What Is AEO (Answer Engine Optimization)? What the Evidence Says

AEO means preparing your content so Google, ChatGPT or Perplexity cite it in their answers. What their official docs support and what still has no evidence.

info Quick Definition

AEO (Answer Engine Optimization) is the name the industry uses for preparing a site so AI answer engines (Google AI Overviews and AI Mode, ChatGPT search, Perplexity, Claude with web search) can read it and cite it in a generated answer. It is not a standard or a feature with its own settings: it is a marketing term, and much of what is promised under that name has no public evidence.

What is an answer engine, and why does the goal change?

An answer engine replies with generated text and links the sources it used. Google’s documentation describes this for AI Overviews and AI Mode, which show supporting links. OpenAI explains that OAI-SearchBot is used to surface websites in ChatGPT’s search features. Perplexity says PerplexityBot is meant to surface and link websites in its results. Anthropic says Claude provides direct citations when it uses information from the web.

What winning means changes: it is no longer only a click, it is also being cited. And the citation is rarely followed. A Pew Research Center study (July 2025) tracked the browsing of 900 U.S. adults during March 2025, covering 68,879 Google searches, 12,593 of them with an AI summary. With a summary, people clicked a traditional result in 8% of visits; without one, in 15%. Only 1% of visits with a summary included a click on a link inside the summary, and 26% ended the session, versus 16% without a summary. This is Google data, from the United States, in 2025.

How does it differ from SEO?

	SEO	AEO
Goal	Position and click	Appear as a source inside the answer
What decides it on Google	Indexing, relevance, quality	The same, according to its documentation
Usual measure	Position, impressions, clicks	Times you are cited across a set of questions
Standard metric	Yes	No

According to Google’s documentation, a page must be indexed and eligible to be shown in Search with a snippet to appear in AI Overviews or AI Mode, and there are no other technical requirements. It adds that indexing and serving are not guaranteed. For Google, then, AEO and SEO share the same base. What is sold as AEO is mostly writing and measurement adjustments on top of that base.

What does the evidence say about what gets cited?

Less than vendors promise. Google, OpenAI, Perplexity and Anthropic do not publish, in the pages I reviewed, the criteria they use to choose sources; they only explain which crawlers to allow. What exists is this:

One experiment with a published method. The paper “GEO: Generative Engine Optimization” (Aggarwal et al., accepted at KDD 2024) tested nine techniques on GEO-bench, a set of 10,000 queries, using a generation model (gpt-3.5-turbo) and the top five Google results. Adding source citations, quotations and statistics improved visibility by 30 to 40% on its main metric. Keyword stuffing did not help. In a test on Perplexity.ai with 200 samples, keyword stuffing came out 10% worse than the baseline. Limit: it is a lab setting with an older model and it does not measure real traffic.
Vendor studies, observational. Seer Interactive (July 2026) analyzed pages cited by ChatGPT, Gemini and Perplexity for four brands: about 75% had been updated in the last year. But it started from pages that were already cited, so it does not show that updating causes citations. Something Inc. (4,100 B2B queries, April to June 2026) found that formats with a clear, citable verdict beat narrative content; that company sells GEO services. Ahrefs (October 2025) found that 28.3% of the thousand pages ChatGPT cited most in September 2025 had no organic keywords, and that only 32.3% of citations were of types a brand can influence.
Weak correlations. Wellows (9,471 questions, five engines, January to May 2026) found correlations between 0.13 and 0.29 for its coverage measure, the lowest on ChatGPT. Its own authors state that it does not show that publishing more or earning links increases citations.

Conclusion: there are signs that answers with data and sources, and maintained content, get cited more, but no study cited here proves causation in today’s engines.

What can you do with official backing?

Allow search crawling. OpenAI recommends allowing OAI-SearchBot in robots.txt, and notes a change can take about 24 hours to apply. Perplexity recommends allowing PerplexityBot. Anthropic says disabling Claude-SearchBot may reduce your visibility in user search results.
Do not confuse search with training. GPTBot (OpenAI training) is independent of OAI-SearchBot (search). PerplexityBot, according to Perplexity, is not used for foundation models. Blocking one does not block the other.
Follow Google’s basics: helpful, unique content, important content in text form, internal links, good page experience, and structured data consistent with the visible text. Avoid restrictive nosnippet and max-snippet settings: according to Google, they limit how your content appears in its AI features.
Do not invest in what Google says is unnecessary: AI text files, special markup or special schema.org data. That page does not name llms.txt, and the OpenAI, Perplexity and Anthropic pages I reviewed talk about robots.txt, not llms.txt.

Writing practices (a direct answer up front, data with sources, a visible update date) are reasonable for readers and have some evidence in their favor, but no official document promises them as a citation factor: treat them as hypotheses. If you also design the interface that shows citations, see citations and sources in AI answers.

How do you measure whether it works?

There is no standard metric. Google says traffic from AI Overviews and AI Mode is included in the Search Console performance report, under the Web search type, without separating it. For citations, run your own test: pick a fixed set of questions, ask them in each engine, note which sources appear and repeat from time to time. Answers vary from one run to the next, so repeat several times before drawing conclusions, as Something Inc. did by running each query three times. To see how a conversational engine chains questions and sources, read conversational search and RAG.

Example

Illustrative example: a design agency wants to appear when someone asks “what is a design system?”. It checks that its robots.txt does not block Googlebot, OAI-SearchBot or PerplexityBot, and that the page has no nosnippet. It puts the definition in the first sentence, with three criteria and a source, and a visible update date. It defines 20 questions and, each month, records in a spreadsheet how many cite its page in each engine. If citations go up, it cannot claim the change caused it: the engines change too.

Common mistakes

Buying an AEO service that promises a number of citations or a traffic increase without showing method or open data.
Blocking OAI-SearchBot believing it blocks training, or allowing GPTBot believing it gets you into search.
Repeating keywords: the GEO experiment found no improvement.
Putting nosnippet on pages you want cited.
Concluding causation from a single test or a single engine.

Sources

Frequently asked questions

What is AEO?

AEO (Answer Engine Optimization) is the name the industry uses for preparing content so AI answer engines cite it. It is not a technical standard: Google says there are no additional requirements to appear in its AI features.

What is the difference between AEO and SEO?

The goal changes: SEO aims for ranking and the click, AEO aims to appear as a source inside a generated answer. In practice, according to Google’s documentation, the base is the same: an indexed page, eligible for a snippet, with helpful content.

What makes an answer engine cite a page?

No engine publishes its criteria. There is one academic experiment (GEO, KDD 2024) and some vendor studies with partial results, and none proves a recipe that works today across all engines.

Do I need a special file or markup to appear in AI Overviews?

No. Google’s documentation says you do not need machine-readable files, AI text files, special markup or special schema.org data to appear in AI Overviews or AI Mode.

How do you measure AEO?

With your own test: a fixed set of questions, repeated in each engine, noting which sources they cite. Google counts traffic from its AI features inside the Search Console performance report, with no separate breakdown. There is no standard metric.