GEO, AEO, SEO: Visible on Google and in AI responses

Rankings, getting answers, being quoted. Three goals, three disciplines, one common foundation. If you focus on just one of them, you’ll miss out on visibility. This overview shows you how SEO, AEO and GEO work together.

SEO, AEO and GEO at a glance

SEO ensures that you are found in traditional search results, AEO ensures that you are displayed as a direct answer, and GEO (Generative Engine Optimisation) ensures that AI systems quote you in their answers. All three build on one another; none replaces the other.

Google is demonstrating just how much search itself is currently changing at its own I/O Conference 2025, where the new AI Mode was unveiled as a standalone, heavily AI-powered search interface.

For brands, this means that visibility now occurs on three levels simultaneously, rather than just in a list of results.

This pyramid has a foundation and two successive layers. SEO forms the basis; AEO builds on this in terms of both technology and content; GEO, in turn, uses both as a foundation to succeed in generative AI responses. Anyone who ignores this sequence and tries to start directly with GEO is building on sand.

These three terms have emerged almost incidentally in recent years because search behaviour itself has changed. Just a few years ago, a search query almost always meant opening a list of results and clicking on one. Today, the search engine answers many questions directly on the results page itself, and a growing proportion of queries are directed straight to an AI system, without any traditional list of results in between.

SEO as a foundation: getting found in search results

SEO remains the foundation of all digital visibility, because technical soundness, relevant content and authority continue to determine whether a page is even considered. AI search has not fundamentally changed this.

Google confirms this in its own documentation AI Features and Your Website: There is no separate set of rules for AI visibility; instead, the same basic principles that apply to traditional ranking still hold true, supplemented by additional requirements regarding clarity and structure. So anyone who carries out good technical SEO work, maintains clean meta data and writes content that actually answers questions has already met the most important prerequisite for the following two levels.

The difference lies in the objective. Traditional SEO optimises for a position in a list of results that a person scrolls through. This remains relevant, particularly for search queries with a clear intention to buy or a local focus. But it is now just one of three targets.

It is important to note that traditional SEO factors such as page load time, mobile usability, clean internal linking and topical authority do not lose their importance as a result of AEO and GEO; on the contrary, they become the key to success. An AI system will not cite a page that it finds technically difficult to crawl or difficult to categorise in terms of content.

In practice, this means that focusing solely on new GEO tactics is of little use as long as the fundamentals are shaky. A slow website, duplicate content or an unclear page structure harm visibility across all three levels equally, not just in terms of traditional rankings. So, for anyone wondering where to start, here is the most honest answer: with precisely those things that have always been essential to good SEO.

AEO: to be played out as a response

AEO, or Answer Engine Optimisation, aims to ensure that content is displayed directly as an answer, for example in featured snippets, voice assistants or the direct answer boxes in search results. The aim is no longer the click, but the answer itself.

For this to work, content must be presented in a format that is easy to extract: a clear question, followed directly by a precise answer, without any lengthy introduction. This pattern is clearly illustrated in Zendesk’s FAQ section, ‘Frequently asked questions, answered’.

The layout there follows the same principle that also favours featured snippets: the question is displayed first, followed immediately by the answer, with no detours – a pattern that works for both traditional snippets and AI-generated answers.

AEO is therefore less a new technology than a writing discipline. Anyone who structures their content to be answer-oriented from the outset automatically provides the raw material that both voice assistants and search engine answer boxes need. In practical terms, this means that when writing, headings should be phrased as much as possible like genuine questions, and the very first sentence following the heading should already contain the answer – not only after two introductory sentences.

It is just as important how a paragraph ends as it is how it begins. A sentence containing a figure, a clear statement or an unambiguous recommendation is easier for a system to extract as a standalone answer than a paragraph that ends in vague terms. If you want to check whether a particular section is suitable for AEO, you can ask yourself whether the first sentence alone, taken out of context, still makes a meaningful, complete answer.

GEO: being quoted in AI responses

GEO, or Generative Engine Optimisation, aims to be named or cited as a source in the responses of generative AI systems such as ChatGPT, Perplexity or Google’s AI Mode. The term originates from a Research conducted at Princeton University from 2023, which was the first study to systematically examine how content can be optimised for generative search systems.

It is this academic background that sets GEO apart from a mere marketing buzzword. An analysis by Search Engine Land shows just how quickly this new search dimension is actually developing: according to the analysis, AI sessions on websites have increased by around up 527 per cent. Unlike with traditional SEO, what matters most to GEO is not the ranking but the citability of the content: whether it is structured clearly enough, up to date enough and authoritative enough for an AI system to use it as evidence.

Another difference concerns the visibility of one’s own impact. With GEO, measuring success is more difficult because a mention in an AI response is not always associated with a traditional click. Companies should therefore consider at an early stage how they can distinguish AI referral traffic from traditional search traffic within their analytics environment.

Added to this is a practical implication for content maintenance: generative systems favour content that is recognisably up to date, because timeliness is a sign of reliability. An article that has not been revised for years will struggle to compete with freshly updated rival content, even if the original message is still factually correct. Anyone wishing to optimise their content for GEO should therefore schedule a fixed update cycle for their most important pages, rather than publishing content once and leaving it untouched indefinitely.

How the three layers interact

SEO, AEO and GEO work together because they are based on the same fundamental building blocks, albeit with different areas of focus. A website with a sound technical foundation, a clear response structure and up-to-date, well-sourced content generally serves all three levels simultaneously.

Google CEO Sundar Pichai has commented on this delay himself: "Search would be an agent manager in which you do a lot of different things." Search is thus increasingly becoming a system that performs many tasks simultaneously, rather than simply providing a list of links.

For brands, this means in practical terms that those who rely solely on SEO will be found in the traditional search results, but are less likely to appear in answer boxes and AI-generated responses. Those who rely solely on quick GEO tricks without maintaining a solid SEO foundation often have no basis at all from which an AI system could even draw information. A product page with a solid technical SEO foundation, supplemented by a clearly formulated Q&A section and up-to-date, well-sourced information, therefore often serves all three levels simultaneously, without the need for three separate content strategies.

Where to start: Setting priorities

The most sensible approach is to follow the foundational steps in order: first, get your SEO right; then, structure your content to provide answers; and finally, optimise it specifically for generative systems. If you reverse this order, you’ll be wasting your efforts.

In our own practice – which we also discussed in podcast episode 2 on modern search visibility – a clear pattern emerges: the companies that appear most quickly in AI responses are almost always those that already had a solid SEO foundation. GEO is rarely a fresh start; it’s usually a further development.

Another common mistake in practice is trying to tackle all three levels at once and with the same level of intensity. This usually means that none of the three levels is implemented properly. A more sensible approach is to proceed in stages: first, bring the most important pages up to SEO standard in terms of both technical aspects and content; then, add clear answer structures to precisely these pages; and only in the third step, work specifically on ensuring the content is up to date, the sources are clear and the content is citable for generative systems.

If you want to tackle the subject systematically, you’ll find in the complete GEO Guide the recess at GEO level, and in A direct comparison of SEO and GEO a clearer distinction between the two disciplines. To help you implement this in practice within your organisation, we can support you with Generative Engine Optimisation with pechschwarz.

Ultimately, it is worth taking a sober look at the effort involved. None of the three levels requires a complete rethink of content production; above all, they demand discipline, maintaining a solid technical foundation, formulating clear answers, and taking sources and up-to-date information seriously. It is precisely this discipline that ultimately distinguishes brands which appear in all three environments from those which are now only visible in the traditional search results, whilst a growing proportion of their own target audience has long since been using AI systems to search.