The Complete Guide to Answer Engine Optimisation (AEO)

What is Answer Engine Optimisation?

Answer Engine Optimisation (AEO) is the term commonly used for the practice of structuring a business's website, content, and online presence so that AI-powered systems, including chatbots, AI search features, and generative answer engines, can more accurately understand that business and surface it in response to relevant queries.

Where traditional SEO is built around ranking a page within a list of links, AEO is built around being correctly interpreted, summarised, and cited within a generated answer. A user searching "best accountant for a small business in Leeds" on Google expects a list of results to click through. The same person asking ChatGPT the same question expects a direct recommendation, and businesses that can be clearly identified and accurately described are better placed to be considered within those recommendations.

AEO isn't a replacement for SEO. It shares the same foundations: technical accessibility, clear structure, genuine expertise, and consistent authority. But it adds emphasis on things that matter specifically to how AI systems process information, such as unambiguous identity, structured data, and consistency across the wider web.

A note on terminology

AEO is sometimes referred to by other names: GEO (Generative Engine Optimisation), AI SEO, or simply "AI search optimisation." Google itself describes AEO and GEO as terms used for work focused on AI-search visibility, while noting that, from Google Search's perspective, optimising for generative AI experiences remains part of SEO, since its generative features are rooted in its core Search ranking and quality systems. AEO is therefore best understood as an emerging specialism within the wider search discipline, rather than a replacement for SEO or a separate field entirely. Echeva uses AEO as a practical shorthand for the broader practice of optimising how a business is understood and surfaced across answer-led and AI-powered discovery.

Why AEO matters now

AI-powered search is no longer a niche behaviour. According to Semrush's 2026 survey of 622 US B2B professionals, 66% said they regularly use AI to research products, vendors, or solutions, and 92% said AI had shaped their vendor shortlist. Google has integrated AI-generated answers directly into Search through AI Overviews and AI Mode, meaning the shift isn't happening on a separate platform. It's happening inside the search engine businesses already depend on.

This creates a new visibility consideration for businesses. Performing strongly in conventional search does not automatically mean a page or business will be surfaced within an AI-generated answer. AI-powered search experiences may use different models, retrieval techniques and supporting sources, so businesses increasingly need to consider both traditional search visibility and how clearly their information can be discovered, interpreted and used within generated answers.

How AI search works, at a high level

When an AI experience uses the live web, it may use search or retrieval systems to find relevant information before generating a response. The exact implementation differs by platform. Google says AI Overviews and AI Mode can issue multiple related searches, sometimes described as "query fan-out," to identify supporting webpages. OpenAI's ChatGPT Search can rewrite a user's prompt into targeted search queries and retrieve information from web sources. Microsoft documents Bing-powered web retrieval within parts of its Copilot ecosystem, including generative answers that draw on Bing search results.

Not every generated answer is produced through the same process, and the platforms do not publish their complete selection or weighting systems. For that reason, credible AEO focuses on the factors businesses can actually influence rather than attempting to reverse-engineer undocumented algorithms.

For search-grounded AI experiences, important pages generally need to be crawlable and available to the relevant search or retrieval system before they can be surfaced as live web sources: the same foundation traditional SEO has always depended on.

A useful way to think about AI visibility

At Echeva, we think about AI visibility through six connected conditions:

These conditions don't represent a guaranteed ranking formula. No such public formula exists, and any provider claiming otherwise should be treated with scepticism. They provide a practical way of understanding why AI visibility is broader than any single technical change, and why a business can be strong on one condition (say, technically accessible) while still being weak on another (say, corroborated by independent sources).

What actually influences AI search visibility

Expanding on those six conditions, in practice:

Technical accessibility. If a page isn't crawlable and indexable, it isn't available to be retrieved by the systems that would otherwise surface it.

Entity clarity (understandable). AI systems need to confidently identify who a business is, what it does, and how it relates to other concepts. Inconsistent naming, vague descriptions, or conflicting information across a website and third-party sources makes this harder.

Content clarity (relevant). Content that directly and specifically answers real questions is easier for a system to extract and reuse accurately than vague, marketing-heavy copy where the actual substance is hard to isolate.

Structured data (understandable). Schema markup gives search engines explicit, machine-readable information about a page's content, which can support clearer interpretation and entity information. It should not be treated as a direct AI-ranking signal or shortcut to being cited.

