GEO vs SEO vs AEO

What is the difference between GEO and SEO?

SEO earns a ranked link on a results page; GEO earns a citation or mention inside a generated answer. Both start from the same crawled and indexed pages, but GEO is judged per passage, per prompt and per AI engine, and it is reported separately.

Search engine optimization (SEO) is the practice of getting pages to rank in search engine results. Its outcome is a position on a list of links, and its test is simple: search the query and look for the URL. Generative engine optimization (GEO) targets a different surface — the written answer that Google AI Overviews, AI Mode, ChatGPT search, Perplexity or Copilot produces — and its outcome is to be named or linked inside that answer. For the full definition and the 2023 paper that introduced the term, see generative engine optimization defined.

The relationship is a dependency, not a rivalry. Wikidata classes GEO as a subclass of search engine optimization, and the engines behave that way: Google’s AI features draw candidates from the Google Search index, Copilot grounds its answers in Bing, and ChatGPT search and Perplexity send their own crawlers to fetch pages. Every one of them needs a page it can reach and read. SEO builds that reach; GEO works on what happens once a page is in the candidate set.

What changes is the level at which a page competes. A ranked link represents a whole page, chosen for a single query. A citation represents a passage — a paragraph, list or table row — chosen because it answers one of several sub-queries the engine generated from a prompt. A page can rank well and never be quoted, because none of its passages answers a sub-query cleanly. A page can also be quoted without ranking in the top three, because the engine read further down the list to cover a detail.

The engines also differ from each other in ways classic search never did. Google and Bing each run one crawler and one index, and SEO has long treated them as two versions of the same job. GEO covers at least five answer products built on four different retrieval paths, each with its own crawler rules and citation style, so a site can be cited often in Perplexity and rarely in AI Overviews for the same prompt.

The last difference is visibility of results. SEO performance sits in one familiar report. GEO performance is split across new first-party reports and prompt tracking, and each engine counts differently.

How do GEO, SEO and AEO compare on 10 attributes?

GEO and SEO differ on 7 of 10 attributes and share 3: crawlability, index eligibility and content quality. AEO matches GEO on almost every attribute, because the two terms describe the same practice in most published usage.

GEO and SEO share crawlability, index eligibility and content quality; they differ on unit of success, result surface, retrieval unit, query handling, metrics, reporting and off-site signal.

The three shared rows come straight from Google’s guidance: pages in its AI features must be indexed and snippet-eligible, and those features are rooted in the same core ranking and quality systems as classic search. The crawl row is shared at its base and extended for GEO, because ChatGPT search and Perplexity use their own crawlers. OpenAI states that sites opted out of OAI-SearchBot are not shown in ChatGPT search answers, and PerplexityBot is the crawler that surfaces and links sites in Perplexity. A site that allows only Googlebot and Bingbot is fully open for SEO and partly closed for GEO.

The seven differing rows describe the work that is new. Off-site signal is the one most often misread. Links still matter for ranking, which feeds retrieval, but an AI answer that recommends a brand usually does so because other sources name it, whether or not they link. That makes unlinked mentions in reviews, comparisons and forum threads a GEO asset in their own right.

The AEO column reads “same as GEO” on most rows for a reason covered below: in current usage the terms are interchangeable. The two historical notes mark where AEO began, with featured snippets and voice assistants that returned one answer from one source.

Where do GEO and SEO overlap?

GEO and SEO overlap at eligibility: Google shows a page in AI Overviews or AI Mode only when it is indexed and eligible for a snippet. Google's generative features draw on its core ranking and quality systems, so SEO work carries into GEO.

Google set out its position in “Optimizing your website for generative AI features on Google Search”, published in May 2026 and last updated on 10 July 2026. Three statements in it define the overlap.

"Optimizing for generative AI search is optimizing for the search experience, and thus still SEO."

"You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search."

Read together, they place every SEO fundamental inside GEO. Crawl budget, canonical tags, internal links, page quality and the removal of stray noindex or nosnippet directives all decide whether a page reaches Google’s AI features. The Search Console setting is the one gate with no SEO equivalent: a site can rank normally and still be excluded from generative features by that switch.

The overlap also has a limit worth stating. Google-Extended, the control that governs use of content for Gemini training and grounding in Gemini Apps, does not affect inclusion in Google Search, so it has no effect on AI Overviews or AI Mode. A site owner who blocks it to opt out of training is not opting out of Google’s AI answers.

Which SEO habit lowers AI visibility?

Keyword stuffing — repeating the target query’s words through a page — is the clearest case of an SEO habit that works against GEO. The 2023 paper that introduced the term tested it alongside 8 other content changes. On its benchmark of 10,000 queries, keyword-stuffed sources scored 17.7 on the paper’s main visibility metric against a 19.3 baseline for untouched sources: the change made them less visible, not more. The authors repeated the test on Perplexity, a live engine, and keyword stuffing again scored below the unmodified baseline, 21.9 against 24.1, about 9% lower.

