6 GEO Myths Debunked
No strategy consulting at F7 currently gets by without this question: Are we GEO-ready? Compared with SEO, Generative Engine Optimization (GEO) is still a young field, which means there is a considerable amount of half-knowledge circulating in marketing-driven LinkedIn posts, whitepapers, and the like.
At the same time, there are repeated claims that websites are becoming obsolete because ChatGPT and other AI systems provide answers directly. Traffic figures paint a more nuanced picture, however: declining traffic primarily affects sites lacking substantive content, while specific, authoritative content is increasingly becoming a source for AI-generated answers. Your own website is therefore the central tool for AI visibility.
Myth 1: SEO is dead
Google explicitly states that its AI features do not represent a separate discipline, but rely on the same ranking and quality systems as traditional search results. This cannot be applied one-to-one to all AI systems. But the core principle remains valid across the board: without a solid technical structure and substantive content, no GEO strategy in the world will get you very far.
Reality: SEO is not dead – quite the opposite. GEO builds on SEO.
Myth 2: Content chunking makes text AI-friendly
Content does not need to be broken down into AI-friendly chunks. A clear structure has always been useful – primarily for the reader, not for the AI. There is no need to break texts apart or artificially simplify them.
Realität: AI search systems do, however, evaluate individual passages rather than entire pages. A paragraph that is understandable without additional context is therefore more likely to be cited. Structure serves both purposes: it makes content easier for people to read and easier for retrieval systems to find. That is simply good writing – not an AI trick.
Myth 3: Scaling content with AI is a bad idea
Google explicitly states that whether content is AI-generated does not affect how it is evaluated. What matters is whether the content is helpful, up to date and factually sound – and whether it offers a genuine, personal perspective. If you produce AI-generated content at scale without anyone checking its substance and accuracy, you may get plenty of volume, but little value when it comes to being cited.
Reality: It’s not about quantity. What matters is genuine expertise and reputation.
BTW: Writing content with AI can be surprisingly annoying – and take way too much time. Greetings from the author. ¯\_(ツ)_/¯
Myth 4: AI understands all languages
“Our content is in German, so AI will figure out the translation” – or so you might think. An analysis by Peec.ai [1] of more than 20 million ChatGPT queries shows that 43% of the underlying searches, or “query fan-outs,” are conducted in English – even when the original question is asked in German. In one example cited by Peec.ai, ChatGPT was asked to name German software companies but did not list a single company actually based in Germany.
Reality: AI systems often rely on English-language sources. Publishing content in English can therefore increase AI visibility – even when your target market is German-speaking.
Myth 5: We need an LLMS.txt
The LLMS.txt file is intended to provide AI systems with information about a website’s structure and content, similar to what robots.txt does for search engine crawlers. However, there is no established standard for it. There is also no evidence that leading AI services actually use the file – quite the opposite: Google says it does not use LLMS.txt, and our own server statistics show no requests for it either.
Reality: LLMS.txt doesn’t hurt – but so far, there is no measurable benefit either. We have one anyway. :)
Myth 6: MCP is the “game changer” for GEO
“MCP” is a topic that comes up in many AI consulting engagements, usually in the same breath as GEO. MCP, or the “Model Context Protocol,” defines how an AI agent can access data and functionality – for example, checking availability, calculating product configurations, or completing bookings on a website. But when it comes to simply being visible in an AI-generated answer, MCP has no direct role to play.
Reality: MCP only matters if your platform offers real functionality – configuration, price calculations, bookings, and the like. Otherwise, it’s money spent in the wrong place.
Myth 7: An AI tool for every problem
By now, there is at least one AI plugin for almost every major platform, promising to solve just about everything. A common example is automated SEO and accessibility optimization. External tools claim to make a website accessible with a single click, automatically generate metadata for every image, or write meta descriptions. Much of this can indeed be (partly) automated – but creating genuinely accessible websites still requires expert review of the AI-generated results.
Reality: AI tools can help, but they cannot replace structural and content-related solutions.
Conclusion
If you’ve been counting along, you may have noticed: there were seven myths, not six – and there are plenty more where those came from. What they all have in common is that they promise a shortcut: a tool, a protocol and, ideally, a project with a fixed end date and budget.
What actually matters is far less spectacular:
- A solid technical CMS platform with a well-designed architecture provides the foundation.
- The building on top of that is the content: up to date, based on a genuine, personal perspective and backed by real expertise – not generic or interchangeable. And that requires a long-term content strategy and governance framework.
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