Ask AI for a lawyer, and 95% of firms aren’t in the answer

Each engine was asked “Who are the best [practice] lawyers in [city]?” for family, employment, real estate, wills and estates, corporate, criminal, immigration, personal injury, tax, and charity and nonprofit law. A firm counts as named if it appeared in at least one of three runs.

The answers aren’t stable. When ChatGPT named one of our sampled firms for a question, it named the same firm in all three runs only 2 times out of 11. Google showed no AI Overview at all for 48% of the questions. City differences aren’t statistically significant.

We counted seven terms (best, top, leading, premier, #1, expert, specialist) when a firm used them about itself without naming a source, such as an award or a directory. “Expert” was the most common in every city. Testimonials, named awards, certified-specialist statements and phrases such as “best interests of the child” weren’t counted.

The rules differ by place. The Law Society of Ontario treats superlatives such as “best” and “#1” as rankings, which must be genuine and provable, and reserves “specialist” for Certified Specialists. Florida’s Bar says “the best” is generally not objectively verifiable, and allows “expert” only when it can be. New York and California prohibit false or misleading communications and warn that unsubstantiated comparisons may mislead. They allow an uncertified lawyer to say they specialize. Dropping “specialist” from the US cities changes the overall figure from 35% to 34%.

A term on this list isn’t a violation. Only a regulator decides that, and a claim may be true and provable.

Firms that used these terms were not measurably more likely to be named by an AI engine (odds ratio 1.70; 95% CI 0.51–5.60; adjusted for city and firm size). That difference isn’t statistically significant. With only 13 firms named, the estimate is too imprecise to say whether the claims help, hurt or make no difference.

New York’s rules required a firm’s home page to carry the label “Attorney Advertising” until June 1, 2026, when the requirement was repealed. Four months later, 34% of New York City firm home pages in our sample still carry it. A check of a random 20% of pages matched the automatic count. A full re-scan of all 70 pages found and fixed one label the parser had missed; it is included in the 34%.

• Sample: 22,406 Google Business listings for lawyers and law firms in four metros. From the 5,313 eligible firms with their own website, we drew a seeded random sample of 80 per metro. 262 sites were reachable and analysable. Listings, not search rankings, so the sample isn’t tilted toward firms that already rank.
• Websites: each firm’s home page and up to four linked pages, fetched politely (robots.txt respected, one request per second per site).
• Classification: 1,602 term mentions, each classified independently by two AI models (Gemini 3.8 Flash and GLM 5.3 Flash). Against a 200-item reference set of Ontario firms, the two agreed on 193 items and were correct on 96.9% of those. On a 150-item US reference set (New York, Miami and the Bay Area), the labels accepted automatically were 99.3% accurate (weighted); all three errors over-counted claims. The 53 mentions where they disagreed or had low confidence were decided by a third AI model (Claude), with a written reason for each.
• AI answers: 479 of 480 planned answers collected on October 1, 2026 through DataForSEO (ChatGPT and Gemini app scrapers, Perplexity Sonar, Google AI Overviews). Firms were matched by domain and normalized name.
• Method fixed in advance: the method was written and hashed (SHA-256) 10 minutes before data collection began (02:44 and 02:54 UTC, October 1, 2026). The hash wasn’t registered with a third party at the time. Every later change is in the deviations log.

Pre-registration · Deviations log · Rule-wording review

• Coverage: Google Business listings miss firms without a profile.
• Volatility: AI answers change with time, location and wording. We asked one question per practice area, on one day.
• Location: ChatGPT could only be set to a country, not a city, so the city was in the question. Perplexity takes no location.
• Size bands: firm size could be detected for only 58 of 262 firms.
• Classifier accuracy: it was measured on 200 Ontario mentions and 150 US mentions, both labelled by AI models rather than people. Its errors on US sites all over-counted claims, so the self-claim figures may be slightly high.
• AI review, not human: the reference set, the disputed mentions and the New York check sample were reviewed by AI models, not people.
• Rule descriptions: checked against primary sources by an AI, not reviewed by a licensed lawyer. This page is general information, not legal advice. Rules checked October 1, 2026.

Innovara Studios is a brand, website and search studio. We sell services to law firms, so we have an interest in this topic. No firm or person is named in this study, its charts or its dataset, and no firm paid for or saw it before publication.

• Downloads: Anonymized dataset (CSV, 262 firms)
• Licence: CC BY 4.0. Reuse it, with credit.