The reason is the retrieval unit. A language model reads for meaning and picks passages that answer a question clearly; repeated keywords add words without adding information, which dilutes the passage. The methods that scored highest in the same test added quotations, statistics and cited sources — information, not repetition.

Is AEO different from GEO?

No consensus separates AEO from GEO. Wikipedia redirects "answer engine optimization" to its GEO article and reports no agreed definition distinguishing the terms as of early 2026. Google groups both under SEO.

Answer engine optimization (AEO) — Wikidata describes it as a form of search engine optimization that optimizes for answer engines. The term is older than GEO. It grew up around featured snippets, the boxed answers Google showed above its results, and voice assistants, which read one answer aloud. In that period the goal was to be the single source extracted for a question. The glossary entry covers the answer engine optimization meaning in more depth.

Generative engines changed the target. An AI Overview or a ChatGPT answer is written by a model from several sources, and it can cite three, five or more of them. Most practitioners who still say AEO now mean exactly this: getting cited in AI-written answers. That is why English Wikipedia treats the two as one topic and records that no consensus definition separates them.

Some agencies draw a line anyway — AEO for direct, question-shaped answers, GEO for longer synthesized ones — but the engines do not work that way. The same retrieval, passage selection and citation steps run whether the answer is one sentence or ten paragraphs. The same is true of LLM optimization (LLMO) and AI SEO in its “optimizing for AI answers” sense.

For planning, treat AEO and GEO as one workstream. The label a vendor uses tells you about its marketing, not its method; ask instead which engines it tracks, how it measures citations and whether it checks crawler access and eligibility first.

Which comes first for a website, SEO or GEO?

SEO eligibility comes first, then GEO. A page that is blocked, unindexed or excluded from snippets cannot be cited by Google's AI features. Once those gates pass, GEO work on passages, brand mentions and citation tracking starts.

Answer the four questions in order. Stop at the first “no” — that is your next task.

1. Can Googlebot, Bingbot, OAI-SearchBot and PerplexityBot fetch your key pages?If no: start with crawler access — no engine can cite a page it cannot fetch.
2. Are those pages indexed in Google and Bing?If no: fix indexing first — Google's AI features only use indexed pages.
3. Are they eligible for a snippet (no nosnippet, and included in Search generative AI features in Search Console)?If no: remove the snippet restriction and check the Search Console setting.
4. Do you know which prompts cite you today?If no: measure a baseline before rewriting anything. If yes: move to GEO work — answer-first passages, brand mentions and re-testing.

The check turns into a fixed order of work:

1. Unblock the search crawlers each engine uses, keeping training crawlers as a separate decision.
2. Index the pages that answer buyer questions, in both Google and Bing.
3. Qualify those pages for snippets and for Google’s generative AI features.
4. Rewrite the key sections so each opens with a self-contained answer backed by first-hand facts.
5. Track mentions and citations on a fixed prompt set, and re-test after each change.

Steps 1 to 3 are SEO work and pass or fail. Steps 4 and 5 are where GEO adds something SEO does not do, and they compete against every other source an engine could cite. The order is a dependency, not a preference: rewriting a page that OAI-SearchBot cannot fetch improves nothing in ChatGPT. The full AI search optimization method expands these five moves into 8 steps with the controls for each engine.

Does GEO replace SEO?

No. GEO extends SEO rather than replacing it. Google states that optimizing for generative AI search "is still SEO", and every AI engine that searches the web retrieves from an index built by crawling, the same foundation SEO maintains.

The order is clear; the remaining question is whether one replaces the other. The replacement claim rests on a real change: when an AI answer satisfies a question, fewer people click through to a results page, and the ranked link loses some of its value. That changes what SEO success looks like. It does not remove the index, the crawler or the quality systems that decide which pages the answer draws on.

Some SEO tasks gain weight under GEO and some lose it. Tasks that make a page easy to fetch, index and understand gain weight, because every engine depends on them. Tasks built around matching exact keyword strings lose it, because a model reads for meaning and the evidence shows keyword repetition lowering visibility. Tasks that build a brand’s reputation off-site shift from chasing links towards earning mentions, since an answer can name a brand without linking to it.

What does change is the reporting and the skills. Teams now track prompts as well as keywords, passages as well as pages, and mentions as well as links. Search Console’s Generative AI performance report, available to all sites from 31 August 2026, and Bing’s AI Performance report, in public preview since 10 February 2026, exist because the engines themselves treat AI answers as a separate surface worth measuring. For the longer argument on whether SEO is dead, the answer follows the same logic: the foundation stays, and the work built on it grows.