AI Search
AI search refers to information retrieval via systems with artificial intelligence that formulate a finished answer to a question in natural language, instead of just showing a list of blue links. Tools like ChatGPT, Perplexity, Google AI Overviews, or Gemini read many sources, summarize them, and often name individual brands or websites directly in the answer.
Why AI search matters
More and more people no longer type their question into Google, but ask an AI assistant directly. The answer comes as fully worded text, often with just a handful of named sources. For you as a company this means: if your brand doesn't appear in this answer, you simply don't exist for that user, no matter how well you rank in classic search results. AI search shifts the competition from "first place in a long list" to "named or not named." This makes visibility both scarcer and more valuable at the same time. Whoever is understood, recommended, and prepared in a citable way gains reach that was previously spread across ten search result positions.
How AI search works
Behind AI search there is usually a large language model, that is, a program that has learned from vast amounts of text to understand and generate language. Many systems additionally use a retrieval step: they first search current web pages or a knowledge database and give the found text fragments to the model as context. The model formulates an answer from this and sometimes links the sources. What is decisive is that these systems order content by meaning, not just by keywords. Clearly structured pages with unambiguous statements, a clean heading hierarchy, and provable facts are captured more easily, attributed correctly, and adopted into answers more readily than vague advertising copy without concrete substance.
Common mistakes
The biggest mistake is to treat AI search like classic SEO and to focus only on keywords and rankings. AI systems reward clarity, not keyword density. Another mistake: hiding important facts like opening hours, prices, location, or unique selling points only in images or PDFs, where models read them poorly. Blocking AI crawlers in robots.txt also costs visibility, often unintentionally. It's equally risky to rely on a single phrasing: users ask in very different words. Whoever delivers only marketing platitudes instead of concrete, verifiable answers is rarely cited. And whoever never measures whether and how they appear in AI answers is steering blind.
Example
Imagine someone is planning a move and asks an AI assistant: "Which moving company in Leipzig is reliable and offers storage?" Instead of ten links, the AI delivers three specific firms with a short reason. One provider appears because its website clearly states that it offers storage, reviews are visible, and the services are stated as clean text. A competitor with an identical offering is missing because these facts are only contained in a PDF and a photo. The user calls the named firm, and the other never learns anything about the lost order.
Common questions
Is AI search the same as Google?
No. Classic search shows a list of links from which you choose yourself. AI search formulates a finished answer in natural language and often names only a few sources directly. Both exist in parallel, but AI search decides more strongly in advance who becomes visible at all.
Do I have to throw away my SEO for AI search?
No. A good technical foundation, clean structure, and strong content help both worlds. But you supplement SEO with clear, citable statements, verifiable facts, and machine-readable data, so that AI systems can understand your content and adopt it into answers.