Answer Engine Optimisation (AEO) is the practice of structuring and writing your content so AI answer engines such as ChatGPT, Google AI Overviews, Perplexity, Gemini and Copilot can extract it, trust it, and cite it as a source. Where SEO earns a ranked link, AEO earns a mention inside the answer itself. You may also see it called generative engine optimisation, or GEO.
Why does AEO matter now?
For a long time the game was simple: rank on page one and earn the click. That is changing fast. Google now shows an AI Overview above the classic blue links for a large and growing share of searches, and millions of people start their research inside ChatGPT or Perplexity, which answer directly and often without sending a click anywhere, a shift known as zero-click search.
When the answer is synthesised for the user, being ranked is no longer enough. You need to be one of the sources the answer is built from. That is a different job from ranking, and it is the job AEO does.
How is AEO different from SEO?
AEO does not replace SEO. Classic SEO, a crawlable site, fast pages, relevant content and genuine authority, is the foundation that makes you eligible in the first place. AEO adds a layer on top: making each answer easy to lift out and worth trusting. For the full side-by-side, see AEO vs SEO.
| Dimension | SEO | AEO |
|---|---|---|
| Goal | Rank a page in the results | Be cited as a source in the answer |
| What wins | The page or URL | The individual passage or claim |
| Where you appear | The list of links | Inside the generated answer |
| Primary signals | Links, relevance, page experience | Extractable structure, evidence, authority, freshness |
| How you measure | Rankings and clicks | Citations and share of voice across engines |
| Who reads it | A person scanning results | A model assembling an answer |
How do AI answer engines pick their sources?
Every engine works a little differently, but the same three levers decide whether you get cited. Get all three right and you show up across engines, not just one.
1. Structure: make it easy to extract
Models lift passages, not whole pages. Lead every section with a direct answer of roughly 40 to 60 words, then expand. Use headings that mirror how people phrase the question, keep each passage self-contained, and use a table for anything comparative. The easier a claim is to quote out of context, the more likely it is to be quoted. For the full page-by-page how-to, see how to structure content for AEO.
2. Authority: make it worth trusting
Answer engines favour sources they can stand behind. Cite primary data, include specific numbers with dates, quote named experts, and show a visible last-updated date. Google's own guidance on people-first content calls trust the most important part of E-E-A-T and specifically rewards clear authorship and transparent sourcing, which is exactly why citations and named authors help. Keyword stuffing does the opposite: it reads as low quality to both people and models.
3. Presence: be where the models look
Much of what an engine cites is not your own site. Reputable third-party pages, Wikipedia, active community threads, review platforms and honest industry roundups, carry real weight, sometimes more than your own domain. Being described consistently across the web helps a model recognise and trust your brand. For the full playbook, see off-page AEO.
How do you let the AI crawlers in?
None of this matters if the engines cannot read you. Allow the answer-engine crawlers you want to be cited by (OAI-SearchBot for ChatGPT, PerplexityBot, Bingbot for Copilot) in your robots.txt, and make sure your content is in the raw HTML, not injected after JavaScript runs, or many crawlers never see it. For which crawlers matter, how to allow or block each, and how to keep model training out while staying citable, see how to control AI crawler access.
What does not work anymore?
A lot of AEO advice is recycled SEO folklore or wishful thinking. These tactics will not move the needle in 2026, and chasing them costs you the time you should spend on substance:
- Speakable schema is not a citation lever for answer engines.
- FAQ schema as a snippet play. Google retired FAQ rich results as a general feature. Keep the markup as machine-readable data, but it will not win you an accordion or a snippet.
- Keyword density. There is no magic repetition count. Stuffing hurts. Prominence in the title, first paragraph and headings matters far more.
- llms.txt. The major engines do not use it to choose citations, and Google explicitly states you do not need to create AI text files or special markup to appear in its AI features. It is not a shortcut around doing the work.
What is on your AEO checklist?
- Open every key page with a direct 40 to 60 word answer to its core question.
- Use H2 and H3 headings that match how people ask, not clever labels.
- Turn comparisons into tables and processes into numbered steps.
- Back claims with specific figures, dated, and link the primary source.
- Attribute content to a named author with real expertise.
- Show a visible last-updated date and actually keep pages fresh.
- Confirm your content is in the raw HTML, not injected after load.
- Check robots.txt allows the answer-engine crawlers you care about.
- Earn honest third-party mentions on pages models already trust.
- Measure citations and share of voice across engines, then repeat.
How does Limecube help?
Limecube is built around exactly this loop. Its AI Search Hub tracks whether ChatGPT, Claude, Gemini and Perplexity cite you, alongside Google AI Overviews, so you can see your share of voice across every answer engine in one place. It writes extractable, source-ready content in your brand voice, and its Site Audit flags crawler-access problems and missing structure before they cost you a citation. If you want the short version of the workflow, the features tour walks through it, and pricing starts with a 7-day trial.