SEO is no longer enough: how your website gets found on Google and in AI search
In short: Google and AI assistants like ChatGPT, Gemini or Perplexity favour the same websites: clearly structured, technically clean, factual and trustworthy. If you plan for both from the start (structured data, a clear positioning, fast pages and citable content), you get found on Google and cited in AI answers. This article shows the six building blocks that make it work.
For years, the central question in every website project was: How do we get to page 1 on Google? It isn't wrong, but it is becoming half the truth. More and more people no longer research through a list of blue links; instead they let ChatGPT, Gemini, Perplexity or the AI overview right inside Google search hand them a finished answer. In those answers there are no ten spots. There is only a handful of sources that get cited, and there is everyone else.
The decisive question therefore shifts from “Are we ranking?” to “Are we being cited?”. Anyone optimising a website for search engines today should keep both in view. The good news: the measures that make you visible in AI search are almost identical to those that also improve your Google ranking and the user experience. It is not a contradiction but the same foundation, just thought through more rigorously.
What is GEO (Generative Engine Optimization)?
GEO stands for Generative Engine Optimization, i.e. optimising a website so that generative AI systems such as ChatGPT, Google AI Overviews, Gemini or Perplexity understand it correctly and cite it as a source. GEO does not replace classic SEO; it extends it. While SEO optimises for a click in the results list, GEO optimises for a mention in an AI-generated answer.
Figure 1: SEO optimises for the click, GEO for the mention.
What is changing in search right now
Classic SEO optimises for a click: you appear in the results list, the user chooses you, they land on your page. AI search optimises for a mention. A language model reads the web, forms an understanding of your offering and passes that understanding on to the user in its own words - sometimes with a link, sometimes only as a recommendation.
This has two consequences for every website:
- Machines have to understand you, not just find you. An AI does not skim your page visually. It processes structure, facts and relationships. The more clearly you explain who you are, what you offer and for whom, the more reliably you shape the AI's answer instead of leaving it to guess.
- Trust becomes the currency. AI systems and Google preferentially cite sources that are clear, factual and consistent. Vague marketing phrases are worthless to a language model. A precise statement with concrete details is citable.
Six building blocks of a website that convinces Google and AI
Figure 2: the six building blocks at a glance.
1. A clear, citable positioning - identical everywhere
Most websites describe themselves a little differently on every platform: one slogan in the header, a different text in the footer, something else again on social networks. For people that is forgivable; for machines it is noise.
Formulate one concise sentence that captures your offering: who you are, what you do, what sets you apart. Then use exactly this sentence consistently - on the homepage, in the meta description, in the preview texts for social networks and in the machine-readable data. When human, search engine and AI read the same core statement, a clear, repeatable picture emerges. That is exactly what a language model rates as reliable.
2. Structured data: your website's “machine language”
Behind every good website today lies an invisible layer that hands machines the facts in an unambiguous form: This is a company. This is its address. These are the opening hours. This is a review. This is a frequently asked question and its answer. This structured data (in the Schema.org standard) is the difference between “the AI has to guess from the body text that you are based in region X” and “the AI knows it beyond doubt”.
The leverage is large and yet often used half-heartedly. In our projects it is regularly the biggest untapped advantage. Anyone who works cleanly here - maintaining a coherent model of the company, the locations, the offerings and the FAQs instead of scattered snippets - gains a measurable edge. Local details in particular (location, contact, opening hours) and FAQ content are exactly the material from which Google builds rich snippets, AI answers and voice search.
3. A “manual” for AI: the llms.txt
Search engines have known the robots.txt and the sitemap for years - signposts for crawlers. For AI systems a counterpart is currently establishing itself: the llms.txt, a compact text file that summarises your offering in clear language and points to the most important pages. Instead of letting an AI stumble through nested menus and scripts, you give it a curated short version of your website: positioning, most important pages, one sentence per area.
