In our article Content for the AI Era, we have already noted that traditional search is undergoing a radical transformation. Today, most users no longer formulate search queries via classic search engines – instead, they engage in conversations with AI systems such as Google Gemini, ChatGPT or Perplexity. These systems don't respond with search results, but select the source they trust most and that provides the clearest answer.
As a result, website visibility shifts away from ranking positions and clicks toward a new question: Does my company appear with trustworthy mentions in AI overviews and LLMs?
The New Conversion: Mentions vs. Clicks
At Digital Bash, Stefan Übelhör, Expert Content Consultant at diva-e Conclusion, took a deeper dive into the topic and answered the following question:
Why does content no longer work through keywords, but through context, clarity and machine readability?
Anyone who wants to be found must not only deliver relevant content, but also structure it so that both humans and AI can understand it equally well. At the same time, the importance of technical foundations, clear entities and clean structures increases so AI crawlers can correctly process content.
The new discipline is called GAIO (sometimes GEO) – Generative AI Optimization. It unites content, technology, UX and data into a shared mission: to structure content so it qualifies to appear in AI-generated answers.
What else is technically and strategically necessary to implement GAIO optimally and anchor it sustainably in the company?
Technical Requirements: AI Readability as the Basis for GAIO
For content to be mentioned in AI answers, it must not only be compelling but also technically structured without errors. Before an AI system can cite a source, it must be able to find, crawl and interpret it effortlessly. This is often where it is decided whether a company is even participating in the race for AI visibility.
One of the most important fundamentals is clean HTML and heading structure. H1, H2 and H3 are not design elements but orientation markers — for humans and machines alike. When headings are chosen purely for visual reasons or used multiple times, the semantic structure of a page breaks down. AI systems can no longer clearly identify what the page is actually about.
Even more important is the clear definition of entities. Entities are “things” (e.g., products, brands, people) and provide context. Attributes such as product, brand, person or event make a page machine-readable. This way, an AI crawler not only sees that a name appears on the page, but understands whether it refers to a brand, a product, an author or a company – and can integrate this knowledge into its network.
Technical requirements are also essential because AI crawlers often can’t get through even if content is good. Firewalls, bot protection mechanisms or improperly configured systems can block modern AI bots. Targeted whitelisting of relevant AI crawlers and checking log files help detect misconfigurations early.
GAIO therefore doesn’t start in the text editor – it starts with your website’s foundation. Only when content is technically clean, structured and machine-readable can it become visible in AI results.
EEAT: Why This Google Criterion Becomes Crucial in the AI Era
Equally important is the role of EEAT – Google’s quality model that stands for Experience, Expertise, Authoritativeness and Trustworthiness.
Especially in the context of GAIO, this framework becomes significantly more important because AI systems favor sources that are credible and authentically built.
The basis for E-E-A-T includes clear author profiles, real hands-on experience, verifiable statements and transparent sources. Brands that demonstrate what they can do — for example through customer references, real photos on their website or expert contributions and engagement on social networks and forums — are more often recognized as trustworthy references. This not only increases the likelihood of appearing in AI overviews but also makes your brand generally more trustworthy to users.
Content Structure: Entities and W-Questions
Beyond the technical foundation, content structure is crucial: AI systems evaluate not only whether information exists, but also how clear, contextual and complete it is. Good content no longer works via keywords but through precisely defined entities, clear W-questions and a comprehensible contextual framework.
Essentially, this means: every page must clarify who is doing something, what is meant, why it matters and in what context the information belongs. Such a journalistic structure provides the context AI systems need to correctly classify content and use it in their answers.
Helpful here is the so-called contextual fan-out. It expands a core topic with use cases, problem-solving approaches, reasons, practical examples and additional perspectives. This creates content that AI systems can use to answer different user intentions — without having to crawl hundreds of individual pages.
Instead of keywords and search volume, AI search is more about semantic completeness. AI tools can support research: identifying entities, structuring topic clusters or semantic keywording.
Collaboration & Processes: No AI Visibility Without Teamwork
One insight from the talk became particularly clear: in large companies, GAIO is not a discipline for lone wolves. It works only when content, SEO, tech, UX and data teams collaborate. Content quality, technical foundations, user experience and data are directly intertwined.
What does this mean in practice? Regular coordination, joint planning of pages and templates, early involvement of content and tech and an awareness that visibility and relevance arise only when all disciplines pull in the same direction.
AI-Ready Content Audit: Where You Stand – and What Your Content Needs
For companies that want to know how well their existing content already performs for AI systems, we offer our AI-Ready Content Analysis. Our experts assess how technically accessible, structurally understandable and qualitatively trustworthy your content is – exactly the building blocks that determine whether AI systems consider a page in their answers. Alongside the status quo analysis, we provide concrete recommendations for optimizing content for the AI era.
Conclusion: GAIO Is a Collaboration – Not a Buzzword
The AI era shifts not only search results but also the expectations for content. To remain visible, it’s no longer enough to simply serve keywords or meet technical SEO requirements. What matters is the interplay of clearly structured content, clean technology and entity-based thinking.
GAIO is not simply “new SEO” but a broader approach to building content that AI systems can easily find and understand — and that gives users exactly what they need. Those who take this path early and consistently not only achieve visibility in AI overviews but also lay the foundation for a credible, future-proof brand presence.
You’ll find a compact overview of GAIO fundamentals in our guide Content for the AI Era.
Learn More in the Digital Bash Recording
Curious? In the full Digital Bash talk, Stefan Übelhör offers deeper insights into the practical challenges and opportunities of GAIO — and demonstrates with concrete examples how your company can make its content fit for AI systems.
About Stephan Uebelhör
Stephan Uebelhör has been an Expert Content Consultant at diva-e Conclusion for over 11 years. His focus: content strategy, AI-driven content processes and internationalization. He supports brands in efficiently orchestrating content to create real experiences.
About Digital Bash
With more than 70 events per year, all free to join, Digital Bash is the largest web event series in the digital industry in the German-speaking region. Like our blog format edge, it targets everyone working in the digital sector: decision-makers and executives, software developers, marketing and e-commerce specialists.
