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Research 8 min read Updated September 26, 2026

What does AI cite when people search for a lawyer?

In short

On 2026-09-26 we ran five legal buyer prompts through gpt-5.1 with web search on. It attached 34 citations: 19 to law firms' own websites and 15 to directories and review sites. Injury and immigration prompts were answered almost entirely from firm sites; the divorce and criminal defence prompts were answered from aggregators, a regulator's directory and a bar association listing, with no firm site cited at all.

Key facts

  • Five prompts were run once each on 2026-09-26 through gpt-5.1 with the web search tool on: personal injury lawyer in Toronto after a car accident, best family lawyer for divorce in Vancouver, criminal defence lawyer recommendations in Calgary, immigration lawyer in Chicago for a work visa, and estate planning attorney in Dallas.
  • The model attached 34 citations across the five answers; every prompt had at least four.
  • The Toronto injury prompt cited six hosts, all law firm websites, and the Chicago immigration prompt cited five, all law firm websites; between them they account for eleven of the nineteen own-site citations.
  • The Vancouver divorce prompt cited only a reviews platform and a ratings aggregator; the Calgary criminal defence prompt cited a defence lawyers' association directory, the provincial law society's directory and two local listing sites, and no firm site.
  • The Dallas estate planning prompt was the most mixed: eleven citations including Avvo, Justia, Super Lawyers and Expertise.com alongside seven firm websites, and the answer itself pointed the reader to those directories to compare more lawyers.

What we asked and how the study works

On 2026-09-26 we sent five legal prompts, one run each, to gpt-5.1 with its web search tool on, and recorded every URL the model attached to its answer. We sorted each cited host by type using our own simple rules: a firm's own site, a directory or review site, a news, reference or government site, Reddit, or social. The categories are our own; the cited hosts are exactly what the model returned.

The prompts were written the way a person would type them: personal injury lawyer in Toronto after a car accident, best family lawyer for divorce in Vancouver, criminal defence lawyer recommendations in Calgary, immigration lawyer in Chicago for a work visa, and estate planning attorney in Dallas.

What each prompt cited

Toronto injury: seven citations to six firm sites, diamondlaw.ca, gluckstein.com, salehilaw.ca, trlaw.com, vclawyers.ca and zwiebelandassociates.ca. The answer named those firms and gave a checklist of questions for the first call. No directory was cited.

Vancouver divorce: seven citations to two hosts, reviews.birdeye.com and trustanalytica.org, both aggregators of reviews and ratings. The answer named several family law firms drawn from those pages and told the reader to shortlist three or four and book brief consultations.

Calgary criminal defence: four citations, to cdla.ca, a defence lawyers' association, lawsociety.ab.ca, the regulator's directory, and two local listing sites, mysage.ca and theseeker.ca. The answer suggested using the law society search with the city filter and asking how much of a lawyer's practice is criminal defence.

Chicago immigration: five citations, all firm sites, chicagoimmigration.net, millalegal.com, mmhpc.com, physicianimmigrationattorney.com and simvisa.com, with the answer sorting firms by focus. Dallas estate planning: eleven citations, four to directories, attorneys.superlawyers.com, avvo.com, expertise.com and justia.com, and seven to firm sites including holmanlawllp.com, robbinsestatelaw.com, srtxlaw.com, wickphillips.com, wrightlegaltexas.com, zabyfirm.com and estateplanningdfw.law.

The pattern: practice area decided the source

Where firms publish detailed practice pages about a specific problem, a car accident, a work visa, the model cited the firms directly and built its list from them. Where the question was broad, best family lawyer, criminal defence recommendations, it leaned on aggregators, a regulator's directory and an association list, and named firms from those pages instead. Estate planning sat in the middle, with the model citing both directories and firm sites and telling the reader to use the directories to compare further.

By our sorting, 19 of 34 citations were firm sites and 15 were directories or review sites, with nothing from news, government beyond the law society, Reddit or social. Two prompts produced every own-site citation but two.

What a law firm can do with this

First, the directories the model cited are the ones to be complete and accurate on: Avvo, Justia, Super Lawyers and Expertise.com in the US, the law society directory and local associations in Canada, plus the review platforms whose pages were cited. Second, a firm's own pages get cited when they answer a specific problem plainly, what to do after a car accident, how a work visa case proceeds, so the practice pages that describe one situation each, in plain words, are the pages a browsing model reaches for. Third, the model's own checklists, how much of the practice is this area, who will handle the file, free consultation, fees, are the questions a firm's pages should answer up front.

SearchPod builds those pages for law firm clients within the advertising rules of the relevant bar or law society, keeps directory listings consistent, and tracks which prompts cite the firm with a fixed prompt panel.

What this cannot tell you

Five prompts, each run once, through one model on one day. Another day, model or wording would produce different citations, and the host sorting is ours. The firms the model named are recorded only as what it said; nothing on this page verifies or endorses any firm, and nothing here is legal advice.

Related questions

Sources

one model with web search, one run per prompt, one date; host types are sorted by SearchPod's own rules; names are recorded as the model wrote them and are not verified or endorsed; nothing here is legal advice; SearchPod sells AI visibility work.

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