GEO and AEO: optimizing for AI search

Four names for one task

A research paper

• GEOGenerative Engine Optimization: an arXiv paper, November 2023, accepted to KDD 2024

Vendor words

• AEOAnswer Engine Optimization: attributed to 2017, the primary source is not confirmed
• ≠LLMOa synonym of GEO, no primary source found
• ≠AI SEOtwo meanings: AI for SEO, and visibility in AI

There is no difference of substance between them.

In the original GEO paper the authors changed the text of pages and measured how often a source appeared in the answer of a generative system. The best techniques raised visibility by up to 40% on their query set. That is an experiment under laboratory conditions, not a promise for any site.

Definitions of all the terms: Glossary.

In its guide for site owners Google writes two things:

• AEO and GEO are terms you may see used, while optimizing for AI features of Search is still SEO;
• there is no need to create special machine-readable files for Search: Search does not use them.

This is one search engine’s position about its own products. It says nothing about how other AI systems work.

1. A questiona person asks an AI system
2. Searchthe system looks for pages in a search index
3. Readingan agent opens several pages
4. An answertext with links to sources

A simplified scheme. Systems differ inside, and their owners disclose the internals only in part.

The main point follows from the scheme: to get into an answer, a page first has to be found. Most AI systems with search rely on an ordinary search index. A site missing from search will not appear in an answer either.

The fundamentals are known reliably. They are the same as for search.

• The page is reachable. It answers 200, the text is in the server-sent HTML, the robots you want are not blocked.
• The page is indexed. A search engine knows it.
• The page has a direct answer. A definition, a number, a step - as text, not as a hint.
• The text is clearly built. Headings by meaning, lists and tables where they fit.
• Facts are verifiable. The source, the author and the date are stated.
• Entities are described explicitly. Structured data says that this is a product, an article or an organization.

There is no need to write “for machines” at the expense of people. Clear text is read by both.

• robots.txt decides whether a robot is let in. Blocking training while staying in AI search is possible: those are different robots. AI crawlers.
• Structured data is read by search engines, and through them the facts reach AI systems. Structured data and JSON-LD.
• llms.txt helps an agent that has already arrived find what it needs. According to the available studies, it does not affect appearing in answers. Does llms.txt work.
• Markdown versions make reading easier for an agent. Markdown versions of pages.

Every layer in order: An AI-ready site.

What is known and what is not

Confirmed

• Google applies the same fundamentals to AI features of Search as to ordinary search.
• The GEO research paper showed that text edits change how often a source appears in an answer under experimental conditions.
• AI systems publish the names and purposes of their robots.

Not proven

• That having llms.txt increases citations: the SE Ranking study of 300 thousand domains found no link.
• That laboratory results transfer to an arbitrary site and survive model updates.
• That one paid “AI visibility” service measures the same thing as another.

What it does not mean

• A position in an AI answer does not exist.
• A mention cannot be guaranteed.

SEO fundamentals work for AI search as well. There are no special techniques with a proven effect for an ordinary site.

How to measure and where measurement ends: How to measure AI visibility.