Foundation<\/strong><\/td>\n| Technical accessibility, authoritative content, E-E-A-T<\/td>\n | The same foundation as classic SEO<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n It is important to note that GEO does not replace traditional SEO. A website that is not technically accessible or professionally credible will not perform well in either standard search results or AI-generated responses. GEO builds upon the work already done in search engine optimization and expands it with a focus on citability in AI engine responses. It is an extension, not a replacement.<\/p>\n For a comprehensive overview of what SEO is and the elements it covers, please refer to the dedicated article on the topic.<\/p>\n Why GEO Matters Now<\/h2>\nAn increasing portion of a buyer\u2019s research no longer begins with a traditional search result, but with a conversation with an AI assistant. ChatGPT, Perplexity, and Google AI Overviews are used to ask questions, compare options, and narrow down a list before the buyer even visits a supplier\u2019s website. This shifts part of the early research phase into an environment where the answer is often presented as a summary citing a few sources.<\/p>\n This is where GEO comes into play. When an AI assistant summarizes a topic and references certain sources, those sources are the ones that come into play early in the customer journey. If your content isn\u2019t retrieved and cited, you won\u2019t be part of the conversation the buyer is having before they decide who to look into further. Generative AI SEO is about strengthening the conditions for being cited in that situation\u2014not about promising that an AI assistant will recommend you.<\/p>\n This is a new field, and behavior is constantly changing as AI assistants evolve. Therefore, the point is one of principle rather than a specific number: As more research is conducted using AI assistants, it becomes more valuable to be a source they can find and cite. GEO is part of an overall SEO strategy, not a discipline in its own right.<\/p>\n How AI Selects and Cites Sources<\/h2>\nTo understand how you get cited, it helps to look at how individual AI assistants actually obtain the information they use to generate their responses. There is a fundamental distinction here that is worth knowing.<\/p>\n Some AI assistants retrieve sources from the web at the exact moment the question is asked. This is called retrieval: The assistant searches in real time, scans a selection of pages, and bases its response on what it finds at that exact moment. Other responses, however, draw on the model\u2019s training data\u2014that is, the material the model was trained on\u2014which remains fixed until the model is updated. The difference is concrete. A response based on live retrieval can reflect content that was published recently, while a response based on training data is limited to what the model knew when it was trained.<\/p>\n The assistants that retrieve information in real time typically present citations with links to the sources on which the response is based. ChatGPT Search and Perplexity both display sources that the user can click on and that the response is based on. OpenAI describes this exact mechanism for ChatGPT Search, where responses are supplemented with links to relevant sources from the web (OpenAI\u2019s description of ChatGPT Search). On Google\u2019s side, results from AI features such as AI Overviews are incorporated into standard search results, as documented by Google in Search Central (Google Search Central\u2019s documentation on AI features).<\/p>\n How citations are displayed and how many sources are highlighted varies from assistant to assistant. ChatGPT, Claude, and Perplexity handle source presentation differently, and an assistant without real-time data retrieval will not necessarily point to a specific source in the same way as one that searches in real time. The actual selection depends on the individual assistant, and there is no public documentation on how the internal prioritization of sources takes place. Therefore, it is more accurate to describe the observable behavior than to speculate on the logic behind it.<\/p>\n However, one prerequisite applies across the board: technical accessibility. If a page cannot be crawled or rendered by the bots that fetch content, it cannot be included in a response based on live fetching. This makes technical SEO a cornerstone before any of the other factors even come into play. A website that is crawlable and renders quickly is a prerequisite for being fetched and cited\u2014not a guarantee that it will happen.<\/p>\n How to Use GEO<\/h2>\nGEO adapts traditional SEO to a world where generative AI reads, evaluates, and cites content. In practice, the work centers on three prerequisites for becoming the source that an AI engine highlights. None of them guarantees a citation, but together they strengthen the conditions for your content to be found, understood, and used.<\/p>\n \n- Citable content:<\/strong> Clear, standalone answers and definitions that an AI engine can extract from context and reproduce directly.<\/li>\n
- Technical accessibility:<\/strong> The content must be crawlable and renderable by AI bots before it can be cited. This is part of the technical foundation you\u2019re familiar with from technical SEO.<\/li>\n
- Documented authority:<\/strong> E-E-A-T and external sources that support the credibility of what you write. This is where generative AI SEO overlaps with link-building efforts.<\/li>\n<\/ul>\n
These three pillars aren\u2019t a new discipline with its own set of rules. They\u2019re based on the same core principle as SEO for AI: content that\u2019s easy to understand, easy to access, and trustworthy. If you\u2019d like to read more, this is closely tied to an overall SEO strategy and the work done at an AI agency.<\/p>\n |