GEO for law firms: be the firm AI names.
Not the one it skips.

GEO for law firms, or generative engine optimization for legal, measures whether a firm appears in the answers AI engines give when someone asks for a lawyer, then strengthens the public evidence those engines may retrieve and cite. The work can include Attorney and LegalService schema, bar admissions, sameAs links, legal directories, practice-area content structured for extraction, and independent corroboration. No markup or citation can guarantee inclusion, and every claim remains subject to the applicable advertising rules.

Law firm SEO focuses on visibility in Google's search results so a searcher can click through to your site. GEO measures whether the firm appears inside AI-generated answers and strengthens the public evidence those systems may retrieve or cite. The two overlap because practice-area pages, schema, reviews and authority can support both. GEO adds prompt baselining, entity resolution, extractable answer content and source-level observation. We run law firm SEO and GEO together, not as a substitution.

Prospective clients can use AI assistants during the research stage for questions such as what to do after a collision, how legal fees work, or which type of lawyer handles a matter. Some answers may mention firms before the person reaches a search-results page. The Outrigger AI Visibility Index, a Q1 2026 study of 95,392 data points across 1,004 businesses, reported 65.9% of the businesses in its study effectively invisible in AI search. That market baseline does not predict any individual firm's visibility or commercial outcome.

Five surfaces commonly matter: ChatGPT, Perplexity, Gemini, Claude, and Google's AI Overviews. Their outputs can draw on model knowledge, live retrieval, and entity resolution, but the exact source mix varies by engine, prompt, and date. For a law firm, useful controllable inputs include crawlable practice-area content, Attorney schema, bar admissions, consistent NAP across Justia, Avvo, Martindale, and Google, and independent corroboration. We baseline the priority prompts and record which sources each engine actually cites rather than claiming to control its model weights.

It has to, and this is where most generalist GEO shops create real exposure. Content optimized for AI extraction still has to satisfy ABA Model Rule 7.2 and state-bar derivatives: no misleading claims, no uncertified specialization claims, required past-results disclaimers, mandatory firm-name and address disclosure. Florida, California, Texas, and New York run stricter regimes than the ABA baseline. An AI-optimized case-result line that reads cleanly to a language model can still trigger a bar grievance if it states a dollar figure without the required disclaimer. We build the same state-bar-aware compliance review into GEO content that we use for legal SEO: disclaimer logic at the template layer, dollar-amount policy per jurisdiction, specialization claims gated behind certification. Compliance is part of the workflow, not a checkbox at the end.

We use Outrigger, a separate joint venture Joel co-founded with Andrew, to monitor a set of legal queries across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews on a weekly cadence. For each query we track whether your firm was mentioned, whether it was cited with a link, the context and sentiment of the mention, and which source the engine pulled from. Then we benchmark that against your top competitors in the same practice area and city. The output is a citation-share metric: your slice of the AI answers in your category, tracked over time so you can see the line move, not just take our word for it. Agencies selling legal GEO without real instrumentation are guessing.

Three things. First, instrumentation. Joel co-founded Outrigger with Andrew as a separate joint venture that measures AI visibility. When the work calls for digital PR, Xpand may use PressForge to organize research, pitching, and follow-up. Most agencies selling 'GEO' have neither a baseline nor a repeatable workflow and are guessing at what the engines actually do. Second, our founder Joel House wrote AI for Revenue and The Growth Architecture, both available through Barnes & Noble. This is published methodology, not pitch material, and he's on every diagnostic call. Third, legal-specific advertising-rule review is built into the content workflow. Practice-area fit, jurisdiction rules, and the firm's final legal and professional-responsibility approval drive the strategy.

Retrieval-driven citations and training-layer associations move on different clocks, so there is no universal result date. Timing depends on the firm's existing authority, directory consistency, technical condition, practice-area competition, and the sources each engine selects. When digital PR is in scope, Xpand may use PressForge to organize research, pitching, and follow-up, with every placement subject to editorial judgment and the applicable advertising rules. We establish a baseline first, then set an evidence-dependent review cadence.