What Are AEO and GEO? The Path to Visibility in AI Search

The question "what is GEO" is the natural continuation of the SEO conversation; they work together, not apart. AEO is the name for work improving a page's comprehension in direct-answer formats, and GEO for work improving that content's chances of being found and shown as a source in generative AI answers. Both rest on SEO: if the page isn't found, isn't indexed and doesn't give reliable information, a separate "AI optimisation" won't save it.

The most expensive mistake here is treating a new term as a new magic service. Google's official generative AI guide, updated on 10 July 2026, recognises the AEO and GEO terms but, from Google Search's standpoint, still counts this work as SEO. In other words, the difference mostly clarifies the goal and the reporting language; it doesn't create a separate hidden ranking system.

What are SEO, AEO and GEO?

SEO: being found and being the fitting result

SEO is the technical, content and reputation work done so the site is crawled by search bots, indexed, understood for query relevance and shown in the search results. That base isn't only for "10 blue links." Google's AI Overviews and AI Mode also draw their information from the Search index and the core ranking systems.

AEO: being ready for the answer format

AEO — Answer Engine Optimization — is the working term for making content give a clear, extractable answer to a question. A direct definition, logical headings, step lists, comparison tables and sources beside claims are useful from an AEO standpoint. These aren't fragments written for robots; they're editorial decisions helping the reader find the answer fast.

AEO doesn't mean separate schema for a special answer box. Per Google's featured snippet documentation, a page cannot be marked up as that result; the system makes the choice itself. So a short answer block can improve eligibility, but it gives no display guarantee.

GEO: appearing in generative answers and being a source

GEO — Generative Engine Optimization — describes the work done so a brand and content are understood correctly, found and, where possible, shown as a supporting source in generative search experiences. The key word is "possible." No agency can guarantee a citation, a link or a position for a given query.

How does Google view GEO and AEO?

Google's position is simpler than expected: SEO is still what matters for generative search. The AI features and your website documentation states openly there are no extra technical requirements and no special optimisation for AI Overviews and AI Mode. The page must be in the index, remain eligible to be shown with a snippet in ordinary Search results and not violate the spam policies.

RAG finds fitting sources from the existing index

In the official guide, Google explains the retrieval-augmented generation mechanism, RAG for short. The system finds current, fitting pages from the index using the core Search ranking mechanisms, then grounds the answer in that material. That shows why technical SEO, original information and the page's update date matter for GEO too.

Query fan-out can split one question into sub-topics

AI Overviews and AI Mode can split a query into several related sub-searches. For example, "how does a small business choose a CRM?" can generate extra queries about pricing, integrations, team size and data security. That's not a call to open a separate weak page for every variation; it's the need to answer one core intent deeply enough, with connected evidence.

What's the difference between SEO, AEO and GEO?

You don't need three separate teams. When one page is technically healthy, useful to people, answers the question clearly and proves its claims, most of the SEO, AEO and GEO needs are solved in the same work. What differs is mostly which kind of visibility you track.

The 7-step implementation system for AEO and GEO

1. Choose one core intent

First separate whether the query is a definition, a comparison, a problem to solve or a purchase decision. Keyword analysis shouldn't only produce phrase lists; it should show which page type will answer that query. Cramming "what is GEO?", "GEO agency pricing" and "the best GEO tool" onto the same URL blurs the answer.

2. Give the real answer in the first paragraph

If the reader wants the definition, give the definition first. Don't hide the answer behind an "in this article we'll learn" intro. There's no rule that a direct answer must be 40 words; the length varies with the question's complexity.

3. Add your own evidence, not commodity information

Generic advice a generative system could write itself has low value. Add an anonymised example from your own process, your measurement method, a local market observation, an original table or an expert decision. Google explains this as "non-commodity content": not a reassembly of the internet's known opinion, but the new value the author adds to the topic.

4. Put the claim and the source side by side

Statistics, legal requirements, product limits and changing platform rules must not stay unsourced. Listing sources at the end is useful, but the reader should also see which link supports which claim. A link to the original document eases both editorial checking and later updates.

5. Keep the page technically accessible

The main text must be visible in the HTML, Googlebot must not be blocked, the URL must be indexable and findable through internal links. Using JavaScript isn't forbidden, but you need to verify the content truly appears after rendering. AI visibility starts not with a separate llms.txt file but with a healthy visibility base in Google Search.

6. Use structured data only for visible content

Article, Organization and other fitting schema types can be useful for Search appearances. But there is no special "AI schema." Google's structured data policies require the markup to correctly represent the page's visible main content — and even correct markup guarantees no rich result.

7. Update the page by outcome

Changing the date is not an update. Check in Search Console which pages appear, in Analytics what arriving users do, and whether the content's changing facts have gone stale. If the answer is still accurate, don't alter the text merely to fake freshness.

How does Google treat AI-written content?

Google doesn't count AI use as an automatic penalty cause. The official guidance on generative AI content says these tools can be useful for research and structuring original content. What gets judged is not the tool's name but the result's accuracy, quality, fit and value to the user.

Where does the risk start?

The risk starts where many pages are created to manipulate rankings without adding original value. Google's scaled content abuse policy doesn't distinguish whether that was produced by AI, humans or a mix. Publishing a hundred weak pages without editorial reading isn't GEO; it's lowering the site's quality floor.

Human editing isn't just style correction

The editor must open the sources, verify the facts, test whether the idea answers the intent and cut the excess sentences. Text "sounding human" isn't enough by itself. Invented experience, non-existent statistics and the same train of thought repeated across articles remain weak content even in natural sentences.

Which AEO and GEO "tricks" won't work for Google?

• "llms.txt is mandatory": Google Search doesn't use this file for AI visibility or ranking. Keep it if another service requires it, but don't promise an effect on Google's results.
• "Text must be split into artificial small chunks": Google has no mandatory chunk size or ideal word count. Use splitting if it helps the reader.
• "Every fan-out query needs its own page": barely differing mass pages can turn into spam risk when they carry manipulative intent.
• "Special AI schema brings citations": no such Google schema type exists. Existing markup must fit the visible content.
• "Fake brand mentions are a GEO signal": a paid, unnatural mention campaign doesn't replace real reputation and can also raise link-spam risk.
• "An agency can deliver 'first place in AI'": generative answers vary by model, query, context and time. A fixed first place isn't a valid measure here.

This list doesn't say "do nothing." On the contrary, it demands work on real editorial links, clear authorship, correct sources, a healthy technical structure and useful visuals. There's just no need to package that work under a new term and sell an impossible guarantee.

How can AEO and GEO results be measured?

As of July 2026, Google Search Console is gradually opening the Generative AI performance report to a portion of sites. The report shows link impressions inside AI Overviews and AI Mode by page, country, date and device. Although this data is included in the regular Performance report's Web search type, the separate report appears only in Search Console properties Google has given access.

The new Search generative AI control option in Search Console is also rolling out gradually. Where it exists on a site property, you can check from Settings whether the site is included in the generative features across AI Overviews, AI Mode and Discover. The official control documentation explains it as an option; it cannot be assumed already present in every account.

Seeing "GEO score: 87" in a third-party tool is comfortable, but no third party has access to Google's internal ranking and AI metrics. The measurement decision should be built like this: did visibility grow, did fitting traffic arrive, and did that traffic convert into business results? Merely collecting screenshots of citations is a report, not a strategy.

AEO and GEO can give a new reporting language. The work itself still rests on three old, hard questions: is the page found, does it give the reader something different from everyone else, can it prove its claims? If the answer is "no," an SEO, AEO and GEO strategy should start by closing that gap — not by creating a new file.