Search engines have long been the most important entry point to the internet. However, with the growing use of generative AI systems such as ChatGPT, Copilot, and Perplexity, search behavior is changing noticeably. Users no longer expect only lists of links, but also direct, context-related answers.
Visibility is therefore no longer limited to Google's classic search results lists, but also extends to AI overviews (AI-supported summaries) and responses from chatbots. Being present there can build trust – at almost every stage of the customer journey, regardless of whether users are looking for initial guidance or making decisions about relevant providers. This means that, in addition to classic SEO, generative engine optimization (GEO) is also coming into focus.
Search engine optimization (SEO) remains the foundation. It ensures that content is technically clean, clearly structured, and can be found by traditional search engines such as Google. This includes proven measures such as the use of relevant keywords (search terms), backlinks (links from other sites to your own website), meta tags (titles and descriptions that help search engines interpret content correctly), and good technical performance.
Generative Engine Optimization (GEO) – often referred to as AI SEO – expands on this approach. Content is prepared in such a way that it can be understood by large language models (LLMs) such as ChatGPT, Gemini, or Claude and integrated into answers. What counts here is quality, clear structure, precise answers – and content that is supported by verifiable sources, such as studies, specialist articles, or your own data.
The difference is evident in the result: Google presents many links from which users can choose. Generative systems, on the other hand, provide a single, condensed answer – sometimes supplemented by tables, code snippets, or PDFs. For companies, this means that visibility is not only measured in clicks, but also by whether a brand is mentioned or cited in this answer at all.
To understand how companies can prepare their content for this new type of visibility, it is worth taking a look at how generative systems actually generate answers.
Generative systems combine three levels:
This results in a response that is condensed, multimodal, and often more trustworthy than a long list of results. For companies, this represents a kind of paradigm shift: in the future, content should be designed in such a way that it can be reliably understood, processed, and cited by AI systems. In the next step, we will show some key areas of action that can be addressed immediately.
In addition to classic metrics such as rankings, click-through rates, and conversions, B2B companies should also track how often their brand is mentioned in AI overviews or generative responses. This reveals whether content is not only findable in Google, but also relevant for generative systems.
A simple test – enter typical customer questions into ChatGPT, Copilot, or Perplexity and check whether your brand appears. If it is missing, this could indicate gaps in your content or external image.
Generative systems place great value on external signals: specialist articles, studies, and customer projects are important indicators of trustworthiness. E-E-A-T criteria (expertise, experience, authoritativeness, trustworthiness – a quality framework used by Google and increasingly also by AI systems) also play a central role. It is therefore advantageous not only to have good content on your own website, but also to have a strong, visible profile in the market as a brand.
Without a clean technical foundation, optimizations cannot reach their full potential. This includes fast loading times, structured data (e.g., using Schema.org for FAQs or product information so that machines can better understand content), and a clear website architecture. An important tool is FAQ markup – a code snippet that technically marks frequently asked questions and answers so that search engines and AI systems can recognize and process them directly. Only when content is machine-readable and technically accessible can it appear in search engines and generative models.
Generative systems prefer content that directly addresses questions, is clearly structured, and is easy to process. FAQ sections, step-by-step instructions, or tables provide an ideal basis for this. It is important to choose language and structure in such a way that even complex B2B topics are formulated in a comprehensible and unambiguous manner.
For B2B companies, the question is not “SEO or GEO,” but how the two intertwine. Classic SEO ensures technical cleanliness and findability in search engines, while GEO complements it with a presence in generative responses. Those who only consider one of these risk visibility gaps. The decisive factor is therefore a hybrid approach.
The following quick check could give you some initial indications of how well your company is already positioned in the area of AI SEO.
If you would like to answer these questions for your company or strategically expand your visibility in the AI age, Uhura Digital will be happy to support you – from analysis and strategy to implementation. Just give us a call.
