Short answer
Answer engine optimization is the practice of structuring content so that AI answer engines — ChatGPT, Perplexity, Claude, Copilot, Google AI Overviews — cite it inside their generated answers. Classic SEO competes for a ranked position on a results page; AEO competes to be the sentence the engine actually reproduces, with attribution.
Also called: AEO
The mechanics differ from ranking work in three ways. First, the unit of competition is a passage rather than a page: an engine lifts a paragraph, so the paragraph has to answer the question without depending on the sentence before it. Second, corroboration matters more than position — engines cross-check a claim against independent sources before repeating it, which is why third-party mentions outrank on-page tuning. Third, freshness is weighted heavily, because a generated answer carries an implicit promise of currency.
AEO does not replace SEO. The same crawlable, fast, well-structured site underpins both, and a page that cannot rank generally cannot be cited either. What changes is what you optimise the content *shape* for: extractable answers, specific numbers, plain attribution, and a visible last-updated date that is actually true.
Common questions
Is AEO different from SEO?
They share a foundation and differ in target. Both need a crawlable, fast, well-structured site. SEO optimises for a ranked position; AEO optimises for being quoted inside a generated answer, which rewards self-contained passages, specific figures, and independent corroboration rather than link position alone.
How do you measure AEO?
By asking the engines. Run a fixed set of your money questions through ChatGPT, Perplexity, Gemini and Copilot on a schedule, and log whether you are mentioned, cited with a link, or absent — and who appears instead. Bing Webmaster Tools also publishes a free AI Performance report, which matters because Copilot and ChatGPT search lean on Bing’s index.
Where this comes up in our work
Related terms
Generative Engine Optimization (GEO)
Generative engine optimization is the practice of increasing how often a brand or page is used as a source by generative AI systems.
Answer-First Content
Answer-first content resolves the question it poses in its opening lines — typically a 40 to 70 word paragraph containing the direct answer and a specific figure — before any background or setup.
Structured Data (Schema Markup)
Structured data is machine-readable markup, usually JSON-LD following the schema.org vocabulary, that states explicitly what a page is about: that this string is a price, that one an opening time, this entity the organisation publishing the page.
llms.txt
llms.txt is a proposed plain-text file at a site’s root that offers language models a curated map of its most useful pages, in Markdown, without navigation and boilerplate.
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