AEO, GEO and SEO: what's different, and what carries over

The three terms, one paragraph each

SEO, search engine optimisation, is the work of getting pages to rank in Google and Bing for the queries people type. The result page is a list; your page has a position; you win clicks in proportion to how high it sits. It has had twenty-five years of practice, tooling and measurement.

AEO, answer engine optimisation, is the work of getting your brand and your pages into the answers that answer engines give. The term predates the current wave: it was used for featured snippets and voice assistants, which also answered the question instead of listing links. Today it mostly means the AI assistants that search the web and write a reply.

GEO, generative engine optimisation, is the same work named from the engine's side: the engines generate text, so you optimise for what they generate. The term comes from a 2023 research paper and spread from there into marketing. When people say GEO they mean ChatGPT, Perplexity, Gemini, Claude and AI Overviews, and they mean mentions and citations.

A comparison table

The last row is the one that changes strategy. In SEO your rival is another page. In AI answers your rival is another brand, and the referee is a handful of third-party pages the engine reads before it writes.

What carries over from SEO

If you have done SEO well, you are not starting from zero. Five things transfer directly.

Crawlability

An engine cannot quote what it cannot read. The AI crawlers (OpenAI's GPTBot and OAI-SearchBot, Anthropic's ClaudeBot, PerplexityBot, Google's Googlebot for AI Overviews) obey robots.txt, and plenty of sites block them by accident through a wildcard rule or a security product. Pages rendered only by JavaScript, hidden behind a login, or missing from the sitemap are invisible in the same way they were to Google ten years ago. AI crawlers explained lists the bot names and what each one is for.

Clear pages

A page that says one thing, says it early and says it in plain words was always what Google rewarded. It is what an AI assistant quotes. The difference is only that the AI is more literal: it looks for a passage that answers the question, and it will take the competitor's plain sentence over your clever one.

Authority

Links, brand searches, press and reviews told Google you were real. They tell the AI engines the same thing, partly through the same signals (the engines often start from a web search) and partly because those mentions are themselves text the engine reads. A brand with a history on review sites and in trade publications is known to the model before it searches.

Structured data

Schema.org markup does not make an AI answer cite you on its own, but it makes facts unambiguous: what the product is, what it costs, who makes it, what the FAQ answers are. Where structured data matches what the page says, it reduces the chance of being misread. What schema.org actually does for AI search sets expectations honestly.

Speed and stability

Crawlers have budgets and time-outs. A slow or flaky site gets fetched less, and a page that was not fetched cannot be cited. Nothing new here, only a second reason to care.

What is new

Five things do not transfer, and each one changes how you work.

You are named, not ranked

There is no first place. An answer to "best scheduling tool for agencies" might name four products in one sentence and recommend one of them in the next. You are in the answer or you are not, and when you are in it, the question is whether you are first, recommended, or an afterthought. Keyword rankings do not predict this well: a page can rank third on Google and still not be named, because the answer was written from a comparison list that left you out.

You are quoted, not visited

An AI answer pulls passages, not pages. The engine fetches your page, takes the two sentences that answer the question, and attaches a citation. Most readers never click. So the passage must be self-contained and correct, because it will be read on its own, and the traffic you get will be a fraction of the exposure. Writing content that AI answers quote is about building pages for that.

Third-party sources carry more weight

For a buying question, the engines read reviews on G2 and Capterra, Reddit threads, "best X" lists and trade publications before they read your site, because those are the pages that compare options. Your own site tells the engine what you say about yourself; the third-party pages tell it what to believe. In SEO these were link sources. In AI answers they are the text the answer is made from, and a wrong or missing entry there is a visibility problem you cannot fix on your own domain.

The answer is written, not listed

A results page shows ten options and lets the reader choose. A written answer chooses for them, and the choosing is done by a model with an opinion formed from everything it has read. That is why the same question on two engines gives different brands, and why a brand can be invisible on one and dominant on another: they have read different things.

Training knowledge sets a baseline

Even when an engine searches the web, the model already has a view of your category from its training data. A brand that is well documented across the web before the training cut-off starts every answer with an advantage; a newer brand must be found through search each time. You cannot edit the training data, but you can make sure the next round of it finds you everywhere it looks.

AEO and GEO: an honest take

They are the same thing. Both mean getting named and cited by the engines that write answers. Both are measured the same way, with the same prompts across the same engines. Both reward the same work. The only difference is who coined the word and which agencies prefer it.

If you need a rule: use whichever word your boss or your customers use, and do not let the vocabulary become a project. Some teams simply say "AI search" or "AI visibility" and skip the acronym. That is fine too.

What a small team should do first

A two-person team cannot do everything, so the order matters.

1. Measure before you change anything. Write 20 to 30 of the questions your buyers ask, mostly without your brand name in them, and run them on ChatGPT, Perplexity, Gemini and Google in a clean session. Log who is named and which sites are cited. This takes an afternoon by hand and gives you the whole picture: what AI visibility is and how to measure it walks through it.
2. Check the door is open. Read your robots.txt and your sitemap, and look at the server logs or your CDN for the AI crawlers' user agents. A blocked crawler is the single most common and cheapest problem.
3. Build or fix the pages that answer the questions. For each prompt where you are absent and should not be, there is usually a page missing or a page that buries the answer. One clear page per question, answer in the first lines, headings that match the sub-questions.
4. Fix the facts. Ask each engine what your company does, what it costs and who it is for. Wrong answers come from stale or missing sources, and they are fixable.
5. Get onto the pages that get cited. Take the short list of sites cited across your prompts and work through them: claim and complete the review profiles, pitch the comparison lists, join the threads where it is honest to do so.
6. Keep doing SEO. The engines search before they answer, and ranking for the underlying queries is still how you get fetched. The budget shifts; it does not move entirely.