SEO vs GEO vs AEO: three labels, one job, and where they actually differ

GEO vs SEO is not a choice between two disciplines, and it is not one job wearing three labels either. The inputs overlap: the same pages, the same crawlable site. What changes is the question asked of them, the instrument that tells you whether it worked, and where the failure sits when it does not.

I am Kevin Pantanella. Syndral is my AI visibility agency, part of Suzaku Productions, which I founded in Bangkok in 2014. I spent twelve years selling the first of these three acronyms before the third one existed.

What follows is the comparison without the upsell. Where the three genuinely differ, where they overlap, and how to tell which one is actually failing you.

SEO earns you a ranked link on a page of results. AEO earns you the answer itself, lifted from your page. GEO earns you a named mention inside an answer a machine writes from several sources at once. Same web, three ways of being found.

Measurement is the row that matters. It is where these three stop being the same job. A surface is simply where an answer appears, and Google reports on the surfaces it owns while the other engines report nothing.

SEO is the work of being findable and rankable on a page of links, and nothing about AI assistants has retired it. An assistant that browses the web reads the pages a crawler already indexed. A site that no crawler can reach is invisible to both, which makes SEO the floor rather than the alternative.

The part that did change is what a good rank is worth. Pew Research measured it directly, and the figure below carries the sample.

Read the scope before you panic. A summary appeared on 18 percent of the searches in that study, and the queries that triggered one skewed longer and more question-shaped, which are lower-click queries to begin with. So this is not a like-for-like comparison of the same query with and without.

The same study found something harder for anyone counting on citations. Readers clicked a source listed inside the summary on 1 percent of visits. Being quoted in an answer is a reputation position, not a traffic plan, and those two things need different arguments to justify a budget.

AEO, answer engine optimization, describes being the answer rather than a link, and the practice predates generative AI even where the label is argued over. Featured snippets, People Also Ask and voice assistants all lifted one page and served it as the answer. The work was structural: clear questions, direct answers, clean markup.

Google's own guidance now treats AEO and GEO as two names for work on AI search experiences, while much of the industry still uses AEO for the snippet era. Two agency pages will define them in opposite ways, and both will be sincere. It is a vocabulary problem.

Here is the practical test. If one page is quoted as the answer, that is AEO territory. If several sources are blended into a new paragraph that names a few companies, that is GEO.

The test decides what you fix. An AEO failure is usually a page problem, the answer sits too far down or is buried in a paragraph nobody can lift. A GEO failure is usually not on your site at all. You are absent from the sources the model consulted, which is a corroboration problem, other people not describing you, and no amount of rewriting your own page solves it.

GEO, generative engine optimization, is the work of being named and cited inside an answer that a model composes from several sources at once. The term came out of an academic paper by Pranjal Aggarwal and five co-authors, published in 2023 and later peer reviewed for KDD 2024, rather than out of an agency deck.

Its headline result, up to 40 percent more visibility, was measured on a benchmark the authors built themselves. A laboratory result, not a client promise. The provenance and its limits are laid out in what generative engine optimization is.

Worth knowing for this comparison: what moved the needle in that study was ordinary editorial work, the same kind SEO has always rewarded.

Google publishes its position and it is the most useful sentence in this debate. Its AI features guidance, updated 10 July 2026, states that "optimizing for generative AI search is optimizing for the search experience, and thus still SEO". No separate discipline, no special files.

For Google's own surfaces, that is correct, and it deserves to be quoted more than it is.

It is also the answer that suits Google. It has nothing to gain from your visibility inside an assistant it does not own, and no say over how that assistant builds an answer. OpenAI runs its own search crawler, OAI-SearchBot, separate from the crawler that gathers training data. A second retrieval path exists, and Google does not control it.

Sort the work by surface rather than by acronym, because the surface is where the answers actually diverge. Syndral asked one buying question on three Google surfaces on 13 August 2026 in Bangkok, with the query written down before it was asked. The full run sits in what generative engine optimization is.

Most of the field appeared on one surface only

Syndral appears in none of the three answers, so there is nothing flattering in this data.

Eleven companies were named across AI Overviews, AI Mode and Gemini. Most of the field was visible somewhere and invisible somewhere else, on one afternoon, in one city.

Something else surfaced on that query. A paid ad at the top of the results sold "Guaranteed AI Visibility", while Gemini's own answer told the buyer to avoid any agency promising guaranteed inclusion, because generative outputs change with intent and context. The assistant gave better buying advice than the advertiser did.

You need all three outcomes, and you do not need three suppliers. What you need is a supplier whose instrument can see the thing you are buying. That is the whole question, and it is answerable in one email.

Ask whoever handles your search work how they measure whether AI assistants name your company. Their rank tracker reports Google positions. It cannot answer that. Positions and mention rates are different numbers, gathered differently, and no positions report contains the second one. The reply you get tells you which kind of agency you are dealing with.

Four steps, and the order is the point. Each one is worthless if the one above it failed, which is why so much AI visibility advice produces nothing: it starts at step two on a site the crawlers cannot read. This is the sequence Syndral runs, and you can run it yourself without hiring anyone.

1. Confirm the machines can fetch your pages. Check your server or CDN logs, not your assumptions.
2. Write direct answers near the top of each section, which serves the reader, the snippet and the model at once.
3. Make third-party sources describe you identically. Assistants blend what other people say about you.
4. Measure per surface, repeatedly, and record how often you are named.

Why the order cannot be rearranged

Run them in that order. Measuring a site the crawlers cannot reach only tells you what you already caused.

Step four is the one people skip, and it is the only one that tells you which of the three is failing. It has to be repeated because the answers move. SparkToro and Gumshoe tested ChatGPT, Claude and Google's AI Overviews: for ChatGPT and Google, under a 1 in 100 chance of returning the same brand list twice, and Claude only slightly better.

One action, if you take one. Run the free AI visibility ScoreCard. Eleven questions, about two minutes, and it tells you which layer is broken before anyone quotes you for fixing it. It scores your readiness from your own answers. Measuring what assistants actually say about you is the paid Diagnostic, and Syndral will not pretend a form can do it.

For a field test of what these tools actually measure, read the AI visibility score study. The rest of the writing lives in resources.