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GEO (Generative Engine Optimization) marks a fundamental shift: the goal is no longer to appear in blue links, but to be cited in AI-generated answers. ChatGPT, Gemini and Perplexity synthesise information from multiple sources and name the brands they consider most relevant. Building visibility for these new engines is now a strategic priority for every business.
What's in this article:
1. What is GEO and how does it differ from SEO?
2. How do AI engines find their answers?
3. Pillar 1: structured data
4. Pillar 2: omnipresence and mentions
5. Pillar 3: social proof
6. Watch the full podcast episode
7. FAQ
8. Conclusion
GEO, or Generative Engine Optimization, is the set of techniques that enable a brand, product or piece of content to be cited in the responses of generative engines like ChatGPT, Gemini, Perplexity or Microsoft Copilot.
The difference from SEO is fundamental: SEO optimises for a click on a link, GEO optimises for a mention in an answer. A traditional search engine presents a list of websites and lets the user choose. A generative engine synthesises information from multiple sources, formulates a response and names the brands it considers most relevant, without the user needing to visit a single site. The goal shifts from being seen to being named. SEO is not dead: its foundations (domain authority, quality content, semantic structure, backlinks) remain solid ground for GEO.
Understanding how AI engines retrieve information is essential for optimising visibility. When a user asks ChatGPT or Gemini a question, the model does not simply search the exact query.
It performs what is called a query fanout: it reformulates the question into several variants, runs parallel searches on a web index, retrieves dozens of sources, breaks them into text blocks called chunks, vectorises them, then selects around twenty representative chunks to inject into the model for the final response. This process is probabilistic: two identical searches can return different sources and produce different answers. For a brand, the challenge is to be present across as many quality sources as possible to maximise the probability of being selected and cited.
Structured data is the foundation of any GEO strategy. When an AI arrives on a website, it does not see colours, buttons or layout. It sees code and data.
Structuring your data means tagging your site with a vocabulary that AI systems understand directly. The reference standard is schema.org, a metadata vocabulary that explicitly qualifies each element: this is a review, this is an address, these are opening hours, this is a product. Semiotic clarity, the ability of each content block to be understood autonomously without additional context, is a key criterion for visibility in AI responses.
The more a brand is mentioned across varied and trusted sites, the greater the chance it will be included in the chunks selected by the AI. This principle transforms link building into mention building.
The goal is to be mentioned, cited and referenced across as many sources as possible, with or without a link. Listicles (articles such as "the 10 best solutions for X") are particularly effective. Press relations take on new strategic importance: being cited in a specialist article or independent comparison directly increases the probability of being selected as a source. The press remains perceived by AI as higher-quality, less biased content than brand-owned pages.
The third pillar is social proof: what others say about you, not what you say about yourself. AI engines give more weight to content produced by individuals than to brand-generated content.
Reviews, forums, video testimonials, social media posts and creator content are sources that generative engines actively exploit. The concept of knowledge graph sits at the heart of this pillar: AI systems build a representation of entities (brands, products, locations) and their attributes from all the content they process. The more positive and consistent the attributes associated with your entity, the higher your citation probability.
This article is based on an AI Corner episode featuring Tibo Renou, co-CEO of Partoo, on generative engine optimisation and the 3 practical pillars for improving brand visibility on AI search engines in 2026.
Watch the full AI Corner episode on YouTube
No. The fundamentals of SEO (domain authority, quality content, semantic structure, backlinks) remain relevant for GEO. The objective changes: you optimise for a mention in a generated response, not only for a ranking in blue links. GEO is an evolution of SEO, not its replacement.
GEO tracking involves testing the same queries a large number of times to identify which sources are scraped and how often your brand is mentioned. It is a probabilistic approach that provides strategic direction rather than an exact measure, sufficient to prioritise your AI visibility efforts.
In SEO, a backlink improves domain authority. In GEO, what counts is the mention: being named in an article, review or comparison, with or without a link. AI engines identify entities cited in text. A mention without a link carries as much weight as one with a link for generative engine visibility.
The first measurable effects of a structured GEO strategy appear within 3 to 6 months. AI Partners integrates generative engine visibility into its AI First Organization programme alongside AI maturity diagnostics and strategic roadmap definition.
GEO changes the way brands build online visibility. Being cited by ChatGPT, Gemini or Perplexity requires structured data, multi-source presence and a reputation built on real user content. AI Partners has supported over 100 companies in their AI strategy with 94% client satisfaction across advisory, training and deployment engagements.
