# Answer Engine Optimization (AEO)

> Source: https://rankxai.com/glossary/answer-engine-optimization · Last updated: 2026-08-18

Answer Engine Optimization is the practice of writing pages so an AI assistant can lift a direct answer out of them. No standards body defines the term and no paper introduced it: AEO, GEO and LLMO are three coinages for one practice, and the differences between them are marketing rather than method.

## Is AEO actually different from GEO?

Not in any way that changes what you do on a page. [GEO](/glossary/generative-engine-optimization) has a paper behind it; AEO does not, and neither does [LLMO](/glossary/llmo). Read a dozen guides to each and the recommended actions converge: answer the question early, structure the page around questions, be specific, be retrievable. Three names, one method, and the name a given company prefers usually tells you what it sells.

The one distinction worth keeping is the one the names gesture at rather than state. “Answer engine” points at surfaces that write an answer instead of listing links, which is a real difference from classic search, and the vocabulary is useful even when the discipline behind it is not new. It is also the older of the two ideas: answer engines predate generative models, and the phrase was in use when the thing being optimised for was a featured snippet.

## Which piece of standard AEO advice is measurably wrong?

Structured data as a citation lever, and it is the first item on nearly every AEO checklist. Two separate findings put it to bed. Ahrefs added schema to 1,885 pages against roughly 4,000 controls over seven months and measured AI Overviews down 4.6%, AI Mode up 2.4% and ChatGPT up 2.2%, which is indistinguishable from zero. A separate test found no engine extracted a fact that existed only in JSON-LD, because training pipelines strip script tags before anything is embedded.

The specific markup usually recommended is worse than neutral, because it no longer produces anything. Neither `FAQPage` nor `HowTo` appears in [Google’s structured data gallery](https://developers.google.com/search/docs/appearance/structured-data/search-gallery), the authoritative list of types that earn a rich result, so the two formats every AEO checklist opens with generate nothing at all in Google. Google’s own guidance is that no special structured data is needed for its AI features, and here the controlled test agrees with Google.

Keep emitting schema, for rich results, entity resolution and Bing, which is the one platform whose staff have said it helps their language-model pipeline. Stop expecting it to earn citations, and never let a fact live only in the markup.

## What is left once the schema advice goes?

The visible question-and-answer shape, which is what was doing the work in the first place. A question as a heading with its answer directly underneath is the most liftable structure a page can offer, and it earns that whether or not a `FAQPage` block wraps it. Everything else on the list is ordinary good writing: name the entity rather than saying “it”, put the answer before the argument, and be specific enough to be worth quoting.

## Sources

- [Ahrefs: schema markup and AI citations, 1,885 pages vs controls](https://ahrefs.com/blog/schema-ai-citations/), checked 2026-08-18
- [Google Search Central: AI features and your website](https://developers.google.com/search/docs/appearance/ai-features), checked 2026-08-18
- [Google Search Central: structured data markup gallery, which no longer lists FAQPage or HowTo](https://developers.google.com/search/docs/appearance/structured-data/search-gallery), checked 2026-08-18