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What Is Answer Engine Optimisation?
Answer engine optimisation is the practice of structuring a website so that AI answer engines such as ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot can find, understand and quote it. It differs from traditional search engine optimisation in what it optimises for. A ranked list of links rewards position. An answer engine rewards being the clearest and most quotable source on one specific question. In practice that means answer first writing, unambiguous entity signals and content an engine can extract in a single pass.
Where the term came from
The idea has an academic origin, which is unusual in this field. In November 2023 six researchers published a paper called GEO: Generative Engine Optimization, later peer reviewed and presented at KDD 2024, which set out a framework for optimising content for engines that generate an answer rather than return links. It is the first serious attempt to test what actually changes a source's chances of being used.
One number from that paper gets misquoted constantly. It reports visibility gains of up to 40 per cent. That is an upper bound for the single best performing tactic on the authors' own benchmark, not an average, and not a result you should expect. Any agency quoting you a flat 40 per cent uplift has read the abstract and not the paper.
Answer engine optimisation compared with SEO
| Traditional SEO | Answer engine optimisation | |
|---|---|---|
| What wins | A high position in a list of links | Being the source an engine quotes |
| Unit that competes | The page | The passage |
| Reward for length | Often helps depth | Neutral at best, and it can bury the answer |
| What the user sees | Your title and description | Often your words without your name attached |
That last row is the one that catches people out. Research by Semrush with Kevin Indig, covering 3,981 domain appearances across 115 prompts, found that almost 62 per cent of citations were what they called ghost citations. The engine used the page as a source link, but the brand name never appeared in the answer the person read. Being used and being named are different outcomes.
AEO, GEO and LLM optimisation: what the labels actually mean
There is no agreed definition, and anyone who tells you otherwise is selling a framework. We use the terms this way, and we say so on every page so you can hold us to it. Generative engine optimisation is the whole discipline. Answer engine optimisation is the narrower craft of making an individual answer extractable. LLM optimisation is the work of making a business legible to a model across training, retrieval and third party corroboration.
The labels matter less than the mechanism. Will Critchlow of SearchPilot has made the point that a language model has no internal ranking system in the sense search marketers mean, which is why importing ranking habits wholesale into this work tends to mislead.
What an answer engine is actually doing
In simplified terms: it breaks your question into several smaller questions, retrieves candidate sources for each, judges which ones it can rely on, then assembles a single answer in its own words. Three consequences follow, and they are the whole of the practical discipline.
- Coverage beats depth on a single page. If a question fans out into five sub questions, five clear answers across your site beat one long article that half covers all of them.
- Retrieval comes before everything. If an engine's crawler cannot reach the page, nothing else you do matters. This is the most commonly missed step and the cheapest to fix.
- Extractability decides selection. The engine needs a passage it can lift with confidence, which rewards a direct answer in the first sentence and punishes a slow build up.
Is any of this separate from SEO?
Less than the marketing suggests. Google's own guidance says its generative features are rooted in its core ranking and quality systems. Cyrus Shepard of Zyppy scored 23 possible AI citation factors against 54 published studies and patents, and the two that scored highest were plain URL accessibility and ordinary search rank. He also found that 38 per cent of AI Overviews citations come from the top ten Google results.
So the honest position is that answer engine optimisation is a discipline within SEO rather than a replacement for it. What is genuinely new is the writing craft and the crawler decisions. What is not new is that you still have to be findable and worth finding.
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Frequently asked questions
Is AEO the same as GEO?
Not quite, though the terms are used interchangeably by most people. We use generative engine optimisation for the whole discipline and answer engine optimisation for the specific work of making individual answers extractable. Nobody has authority over these definitions, so ask anyone using them which they mean.
Does AEO replace SEO?
No. Google states that its generative features are rooted in its core ranking and quality systems, and independent analysis puts crawlability and ordinary search rank at the top of the citation factors. Treat it as a discipline within SEO. A site that cannot rank will not be cited either.
Which businesses benefit most from AEO?
Businesses whose customers ask comparison and recommendation questions before buying, which covers most professional services, healthcare, trades and B2B. If your customers already research before they enquire, an assistant is now part of that research.
How do I know if my site is AEO ready?
Start with three checks you can do yourself. Read your most important page aloud and see whether the first sentence answers the question in the heading. Open your robots.txt and look for AI crawler names. Then ask an assistant a question you should be the answer to, and see who it names instead.
Not sure how AI assistants describe your business?
We run a hand checked AI visibility audit, scored out of 100 across five areas, with the weightings published so you can argue with them.
Book a 15 minute callSources
- Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan and Deshpande. GEO: Generative Engine Optimization, KDD 2024. Published 24 August 2024.Peer reviewed. Reports gains of up to 40 per cent on the authors' own benchmark. That is an upper bound for the best performing tactic, not an average.
- Semrush with Kevin Indig, Growth Memo. Why 62% of AI citations don't lead to brand mentions. 9 June 2026.3,981 domain appearances, 115 prompts, four engines. 61.7 per cent ghost citations.
- SearchPilot, Will Critchlow. LLMs do not rank anything. So what are you optimizing for?. 1 May 2026.On the absence of an internal ranking system in language models.
- Zyppy, Cyrus Shepard. AI Citation Ranking Factors Analysis. 7 May 2026.54 sources, 23 factors scored. URL accessibility and search rank scored highest.
- Google Search Central. Google's Guide to Optimizing for Generative AI Features on Google Search. Updated 10 July 2026.Generative features are rooted in core ranking systems. No special schema required. Google Search ignores llms.txt.
Every figure on this page was read on the source page listed above. This page is reviewed monthly and the last checked date is updated when it is.