Authority and corroboration (credible). AI systems appear to weigh source reputation and cross-source consistency. The same fact appearing accurately across multiple independent, credible sources tends to be treated with more confidence than an isolated claim on a single website.

Consistency across the web (corroborated). Beyond a business's own site, how consistently it's described across directories, review platforms, social profiles, and other third-party sources contributes to how confidently an AI system can identify and describe it.

What AEO is not

There's a lot of low-quality advice circulating about AEO, so it's worth being clear about what it isn't:

• It is not adding an llms.txt file and expecting a ranking boost. Google has stated it doesn't use llms.txt for Search, and there are no extra AI-specific technical requirements or special machine-readable files needed for its AI Search features.
• It is not simply adding schema markup and stopping there.
• It is not a replacement for SEO. The two overlap substantially.
• It is not writing every paragraph as a short, robotic 40-word answer purely to game a hypothetical algorithm. Google has stated there's no requirement to chunk content in artificial ways, and producing content at scale primarily to manipulate rankings or generative responses may violate its spam policies.
• It cannot guarantee that ChatGPT, Gemini, or any other platform will recommend a specific business. No credible provider can promise that outcome, because these platforms control their own results.

An example: how ambiguity affects visibility

Common mistakes

Treating AEO as a one-off technical fix. AI visibility depends on an ongoing pattern of clarity and consistency, not a single change applied once.

Chasing unconfirmed "hacks." As above, Google has been explicit that there's no requirement to chunk content, that it doesn't use llms.txt for Search, and that manipulative content at scale risks violating its spam policies. Content built around genuine usefulness holds up better than content built around guessed algorithmic signals.

Ignoring Bing. Microsoft documents Bing as the web-search service used to ground parts of its Copilot ecosystem, and OpenAI lists Bing among the third-party search providers ChatGPT Search may use. That makes Bing visibility relevant well beyond conventional Bing search itself, and it's an area many businesses overlook entirely.

Inconsistent business information. Conflicting names, addresses, or descriptions across a website, directories, and social profiles create exactly the kind of ambiguity that makes it harder for an AI system to confidently identify a business.

Assuming ranking equals visibility. Strong conventional search rankings don't guarantee inclusion in AI-generated answers, since the two systems may use different models and supporting sources.

How should AEO be measured?

AI visibility isn't a single ranking position, so it can't be measured the same way as a traditional keyword rank. Relevant measures can include whether a business appears across a representative set of queries, how frequently and accurately it's mentioned, which sources are being cited alongside it, how it compares to competitors, and whether AI-driven discovery contributes to website visits or conversions.

There's some useful public infrastructure emerging here. Google includes generative AI Search visibility within its broader Search Console performance data and, from June 2026, has begun rolling out dedicated Generative AI performance reports, initially to a subset of UK websites, with wider rollout expected to follow. These reports show impressions, pages, countries, and devices for appearances within features like AI Overviews and AI Mode, though click data isn't included yet. ChatGPT Search can also surface the linked web sources behind its answers, giving businesses another way to observe which sources are contributing to AI-generated responses.

Beyond these platform-provided tools, most organisations are still developing their own approaches to tracking AI visibility consistently, since this remains a newer and less standardised area than conventional rank tracking.

A practical starting checklist

• Confirm important pages can be crawled and indexed by relevant search systems, and check that hosting, CDN, or security settings aren't unintentionally blocking legitimate crawlers (OpenAI, for example, publishes guidance on allowing its OAI-SearchBot; Google requires Googlebot access for its AI Search features in the same way it does for conventional Search)
• Ensure your business name, description, and key facts are stated clearly and consistently across your website
• Check that the same information is consistent across your Google Business Profile, directories, and social profiles
• Add accurate structured data (Organisation, LocalBusiness, Service, or relevant types) where appropriate
• Review your key pages: does the content clearly and specifically answer the questions your customers are likely to ask?
• Check your visibility in Bing, not just Google
• Periodically test how AI platforms describe your business, using the kinds of questions a genuine customer might ask
• If available to you, review Search Console's Generative AI performance report to see how your pages appear within Google's AI features

This is a starting point for understanding where a business stands. A full assessment of AI search visibility typically involves considerably more depth than a single checklist can capture.