A managing partner who has taken a few calls about AI search this quarter has probably heard three different acronyms for it. One provider sells GEO. Another sells AEO. A third avoids acronyms entirely and calls it AI search visibility. All three describe work that overlaps heavily, and the vocabulary is doing more to confuse the buying decision than to clarify it.
None of these terms were invented by us, and none of them are ours to define. They emerged from different corners of the search industry at different times, which is exactly why they do not line up cleanly. This piece defines each one honestly, explains where they genuinely differ, and then sets the vocabulary aside to look at what a law firm should actually be paying for.
What GEO Describes
GEO stands for generative engine optimization. It is the newest of the three terms and the most specific: the practice of getting a business named and cited inside answers produced by generative AI systems. The target surfaces are the assistants people now ask directly, including ChatGPT, Claude, Gemini, and Perplexity, along with the AI Overviews that appear above Google's blue-link results.
The word "generative" is doing the work in that definition. GEO is concerned with text a model writes rather than a list a search engine retrieves. That changes what success looks like. There is no position one. There is a paragraph, and your firm is either named in it or it is not.
What AEO Describes
AEO stands for answer engine optimization, and it predates the current wave of generative assistants by several years. It originally described optimizing for direct-answer surfaces inside conventional search: featured snippets, the answer boxes at the top of a results page, and the responses returned by voice assistants when someone asks a question out loud rather than typing it.
The underlying idea was that a growing share of queries were being answered without a click, so content needed to be structured to be extracted rather than merely ranked. Clear question-and-answer formatting, concise definitional paragraphs, structured data, and content organised around how people actually phrase a question are all AEO practices, and they long predate any large language model.
What has happened since is that the term stretched. Because generative assistants are also, loosely speaking, answer engines, AEO now gets used to describe generative work too. That is not wrong exactly, but it is imprecise, and the imprecision is why two providers can use the same acronym to describe fairly different scopes of work.
What AI Search Visibility Describes
AI search visibility is the plainest of the three and the least technical. It is not a methodology, it is an outcome: whether your firm shows up when someone uses an AI system to look for what you do. It covers generative answers, AI Overviews, and the direct-answer surfaces that AEO was originally about, without taking a position on which technique produced the result.
We use this term as the name of our own service for a straightforward reason. Outcome language survives changes in the underlying technology, and acronym language does not. The surfaces have already changed more than once and will change again. Whether a firm gets named when a prospect asks will not stop being the question.
Where the Three Genuinely Differ
Stripped of the marketing, the real distinctions are narrow.
GEO is a subset of AI search visibility. It addresses generative surfaces specifically. If a provider sells GEO and only GEO, they are working on assistant citations and probably not on featured snippets or voice results.
AEO is partly older and partly overlapping. Its original scope, extraction-ready content and structured data, remains genuinely useful and feeds directly into generative citation. Its expanded scope is largely the same work GEO describes.
AI search visibility is the containing category. It includes both, plus whatever the next surface turns out to be.
The practical consequence is that the acronym a provider uses tells you almost nothing about the quality of their work, and a little about when they started doing it. What tells you something is what they propose to do and how they propose to measure it.
Find out where your firm currently appears across both Google and AI search.
Free AI Visibility Audit including a parallel Google search visibility check, delivered as a PDF.
Get My Free AI Visibility AuditWhat Actually Matters for a Law Firm
Underneath all three labels, the work that moves the needle for a legal practice is a short and fairly stable list.
Entity clarity. The systems have to be able to tell who your firm is, unambiguously, and separate you from every similarly named practice in the country. That means consistent name, address, and phone data everywhere it appears, coherent schema on your own site, and a Google Business Profile that agrees with all of it. This is unglamorous administrative work and it is the highest-leverage item on the list.
Content an engine can extract cleanly. A thorough page on a specific practice area in a specific jurisdiction, structured so that a definitive paragraph can be lifted out of it, outperforms a longer page that buries the same information. This is the part of AEO that never stopped being true.
Authority beyond your own domain. Generative systems build a picture of a firm from how it is described across many sources, not from what it says about itself on one. Coverage, credible mentions, and presence on the sources those systems already lean on all contribute.
A working Google SEO foundation. The signal sets overlap enough that a firm with weak organic performance rarely does well in generative answers. The relationship between the two is covered in more depth in GEO vs SEO: what is different for law firms.
Measurement at the prompt level. Rankings do not describe this channel. What describes it is a fixed set of the questions a prospect would actually ask, run repeatedly across the engines, recording whether your firm is named, how it is characterised, and who is named instead. Without that, nobody can tell you whether any of the work is landing.
How the Engines Differ in Practice
The systems do not behave identically, and the differences affect what gets prioritised.
ChatGPT and Claude both draw on a training corpus and, when web access is enabled, live retrieval. Neither tends to cite a single page the way a retrieval-first engine does. They name firms by reputation accumulated across many sources, which makes broad, consistent recognition matter more than any individual page.
Perplexity retrieves in real time and shows its citations openly. That makes it the most legible of the four for measurement purposes, and it rewards thorough, well-structured pages on specific topics fairly directly.
Gemini follows similar principles to the other assistants with noticeably stronger influence from Google's entity graph. Firms with a complete Google Business Profile and clean entity data tend to appear more consistently here.
Google AI Overviews sit above conventional results for a growing share of queries and lean on much the same publisher authority Google already ranks. Ranking on page one for a query correlates with being cited in its Overview, though not reliably, and the behaviour is still changing as the system is tuned.
The shared foundation across all of them is the same: authoritative content on a credible domain, referenced widely, structured cleanly, with consistent entity data. The differences sit on top of that foundation rather than replacing it.
How to Tell a Label From a Practice
Since the vocabulary is unreliable, the questions have to do the work instead. Three of them separate a real practice from a rebranded content package.
"Which prompts will you track, and can I see the list?" A provider doing this work has a specific prompt set built around your practice areas and geography. A provider without one is producing content and hoping.
"What does the baseline look like today?" If they cannot tell you where you currently stand before starting, they will not be able to tell you what changed afterwards.
"What are you doing that is different from our SEO?" A candid answer acknowledges the substantial overlap and then names the additions: entity work, prompt-level measurement, and content structured for extraction. An answer that presents it as an entirely separate discipline is overselling.
The broader version of this vetting exercise, covering accountability, timelines, contract terms, and asset ownership, is in what to ask a law firm marketing agency before you hire.
What to Do Next
Pick whichever term you find clearest and stop worrying about it. What matters is whether your firm is named when a prospect asks an assistant who handles a matter like theirs, and that question has a measurable answer today.
Our AI search visibility service covers the entity work, the content structuring, and the prompt-level measurement across the engines. If you want the baseline first, the free AI Visibility Audit shows where your firm currently appears across both AI and Google search, delivered as a PDF. Either way, the useful move is to replace the vocabulary argument with data about your own market.