Morgan & Morgan is named on every engine except Perplexity. Eighty other firms split the rest.

When a prospective claimant asks AI to name a personal-injury law firm, the five major engines produce the most fragmented shortlist we have measured. In our May 2026 pilot, 80 firms were named across six buyer-intent prompts (mass torts, product liability, catastrophic injury, motor-vehicle, workplace and toxic exposure, wrongful death). Mean inter-engine overlap of 0.24 — lower than commercial insurance brokers (0.38), lower than wealth-management RIAs (0.32). Morgan & Morgan is the closest the engines come to consensus, named on roughly 83% of ChatGPT, Claude, and Gemini buyer prompts; Perplexity surfaces a different roster entirely, dropping Morgan & Morgan to roughly 17% and leaning toward mass-tort specialty firms (Motley Rice, Simmons Hanly Conroy, Lieff Cabraser Heimann & Bernstein). This page reports observed surfacing under ABA Model Rule 7.1 and 7.2 constraints — observational language only, no comparative or capability claims about any named firm.

The shift we keep hearing

Paid acquisition for PI firms continues to escalate. Local-broadcast and out-of-home buys still drive measurable intake, but the per-acquisition cost has trended in one direction. Search-engine paid placements have similarly tightened. What has changed: a growing share of pre-call research is happening inside AI chat interfaces. Prospective claimants ask AI which firms handle their case type, in what states, with what experience — and the firms that surface enter the consideration set.

The shortlists those engines produce, however, are not consistent with each other. Our pilot capture shows the engines treat “personal injury” as a category with a strong national brand and a long tail of specialty plaintiff firms, but they disagree sharply on which specialty firms to surface. Morgan & Morgan is the closest thing to a unanimous answer — and Perplexity is the systematic exception. For a multi-state PI practice or a mass-tort plaintiff firm, the practical question is which engines are surfacing the firm in which buyer scenarios, and what the closeable gap looks like.

What we found when we asked AI to recommend a personal-injury law firm

In late May 2026 we ran a bounded pilot capture — six buyer-intent prompts covering multi-state product-liability, catastrophic injury, class-action settlements involving defective pharmaceuticals and medical devices, motor-vehicle accident regional representation, workplace injury and toxic exposure, and wrongful-death/mass-tort litigation — on five AI engines (ChatGPT, Claude, Gemini, Perplexity, Grok), three runs each (90 captures, scored line by line). The category is the most fragmented in our research to date.

Morgan & Morgan is the closest the category produces to a unanimous national-brand answer. It surfaces on every ChatGPT run of nearly every prompt (~83% of relevant prompts), on Claude (~83%), and on Gemini (~83%). Perplexity drops it sharply to ~17%; Grok shows it at ~50%. Where Perplexity does not surface Morgan & Morgan, it surfaces mass-tort specialty firms instead — Motley Rice, Simmons Hanly Conroy, Lieff Cabraser Heimann & Bernstein — firms known for product-liability and class-action litigation rather than general PI intake.

The other surfaced firms split widely by buyer scenario. Weitz & Luxenberg is named for mass-tort and pharmaceutical class actions on ChatGPT and Claude. Beasley Allen surfaces on Claude for catastrophic-injury and product-liability prompts. The Lanier Law Firm is named on Claude for class-action prompts. The Cochran Firm appears on ChatGPT and Claude for motor-vehicle and catastrophic-injury scenarios. Each engine has a different second-tier of firms it routinely surfaces. This is observed AI behavior; it is not a ranking, a recommendation, or a capability claim about any firm.

Five engines · five shortlists Prompt: class-action settlements involving defective pharmaceuticals or medical devices (PIL-03)

Four different rank-1 firms across five AI engines on a single buyer prompt. The full per-prompt exhibit, with the same fragmentation pattern across motor-vehicle, workplace, catastrophic-injury, and wrongful-death scenarios, is in the Answerability Index entry for Personal Injury Law Firms.

If your diagnostic shows a similar gap, here is what we usually recommend building

For multi-state personal-injury firms and mass-tort plaintiff practices, the typical post-Diagnostic build queue is six to eight specific assets — all written in observational, hedged language compatible with state-bar advertising-rule review (ABA Model Rule 7.1):

• Three to five practice-area pages for the case types where AI names a competitor instead of your firm — mass torts, multi-state product liability, catastrophic injury, motor-vehicle, workplace and toxic-exposure, wrongful death. Specific legal terminology, named case-type taxonomy, no superlative claims.
• Entity-graph cleanup — consistent firm identity across Best Lawyers, Super Lawyers, AAJ membership directory, state-bar registries, your site, Wikidata, LinkedIn, and court-record databases. The engines stop fragmenting your firm across variant names.
• Citation assets — peer-recognition submissions (Best Lawyers, Super Lawyers, AAJ Top 100 applications), mass-tort trade-press placements (Law360 mass-tort coverage, Justia firm profiles, court-record case citations).
• Competitor-comparison pages — your firm vs the consensus players (Morgan & Morgan / Motley Rice / Simmons Hanly Conroy / Lieff Cabraser / Beasley Allen) for the practice areas you compete on. Hedged, observational, no comparative quality claims.
• Schema package — Organization, LegalService, FAQPage, BreadcrumbList, named-attorney biographies with bar admissions and AAJ membership. Ship-ready JSON-LD with no attorney-advertising violations.
• FAQ expansion — passage-citable answer blocks (134–167 words each) on the practice-area questions prospective claimants actually ask, with state-bar-compliant hedged language throughout.

