AI Search Engines

AI search engines are revolutionising traditional internet search. Instead of displaying a list of results, they combine a classic web index with a language model and formulate a direct answer. This makes the search more dynamic, yet reliable and up-to-date.

AI search engines – the real story.

AI search engines have emerged alongside Google in recent years. Among the best-known are Perplexity and ChatGPT. Their approach differs significantly from traditional search systems.

Essentially, two levels are being combined:

A search index – usually Microsoft Bing’s – provides relevant websites.
A language model processes this content and formulates a coherent answer in natural language.

The result is a direct, dialogue-like response instead of a list of links. While AI search engines are similar to Google’s AI Overviews and AI Mode, they present the information within their own environment. The responses are based either on their own index or on Bing’s index, and users can ask follow-up questions.

This presents new challenges for evaluating and analysing this content. The results are highly dynamic: the index changes continuously, and the AI engine interprets the same content slightly differently with each query. Visibility in these systems therefore cannot be described by fixed rankings, but only by whether and in what context a domain appears in the responses.

What changes now?

AI-powered search engines present SEOs with new challenges. Visibility is no longer solely determined by fixed rankings, but rather by whether and how a domain or brand is mentioned in the search results. Traditional SERP positions are losing their significance.

Furthermore, there is high volatility: results can change daily because both the underlying index and the language model are variable. Even self-generated content doesn’t always appear as a cited source, and source information can be incomplete or incorrect. For SEOs, this means that familiar success metrics are reaching their limits, and new approaches are needed.

Publishers also face risks . Content can be used by AI without reliably generating return traffic. At the same time, there is an increased risk that faulty or outdated information will be spread via AI systems, thus influencing brand perception.

In the long run, one thing is clear: AI-powered answers will become established in search behavior. For SEOs, this means addressing these changes early on in order to seize opportunities and keep an eye on risks.

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Analyse visibility in AI search engines with SISTRIX

AI visibility in focus

AI search engines don’t provide fixed rankings, but rather dynamic results. This makes it all the more important to know if and how your brand appears in them. Projects can help you regularly monitor this visibility and keep track of changes.

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Making success measurable

Only by keeping track of developments can you recognise actual progress. The timeline of your prompts shows you how visibility shifts, which measures are effective, and when competitors gain strength.

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Comparison with competitors

Only a direct comparison reveals how strong your brand truly is in the market. You can see which competitors appear in AI-generated answers, which topics they are addressing, and where new opportunities arise for you.

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What SEO’s can do now

Those who want to remain visible in AI search engines should actively shape the transformation. Their brand must be positioned in such a way that language models can clearly recognise it. Clear facts, up-to-date data, and a well-structured organisation increase the likelihood of accurate responses. External signals, such as mentions in trusted sources, are equally important.

The technical foundations must also be sound. Content should be accessible to language models, relevant bots must not be blocked , and brands must be clearly identifiable as entities.

The foundation, however, remains classic SEO. AI search engines rely on a search index like Bing’s for their content. Those who rank well there are also mentioned more frequently in generative search results. On-page optimisation, off-page signals, and a sound content strategy retain their full value. In addition, monitoring is needed to show whether and in what context a brand appears in search results.

SEO for AI search engines is therefore not a replacement for what we know so far, but complementary. Those who combine both early on gain a clear advantage.

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