GEO vs AEO vs SEO: what's the difference?

The terms, defined

• SEO (search engine optimization) is the work of ranking pages in search engines such as Google and Bing.
• AEO (answer engine optimization) is the work of being the answer: first for featured snippets and voice assistants, now for AI answers.
• GEO (generative engine optimization) is the work of being named and cited in answers that AI engines write, such as ChatGPT, Perplexity, Gemini and Google's AI Overviews and AI Mode.
• LLM SEO, LLMO and AI SEO are newer labels for the same goal as GEO.

Why GEO and AEO are mostly the same

AEO is the older term. It described optimizing for featured snippets and voice assistants, where a search engine read one answer aloud or boxed it above the results. GEO was named in a 2023 research paper, GEO: Generative Engine Optimization (Aggarwal et al., KDD 2024), about engines that write an answer from several sources.

The distinction made sense when answers were extracted rather than written. It no longer does: Google's AI Overviews write their answers, and ChatGPT and Perplexity both search and summarise. Agencies and tools pick whichever label their buyers search for. Our advice is to ignore the label and ask what the work produces: more answers that name and cite you, measured against your competitors.

What SEO still does for AI answers

Anyone who tells you SEO is dead is selling something. Engines that search the web find pages the way search engines do, and much of the time through a search engine.

• Access and indexing. Google's AI features use pages that are indexed and eligible to show with a snippet; there is no separate AI requirement (Google Search Central). An engine cannot cite a page its crawler is blocked from.
• Ranking for the engine's own searches. In our 1 October 2026 experiments, 66.3% of the brands an answer recommended ranked in the top 10 for one of the searches the engine ran, against 30.7% of the brands it left out (method).
• Authority. The signals that make a page rank, links and mentions from sites people trust, are also what make engines trust and cite it.

But ranking is not enough on its own. Ahrefs found only 38% of the pages AI Overviews cite also rank in Google's top 10 (Ahrefs, March 2026). That gap is where GEO starts.

What changes when AI writes the answer

1. The result is a sentence, not a position

There is no "position 3" in an AI answer. You are named, cited, recommended first, or absent, and the wording matters: an answer can name you and describe you wrongly. Measure share of answers, not rank.

2. Other people's pages matter more

With search on, an engine reads a handful of pages and leans on what they say. In our tests, a brand named on six or more of the pages other answers cited was named in 34.9% of answers, against 11.9% for a brand on none of them. Muck Rack found 84% of the links ChatGPT, Claude and Gemini cite go to earned media (Muck Rack, May 2026). GEO is as much digital PR as on-page work.

3. Keywords give way to questions

People ask AI long, specific questions, and engines break them into searches of their own. In our run, 45% of the searches engines ran contained "best", 11% "vs" and 10% "alternative". The pages that win are the ones that answer shortlist questions directly: comparisons, alternatives, pricing with its conditions, who a product is best for.

4. Passages are quoted on their own

Engines retrieve passages, not whole pages (the evidence). A paragraph that names its subject and gives the answer in its first sentence can be quoted alone; one that leans on "it" and "as mentioned above" carries less.

5. The model's memory counts

Before it searches, a model already has a view of your category from training, and that view changes only when it is retrained. It also differs from what the engine says after searching: ChatGPT's recommendations with search off and on overlapped by only 32% in our tests. Being well known in your category, across many independent sources, is what shifts the memory over time.

What the research says works

The paper that named GEO tested rewrites on a benchmark of queries. Adding citations to sources, quotations and statistics raised a source's visibility in the generated answers by 30 to 40% on its main measure, while keyword stuffing made it worse (the details). Treat the numbers as direction, not promise: the benchmark used a 2023 model, and today's engines search and cite differently. The direction matches what we see: specific, sourced, quotable facts get used; padding does not.

What not to do

• Do not try to game the answers. Since May 2026 Google's spam policies say plainly that attempts to manipulate generative AI responses are spam (the details).
• Do not mass-produce pages for every variation of a question. Google calls that scaled content abuse however it is made (the details), and warns specifically against separate pages for fan-out queries (the details).
• Do not buy special markup or files. Google says no special schema, AI text files or llms.txt are needed for its AI features (the details).
• Do not judge by one engine or one week. Engines disagree, and answers move on their own.

Where to start: the first month

1. Week one: access and a baseline. Check that AI crawlers can read your site (the free checker does it in a minute), then take a first reading of your share of AI answers on the questions your buyers ask (the free audit, or a manual check).
2. Week two: the source map. List the pages the answers cite for your topics. Mark where you are missing, and where you are described wrongly.
3. Week three: the shortlist pages. Make sure your own site answers the comparison, alternative and pricing questions plainly, in passages that stand alone.
4. Week four: one change, judged. Ship one change aimed at named topics, and compare those topics with ones you left alone over the next weeks. Scale what works.

How to improve your brand's visibility in AI search goes through each move in detail.