context

Schatz & Stancu LLP is a criminal defense firm in Philadelphia that's been using automation to cut administrative overhead — their docket monitoring system turned three days of manual checking per week into a two-minute nightly summary.

Legal research is the next frontier. Not replacing attorney judgment — there's no tool that does that — but removing the time that gets consumed orienting yourself, running down dead ends, and drafting frameworks from scratch. A solo attorney or small firm that shaves two hours off research time per case has more time for the work that actually wins cases: the client relationships, the motion strategy, the courtroom prep.

That's what good automation does. It handles the parts of the work that don't require your specific expertise so you can focus on the parts that do.

One Caution Worth Repeating

Because it bears repeating: AI hallucinates. It makes up case citations that look real. If you use AI in your legal research workflow and you don't verify every citation against an actual database, you will eventually be in a position you don't want to be in.

Use AI to think, to orient, to draft. Use real databases to verify. That division of labor is what makes AI genuinely useful in a legal practice without creating malpractice risk.

Where to Start

If you're a criminal defense attorney in the Philadelphia area and you want to start experimenting with AI for research, start simple. Pick your next suppression motion. Before you open Westlaw, spend ten minutes asking ChatGPT or Claude to orient you on the issue. Then do your normal research and see how much of the territory you'd already mapped.

Most attorneys who try this once keep doing it. It's not magic — it's a faster starting point.

If you want to talk about how AI fits into your firm's broader workflow — research, intake, docket monitoring, anything that's eating your team's time — reach out. That's what we do at Schatz Consulting: practical automation for small law firms, built around how you actually work.