What is answer engine optimization (AEO)?

Short answer: AEO is mostly the same work as good SEO, aimed at a new place where the answer appears. The platforms’ own documentation asks for very little beyond letting their crawlers in and being indexable. Everything below is labelled as platform documentation, a research finding or our recommendation, so you can see what kind of claim each one is.

AEO in plain English

Someone asks a question. Instead of a page of links, they get a written answer with a few sources attached. AEO is about being one of those sources, or at least being a page the system can reach, make sense of and quote accurately.

In practice that means pages that can be crawled and indexed, plain answers near the top, and facts about your business that say the same thing everywhere. If that sounds like good SEO, that is because most of it is.

The term is young, and agencies and tool vendors define it slightly differently. Some present it as a new discipline with its own toolkit. Others use it as another name for work you may already be doing. What follows is our reading, and it is a recommendation.

AEO, GEO and SEO: are they different things?

Our recommendation: treat them as overlapping labels for the same work.

Term	Usually means	Where the result appears
SEO (search engine optimisation)	Being found and ranked in search results	Lists of links
AEO (answer engine optimization)	Being the source a system quotes when it answers a question directly	AI answers, assistants, answer boxes
GEO (generative engine optimisation)	Being used and cited when a generative AI system composes an answer	AI answers from ChatGPT, Perplexity, Claude, Gemini, AI Overviews

AEO and GEO describe nearly the same target, and you will see them used interchangeably. Both rest on SEO foundations: a page that cannot be crawled or indexed cannot be quoted. Arguing about the label will not change a single answer, so spend the time on the pages. For the longer version, see what GEO is and how GEO compares with SEO.

What answer engines are and how they produce answers

An answer engine replies to a question with a written answer, usually with links to its sources. ChatGPT search, Perplexity, Claude and Google’s AI Overviews and AI Mode all work this way.

The detail differs by platform, but the broad shape is the same. The system has to reach your page, either through its own index or by fetching it when a user asks. Then it has to read the page and decide whether to use it.

Platform documentation: Google says AI Overviews and AI Mode may use “query fan-out”, issuing multiple related searches across subtopics and data sources to build a response, which lets them show a wider set of supporting links. The mechanics are covered in how AI answers happen.

What the platforms themselves say you need to do

These points are all platform documentation, taken from each company’s own pages.

Google (AI Overviews and AI Mode). Google says there are no additional requirements to appear in AI Overviews or AI Mode, and no special optimisations are necessary. A page has to be indexed and eligible to appear in Search with a snippet. You do not need to create new machine-readable files, AI text files or markup, and no special schema.org structured data is required. Inclusion is still not guaranteed. To limit what is shown from your pages, Google points to nosnippet, data-nosnippet, max-snippet and noindex. Traffic from these features is counted in your overall Search Console figures, under the “Web” search type.

OpenAI (ChatGPT). OpenAI runs separate user agents, and each setting is independent. OAI-SearchBot is for search: sites that block it will not be shown in ChatGPT search answers, though they can still appear as navigational links. GPTBot crawls content that may be used to train OpenAI’s models, so you can block GPTBot and still allow OAI-SearchBot. ChatGPT-User visits pages when a user asks, and OpenAI says robots.txt rules may not apply to it. OpenAI notes that changes to robots.txt can take about 24 hours to take effect for search.

Perplexity. PerplexityBot surfaces and links websites in Perplexity’s search results, and Perplexity says it is not used to crawl content for AI foundation models. Perplexity-User fetches pages when a user asks a question, and because a user requested the fetch, it generally ignores robots.txt rules.

Anthropic (Claude). Anthropic lists three bots. ClaudeBot collects content that may be used for training. Claude-User fetches pages when people ask Claude questions. Claude-SearchBot indexes content to improve search results. Anthropic says that blocking Claude-User or Claude-SearchBot may reduce your site’s visibility in user search results.

The pattern is clear: most platforms separate the bot that finds pages for answers from the bot that collects training data. That gives you a real choice. You can stay visible in answers while opting out of training. robots.txt is the shared mechanism, and it is now a standard (RFC 9309). The RFC itself says its rules “are not a form of access authorization”: they ask crawlers to behave, they do not lock anyone out. The practical set-up is in crawler access.

On llms.txt: llmstxt.org describes it as “a proposal to standardise on using an /llms.txt file” to help AI agents use a website. None of the platform pages above say they require one, and Google says outright that AI text files are not needed for its AI features. Adding one is optional.

What the research shows, and its limits

Research finding: the paper that named the field is Aggarwal et al., “GEO: Generative Engine Optimization”, accepted to KDD 2024. The authors built GEO-bench, a benchmark of 10,000 queries drawn from several sources, and tested ways of rewriting source content to see which raised its visibility in generated answers. In their tests, adding citations to sources, adding relevant quotations and adding statistics performed best. Keyword stuffing, the classic SEO trick, did not perform well. The abstract reports visibility gains of up to 40%, and the authors found that what works varies by subject area. They also ran the same methods on Perplexity.ai and report gains of up to 37% there.

The limits matter as much as the results:

• The main experiments used a generative engine the authors built themselves. It was based on GPT-3.5 and fetched only the top five Google results for each query. Today’s assistants work differently and change often.
• Visibility was measured with the authors’ own metrics, some of which were scored by an AI model.
• “Up to” figures are best cases under test conditions. They are not forecasts for your site.

Read the paper as evidence that content choices can change visibility in AI answers. It shows nothing about what will happen to your pages next month.

A practical AEO checklist (our recommendations)

These are our recommendations, based on the documentation and research above. None of them guarantees inclusion. The thinking behind them is in principles.

1. Let the search crawlers in. Check your robots.txt, and any firewall or bot protection, for OAI-SearchBot, PerplexityBot, Claude-SearchBot and Googlebot. Decide separately whether to allow the training bots (GPTBot, ClaudeBot).
2. Be indexable. Confirm in Google Search Console that your key pages are indexed and can show a snippet. Google says nothing more is required for its AI features.
3. Answer the question early. Give a direct, plain answer near the top of the page, then the detail.
4. Back up claims. Cite sources and give specific facts. This matches what did well in the GEO study, but only claim figures you can stand behind.
5. Keep your facts consistent. Your name, what you do, where you work and your prices should say the same thing on your site and your profiles.
6. Skip paid shortcuts. Be wary of anyone selling special markup or files as a route into AI answers. The documentation above does not support it.

How to tell whether it is working

No platform gives you a single report of how often you were quoted. Google counts AI feature traffic within your normal Search Console totals, so you cannot pick it out from there.

Our recommendation:

• Write down the questions your customers actually ask. Put them to ChatGPT, Perplexity, Claude, Gemini and Google on a fixed schedule, and note whether you are named or linked.
• Check your server logs for visits from the search bots you allowed, which confirms that access is working.
• Watch referral traffic from AI tools in your analytics, alongside your normal search performance.

Answers change from one asking to the next, so one appearance tells you little. A pattern over several checks tells you more. More on this in measuring progress.

What AEO cannot promise

It cannot promise inclusion. Google says plainly that appearing is not guaranteed, and no agency, tool or consultant controls what an answer engine decides to say.

It cannot promise a traffic figure either. Be sceptical of any page that quotes one without a source you can open and read. Platforms change how they work and update their documentation to match, so check the sources on this page before relying on any summary of them, ours included.

What AEO can do is make your pages easier to reach, read and quote. That is a modest claim, and it is the one the evidence supports.