What do law firms ask about AI visibility?

No. OpenAI banned legal-services advertising on ChatGPT in June 2026, alongside other regulated categories. Law firms cannot buy placement, sponsorship, or promoted answers there. The only way a firm appears in ChatGPT responses is organic citation: being the source the model selects when it answers a legal consumer’s question.

Make your firm the easiest credible source to cite: consistent name-address-practice data across the web, LegalService and Attorney schema markup, a question-and-answer content hub that directly answers client queries, and crawlable pages open to GPTBot. ChatGPT recommends firms it can identify, verify, and quote — not firms with the biggest ad budget.

Roughly 28% of legal consumers now start attorney research in AI assistants like ChatGPT, up from single digits two years ago. Adoption skews toward exactly the matters consumer firms want: injury, family, and immigration questions people are embarrassed to ask a human first. Meanwhile fewer than 15% of firms appear in those AI answers.

AEO is the practice of making a law firm citable by AI answer engines — ChatGPT, Claude, Perplexity, and Google AI Overviews — so the firm is named when consumers ask legal questions. It combines entity cleanup, schema markup, AI-crawler access, and question-shaped content, and it is measured in citation share-of-voice rather than rankings.

At FirmCited: a $490 diagnostic audit, a $6,500 Starter install (AEO foundation, 14 days), a $12,000 Pro install adding a 24/7 AI intake chatbot (21 days), and a $2,000/month growth retainer for ongoing content and monitoring. The $490 audit credits in full toward any install within 60 days.

No. Nobody controls what ChatGPT, Claude, Perplexity, or Google AI Overviews say — answers vary by model version, phrasing, and day. Any vendor guaranteeing AI citations or rankings is selling something they cannot deliver. Honest vendors guarantee what they control: deliverables, timelines, response speed, and transparent measurement.

Typically 6 to 16 weeks from fixing the foundations. Perplexity and Google AI Overviews respond fastest — sometimes within weeks of indexing — because they retrieve live web results. ChatGPT and Claude move slower, as citations depend on crawl cycles and model refreshes. No honest vendor promises a specific date.

An AI visibility audit measures whether AI assistants recommend your firm. FirmCited’s version runs 25 realistic client prompts across ChatGPT, Claude, Perplexity, and Google AI Overviews, records every firm cited, computes competitor share-of-voice, and delivers a 10-page prioritized fix list within 48 hours for $490 — credited toward any install.

Four: ChatGPT (largest consumer reach), Google AI Overviews (sits atop existing search volume), Perplexity (fast-growing research assistant with visible citations), and Claude (rising consumer use, quality-skewed audience). A firm optimizing for these four covers the overwhelming majority of AI-assisted legal research in the US today.

AI Overviews increasingly answers “lawyer near me” queries with a generated summary naming two or three firms before any traditional result appears. It draws on Google’s index, Business Profiles, reviews, and schema markup. Firms with consistent local entity data and question-shaped content get named; everyone else is pushed below the fold.

llms.txt is a plain-text file at your site root that gives AI systems a concise, structured summary of who you are, what you do, and which pages matter. It costs minutes to ship, carries zero risk, and several AI crawlers already read it — so for a law firm it is a cheap, sensible default.

Four core types: Organization or LegalService for the firm entity, Attorney for each lawyer, FAQPage on question-and-answer content, and Article on substantive pages with a named author and dates. Schema is how AI engines read your identity unambiguously — it converts marketing copy into machine-verifiable facts.

Under 60 seconds. Legal consumers contact multiple firms and typically retain the first one that responds substantively. Response within a minute can multiply qualification rates several times over versus responding in hours — and most firms take four hours or more. Speed-to-lead is the cheapest conversion lever a firm owns.

Yes — when properly fenced. Ethics rules permit technology-assisted intake as long as the bot never gives legal advice, never forms an attorney-client relationship, discloses it is not a lawyer, and keeps confidences secure. The ethical risk is not the chatbot; it is an unfenced chatbot improvising legal conclusions.

No — and a law-firm chatbot must be engineered so it cannot. Applying law to a specific person’s facts is legal advice; delivered by software it risks unauthorized practice, malpractice exposure, and a relationship no one intended to form. Properly built bots inform, qualify, and schedule — then hand facts-specific questions to a lawyer.

AI share-of-voice (SoV) is the percentage of AI-generated answers that cite your firm across a fixed panel of realistic client queries. Run 25 prompts across four engines: if your firm appears in 12 of 100 engine-answers and a competitor in 30, your SoV is 12% against their 30%. It is the core KPI of AI visibility.

Almost always: their web footprint is machine-readable and yours is not. They have consistent entity data across directories, schema markup, crawlable pages, and content that answers client questions directly — so models can identify, verify, and quote them. It is rarely about firm size or reputation; it is about legibility to machines.

No. Paid search ads have zero influence on whether ChatGPT, Claude, Perplexity, or Google AI Overviews cite your firm — AI answers are generated from organic signals, and OpenAI banned legal ads outright. Ads still buy clicks on Google, but every ad dollar leaves your AI-channel invisibility exactly where it was.

Content that answers a real question directly, early, and verifiably: a question-form heading, a complete 40-60 word answer up front, supporting specifics (numbers, statutes, dates, named tools), a table, schema markup, a named author, and a visible update date. LLMs quote sources that make extraction effortless — not the longest or prettiest page.

Track three linked numbers: citation share-of-voice on your money queries (the leading indicator), AI-referred leads — from ask-how-they-found-you intake plus assistant referral traffic (the middle), and retained cases from that channel against average fee value (the result). One retained consumer case typically repays an entire year of AEO investment.