It is not mandatory and (yet) not an official ranking factor. But it is a cheap, future-oriented signal. You make it easy for language models to represent you correctly and reduce the risk of them summarising you wrongly.
4. Content an AI can cite
Language models and Google's algorithm prefer content they can take over directly. In concrete terms:
- Factual instead of vague. “We deliver within 48 hours across the entire DACH region” is citable. “We place great value on fast delivery” is not.
- Answer questions the way people ask them. An FAQ section on the most important pages hits exactly the phrasings users type into Google, voice search and chat, and is the direct template for featured snippets.
- Structure that isolates statements. Definitions, short tables, numbered steps - formats from which a single, correct statement can be extracted.
- Evidence instead of claims. Experience, references, qualifications, real contact details. Google sums this up as E-E-A-T (Experience, Expertise, Authoritativeness, Trust), and AI systems follow the same instinct.
Important: none of this means bloating texts for machines. Every statement must serve the user first. Content that helps people is exactly what gets ranked and cited.
5. Technical SEO hygiene: the invisible foundation
Much of this only holds if the craft is right. And this is exactly where a surprising number of sites fail on the basics:
- One topic per page. Every page owns a clear focus with a unique title and its own meta description. Otherwise overlapping pages compete against each other (keyword cannibalisation).
- Unique titles and descriptions per page, with the central search term and, where it makes sense, the location. Not the same default text everywhere.
- Clean crawling: a working XML sitemap, correct canonical tags (which version of a page counts), no dead ends, short click paths.
- Multilingual content correctly marked up (hreflang) when content exists in several languages. Otherwise Google sees duplicates instead of language variants.
- Speed and mobile first. Fast load times (Core Web Vitals) and a flawless mobile display are no longer a bonus but the entry ticket - for users as much as for ranking. In Germany, roughly two out of three visitors arrive via smartphone.
6. Freshness and trust
Both Google and AI systems prefer content that is visibly maintained. A visible “last updated on”, regularly revised core pages and consistent company details across all channels signal: this source is alive and reliable. Outdated opening hours or contradictory addresses cost exactly the trust that decides visibility.
What this means for your website project
The temptation is great to treat SEO and “AI optimisation” as two separate projects: first the website, then “the AI thing” at some point. That is the expensive route. Structured data, a clear positioning, clean technology and citable content can hardly be stuck on afterwards. They emerge from a website's architecture.
That is why we think both through from the start. When we build a website, the machine-readable foundation belongs in the blueprint and not in a downstream optimisation step: structured data, consistent positioning, technically clean and fast pages, plus content that answers real questions. The result is a site that ranks on Google today and gets cited in AI answers tomorrow, without having to touch it twice.
The core rule stays simple: never optimise for the machine at the expense of the human. A website that is clear, honest and helpful for users is automatically the website that search engines rank and language models cite. Everything else is craft.
Are you planning a new website, or wondering whether your current site is ready for Google and AI search? Talk to us - we will take a look at your foundation.
Frequently asked questions about SEO and AI search
Is GEO (AI optimisation) something different from SEO? It is an extension, not an opposite. GEO builds on the same foundation (clean technology, clear structure, trustworthy content) but places additional emphasis on machines being able to extract and cite facts unambiguously.
Do I have to rewrite my texts for AI search? Do not rewrite - sharpen. Concrete, factual statements and an FAQ section that answers real questions help users and AI alike. Bloating content just for machines harms both.
What is an llms.txt and do I need it? A compact text file that summarises your offering for language models and points to the most important pages. It is not an official ranking factor, but a cheap signal that helps AI systems represent you correctly.
How quickly will I see results? Technical improvements (speed, structure, structured data) take effect over a matter of weeks. Visibility in AI answers and building trust are a longer process - but it starts with the same foundation.
Do I need long texts for good ranking? No. What matters is that the content fully satisfies the search intent, not the word count. A precise, well-structured answer beats a bloated text.