AI SEO
AI SEO – also called AI SEO or AI search engine optimization – describes search engine optimization under the conditions of artificial intelligence. The term has two sides: On the one hand, it is about SEO for AI search results – that is, ensuring that content is included in AI Overviews, in Google AI Mode or in AI search engines such as ChatGPT and Perplexity. On the other hand, AI SEO stands for the use of AI tools in the SEO process itself, for example for keyword analyses, content planning or technical audits. Both sides are connected: Those who work with AI search understand better how AI systems read content and can align their optimization accordingly.
How artificial intelligence is changing search
AI in Google Search is nothing new. As early as 2015, systems such as RankBrain, later BERT and MUM, have been incorporated into the ranking. They help Google understand the meaning of a search query instead of just looking for matching words. However, the change only became visible with the AI Overviews: Above many search results today there is an AI-generated summary with source references; in AI Mode, a chat dialog completely replaces the classic list of results. At the same time, standalone AI search engines are growing, which manage without the Google index or use it only as a data source.
For website operators, this means two things. First, for informational search queries, the share of clicks decreases because the answer is already on the search results page. Second, the competition is shifting: It is no longer just position one that counts, but whether your own page appears as a source in the AI answer. AI Search SEO must therefore achieve both – securing classic rankings and creating the prerequisites for being mentioned in AI search results.
SEO for AI search engines: What changes in optimization
The basics of search engine optimization remain in place, because AI search engines access the same indexes as traditional search engines. A page that is not crawlable, is slow or has thin content will also not be considered by AI systems. Building on this, AI search engine optimization shifts its focus to five areas:
Search intent instead of keyword
AI systems interpret queries semantically. Content should fully answer the question behind the search term, not just contain the term.
Passage quality
Language models select individual paragraphs, not entire pages. Clear subheadings, compact definitions and directly formulated answers increase the chance of being quoted.
Entities and E-E-A-T
AI systems evaluate whether a source is considered an authority on a topic. Consistent information about brand, authors and products, evidence of experience and expertise, and mentions on third-party sites strengthen this signal.
Structured data
Schema.org markups for organization, products, FAQs or authors make relationships machine-readable and make it easier for AI systems to classify them.
Access for AI crawlers
Bots such as Google-Extended, GPTBot or PerplexityBot must be deliberately allowed or excluded in robots.txt. Content should be present in the delivered HTML and not only loaded afterwards via JavaScript.
Optimization specifically for generative answers is summarized under the term Generative Engine Optimization (GEO); AI SEO is the broader framework in which GEO is one discipline.
AI as a tool in search engine optimization
The second side of AI SEO optimization concerns the way of working. AI-supported tools now take over tasks that previously required a lot of manual work: keyword lists are automatically clustered according to search intent, competitor content is analyzed, content briefings are created and meta data is pre-formulated in large quantities. In technical audits, AI models help to evaluate crawl data and log files and to identify patterns.
When creating text, a sense of proportion is required. Google evaluates content based on quality and usefulness, not on its origin – AI-generated texts are therefore not fundamentally a problem. However, mass-produced, interchangeable content without its own experience or expertise is classified as spam and can devalue the entire domain. A process has proven successful in which AI handles research, structuring and the first draft, while experts review, supplement and take responsibility.
AI SEO in e-commerce
For online shops, AI SEO is particularly relevant because purchase advice increasingly takes place in AI answers. Users ask for the right product for their use case and receive recommendations before they open a shop. Complete product data, clear attributes, a well-maintained Merchant Center feed and category texts that answer real questions form the basis for this. At the same time, AI tools make it possible to efficiently provide thousands of product and category pages with individual content – provided that quality assurance and expert review remain part of the process.