Build it in-house from the Diagnostic, or have us build it — a Sprint engagement ($15,000 then $950/mo) is done-for-you remediation over four weeks, with all output staged for your state-bar advertising-counsel review before any external publish. We make no comparative claims about your firm and ship nothing that violates Rule 7.1 / 7.2. Either way, the Diagnostic is the prerequisite.

Order the Diagnostic to see your specific build queue — $2,500 →

Why PI surfacing fragments — and what to do about it

Three structural reasons. First, the category has both a brand-dominant national firm (Morgan & Morgan) and a long tail of mass-tort and product-liability specialty practices — the engines have to decide whether the buyer wants the general national firm or a specialty plaintiff firm, and they decide differently. Second, state-bar advertising rules (ABA Model Rule 7.1, state-by-state variations on attorney advertising and superlative claims) constrain the language firms can use about themselves, so the brand signals the engines can lift are intentionally hedged. Third, the corroborating sources fragment: Best Lawyers, Super Lawyers, AAJ membership lists, court-record databases, mass-tort litigation press, and state bar disciplinary records each contribute different signals, weighted differently per engine.

The result is the lowest cross-engine consensus we have measured. The Diagnostic reads where your firm sits and locates the gap in three places.

Pillar	The question we answer	What we look for in a PI firm site
Content	Can the engines extract practice-area substance from your site?	Server-side-rendered practice-area pages with the specific legal terminology and case-type taxonomy buyers use (“3M Bair Hugger litigation,” “PFAS exposure class action,” not just “Mass Torts”); named attorneys with bar admissions, AAJ membership, and relevant credentials; verdict and settlement notices in the form the engines can lift while respecting state-bar disclosure rules.
Retrieval	Do you appear when claimants actually run the buyer-intent prompts?	Observed surfacing across the prompts that match your practice mix, on the engines prospective claimants use. Measured per prompt, per engine; reported with the hedged observational language that state-bar advertising review expects (“observed surfacing,” “named in N of 3 runs”).
Trust	Are you corroborated in the sources these engines weight?	Presence in Best Lawyers, Super Lawyers, AAJ Top 100, state-bar discipline-clean records, mass-tort and product-liability trade press, and court-record databases for representative cases. Named-but-not-cited gaps where an engine knows your firm exists but does not surface it on a relevant query.

The intake call still runs on your own screening criteria. The consideration set that gets to that intake call is being assembled, inconsistently, by five engines that disagree on which firms belong on it.

What you receive

Built for

Multi-state personal-injury law firms, mass-tort plaintiff firms, multi-location PI practices, and product-liability litigation groups — partner-led firms already investing in legal marketing, intake operations, and AAJ / Best Lawyers / Super Lawyers recognition who need to know how AI surfacing maps to their practice areas and state-bar advertising posture.

Order the Diagnostic

Find out which engines surface your firm on which practice areas — and which do not.

Delivered in 10–14 business days. Five engines. Thirty to fifty buyer-intent prompts measured for your specific firm, scoped to your state-bar admissions and practice areas. Confidential under MNDA. The first month is the full Diagnostic; thereafter the Visibility Intelligence subscription keeps the picture current as the engines move. Report uses observational, hedged language compatible with state-bar advertising-rule review; we make no comparative claims about your firm and no public-facing statements without your counsel’s review.

Order your Diagnostic — $2,500 See the underlying capture →

$2,500 first month (the Diagnostic) · $950/mo thereafter (Visibility Intelligence: monthly re-runs, deltas, build-queue updates)

A note on scope and state-bar advertising compliance. Attorney advertising is regulated state-by-state under variations of ABA Model Rule 7.1 (prohibiting false, misleading, or comparative claims) and Rule 7.2 (constraints on testimonials and endorsements). The Diagnostic measures observed AI surfacing — what the engines say when asked — not the firm’s capabilities, case results, settlement amounts, or quality. The report is internal intelligence for your firm; it makes no superlative statements about your firm (no “best,” “top,” “most successful,” or comparative claims), no statements that could be construed as testimonials or endorsements, and no specific case-outcome predictions. Public-facing marketing or website language derived from the report remains subject to your firm’s state-bar advertising-rule compliance review before any external use. Nothing on this page is legal advice, attorney advertising, or a solicitation. Surfacing patterns reflect the engines’ current behavior on the captured date and will change as the engines and the underlying public sources change. Capture: 2026-05-30. Six buyer-intent prompts, five engines, three runs per engine (90 captures total). Firm names canonicalized; firms named only by a single engine summarized in the Index entry, not named individually here.