Why the terminology is confusing

SEO, AEO, and GEO are often presented as separate generations of the same discipline. That makes a useful distinction sound like a complete replacement.

Search behaviour and result interfaces have changed. People can receive answers directly on a results page, inside an AI-generated search experience, or through a conversational product that retrieves information from the web. The practical foundation, however, still overlaps heavily with established search work.

What each label usually means

Search engine optimization

SEO is the established label for improving how pages can be crawled, indexed, understood, and presented in search, while making those pages genuinely useful to the people searching.

Answer engine optimization

AEO is commonly used for work intended to make information clear and useful when a system produces a direct answer. Depending on the person using the term, that may include featured answers, voice interfaces, or AI-generated search responses.

Generative engine optimization

GEO is commonly used for work intended to improve how information is discovered, understood, and referenced in AI-generated answers. There is no single technical standard shared by every product described as a generative engine.

AI-assisted search

AI-assisted search describes the user experience rather than claiming a separate optimization discipline. It includes search products and features that generate, organise, or summarise information with AI while drawing on web sources or other retrieval systems.

The shared foundation

Useful work across these labels can include:

• allowing relevant systems to access public pages;

• ensuring important pages can be rendered and indexed where applicable;

• creating original information that completes a real user task;

• using precise titles, headings, links, and page structure;

• showing who created or reviewed the information;

• separating evidence, interpretation, and recommendation;

• supporting claims with first-party material or credible sources;

• keeping names, services, people, and factual descriptions consistent;

• using structured data only when it accurately represents visible content;

• maintaining accurate canonical URLs, redirects, and sitemaps; and

• earning legitimate references by publishing material worth referring to.

For Google’s AI search features, the company states that no special AEO or GEO markup is required. It also says that an llms.txt file is not required for Google Search. Structured data can help a system understand visible content, but it does not guarantee a special result or citation.

What changes in AI-assisted search

The foundation overlaps, but the observation method changes.

A conventional search review can examine queries, impressions, clicks, landing pages, positions, and the visible results page. An AI-search review may also examine how the organisation is described, which sources are cited, whether the answer is accurate, how the wording of the prompt changes the response, and whether a referral is visible.

These observations are less stable than a normal analytics report. The product, prompt, date, location, and account state must be recorded.

What makes information more reference-worthy

No format guarantees a citation. Material becomes more useful to readers and potential sources when it offers something specific that weaker pages do not.

That may include:

• a direct and accurate definition;

• an original dataset with a disclosed method;

• a real diagnostic artefact with confidential details removed;

• a decision framework another person can apply;

• a clear comparison that explains where each option fits;

• first-hand experience with visible limits;

• named authorship and specialist review;

• primary sources that support technical claims; and

• a substantive review date rather than an automatically refreshed timestamp.

Artificially shortening every answer, publishing a page for every query variation, or adding FAQ markup to ordinary content does not create authority.

Crawler access is a policy decision

Search visibility and model training are not the same choice. OpenAI, Perplexity, and Anthropic document search or retrieval crawlers separately from some training crawlers. An organisation that wants its public pages to remain eligible for search retrieval should review its robots and firewall rules against current official documentation. Training access should be decided separately.

Crawler access only makes retrieval possible. It does not guarantee selection, description, or citation.