Gustav GEO (Generative Engine Optimization) is the practice of structuring and writing online content so that AI-based search tools like ChatGPT, Perplexity, and Google AI Overview select it as a source when generating answers to users' questions.
The background: search is changing
For many years, search worked in one way: a user typed a question into Google, received a list of results, and clicked on whichever looked most relevant. The entire SEO discipline is built around winning that click competition.
That pattern is shifting. A growing share of searches now happens inside AI assistants that do not return a list of links but generate a direct answer. ChatGPT has over 100 million weekly users. Perplexity is growing quickly as an alternative to Google. Google itself has added AI Overview at the top of many search results, an AI-generated answer that appears before users even see the organic results.
The consequence is that a rising portion of the visibility businesses previously gained through clicks now happens through citations in AI answers. And that requires a different kind of optimisation than classical SEO.
How AI search works (simplified)
When a user asks a question in ChatGPT or Perplexity, the model generates an answer based on two things: what it was trained on, and what it can find by searching the web in real time.
For businesses, the relevant part is the real-time search. The tool finds content, evaluates it against a set of signals, and decides what to cite. The signals it weights are similar in some ways to those Google uses: is the content clear and authoritative? Does it answer the question directly? Is the company described consistently across the web? Are there credible other sites that reference it?
GEO work is about strengthening those signals so the answer to those questions is yes.
What GEO concretely involves
GEO is not a single action but a collection of adaptations. The most important are:
- Content structure: text organised so AI models can easily extract precise answers. That typically means clear headings, explicit questions and answers, and short definitions of key concepts.
- FAQ sections: direct Q&A format is something AI models are particularly good at drawing on as a source.
- Schema markup: structured data that tells search engines and AI models exactly what a page is about, who wrote it, and what the business offers.
- Entity consistency: your name, your services, and your location are described in exactly the same way everywhere on the web. Inconsistency confuses AI models and weakens authority.
- Citable content: original data, clear recommendations, and concrete examples are something AI models find easier to use as a source than vaguely worded marketing copy.
Many GEO techniques are the same as good SEO practice. That is not a coincidence: both disciplines reward clear, authoritative, and well-structured content. A solid SEO foundation is the starting point for GEO work.
What it looks like without GEO optimisation
A business without GEO optimisation can rank well in Google and still be invisible in AI search. This typically happens because the content is written to impress humans, not to function as a source for an AI model. Text that is vague, brand-focused, and without concrete answers rarely gets cited, regardless of how well it ranks.
The reverse is also possible: well-structured, specific content can start appearing in AI answers even from pages without a particularly strong traditional SEO foundation. This is one of the interesting dynamics in GEO: newer, thinner sites can compete on content quality rather than domain authority.
GEO and SEO used together
For most businesses, it makes most sense to treat GEO and SEO as two layers within the same strategy. SEO builds the technical foundation and ensures visibility in traditional search. GEO optimises on top of that foundation and ensures visibility in AI-based search, which is growing in use.
A deeper look at the differences between the two disciplines can be found in the article GEO vs SEO: what is the difference?