Answer engine optimisation, without the acronym fog.
AEO is the practical work of making useful answers easy to find and extract. It covers page structure, direct answers, schema that matches the page, and normal SEO foundations. It supports the broader AI-search service and does not promise inclusion in any answer surface.
Founder of TomHow, based in Stevenage. SEO and AI search consultancy.
Policy baseline: Google Search Central guidance for AI features.
Direct answer
What is answer engine optimisation?
Answer engine optimisation, or AEO, improves the chance that a page can supply a clear, accurate response when a search feature or assistant answers a question directly. The work begins by choosing real buyer questions, then placing concise answers near the top of the relevant page. Supporting sections explain scope, evidence, limits and next steps in language that a person can verify. Headings, internal links and structured data help describe the page, but they do not replace useful visible copy. TomHow also checks whether important facts agree across service pages, reports and business profiles. AEO cannot guarantee a featured snippet, voice answer, AI summary or citation. Search systems choose what to show and may change their outputs without notice. The practical goal is a page that answers the question well for a reader and gives retrieval systems less ambiguity about the subject, source and commercial route.
Thomas Howcroft starts with a simple human test: can he tell immediately what the page is about and what service it offers? If not, he checks the buyer's search intent and relevant query data, then gives the main question a quick answer near the top. The rest of the page should cover closely related questions in useful depth. A distinct topic may need its own page rather than another thin section.
Method source: Thomas Howcroft, founder interview, 11 October 2026. Edited for clarity; this is a method description, not a measured result.
Google introduction to structured data ->A single buyer query now hits five different answer surfaces.
Ten years ago, a buyer typed a query into Google, clicked a link, and you measured an organic session. The optimisation target was a position on the results page. The discipline was SEO.
In 2026, the same buyer query can end inside an AI Overview at the top of the SERP, a generative answer from ChatGPT or Claude, a Copilot answer inside Microsoft 365, a featured snippet, a People Also Ask accordion, or a voice assistant response. Most of these surfaces did not exist five years ago. None of them treat your site as a destination by default. All of them treat it as a source.
Answer engine optimisation, usually shortened to AEO, is the work of making a brand easy to find, understand and quote inside an answer rather than a list of links. It is the umbrella term, and it covers Google AI Overviews, Microsoft Copilot, standalone generative engines such as ChatGPT, Claude, Perplexity and Gemini, featured snippets, People Also Ask, and voice assistants. Generative engine optimisation, or GEO, sits inside AEO and deals with the standalone engines specifically. The practical work is page structure, direct answers written to stand alone when they are extracted, schema that matches what is visible on the page, consistent entity names, and the normal SEO foundations underneath. None of that creates eligibility by itself, and nobody can honestly promise inclusion in any answer surface. TomHow sells SEO, GEO and AEO as one retainer because the technical work overlaps heavily, and splitting the offer would mean charging three times for the same fixes.
Six surfaces under one discipline.
Seven core techniques.
These are the main levers. Most are technical, all are learnable, none are secret. The hard part is shipping them consistently across a real site for months on end.
Use Organization, Service, Article or Product markup where it describes the visible page. Google does not require special AI schema. FAQ rich results have ended, and HowTo markup is not a shortcut to answer inclusion.
Content written in clear question-answer structure with explicit headings. Each block should stand alone as a usable extract.
A map for systems that choose to use it. Google ignores llms.txt for Search visibility and rankings. The file is not crawler access control or a requirement for AI features.
Use a direct, definition-led answer where it helps the reader. There is no required word count and no guarantee of inclusion.
Consistent canonical strings for brand, products, people, and category terms. SameAs references to Wikidata, Wikipedia, LinkedIn, and Crunchbase where useful.
Use PAA questions as one demand signal, then answer the useful ones clearly. A PAA result does not guarantee an AI Overview or citation.
Natural language Q and A blocks that read as if a person asked them aloud. Useful for assistant inclusion where it applies.
Generate clean schema for your service pages.
The Schema Generator builds Organization, Service, Article, FAQ, and HowTo JSON-LD blocks in the browser. Useful first step before deeper AEO work.