SEO in transition: How artificial intelligence is impacting the industry

Search engine optimisation (SEO) is facing a profound change. With the increasing use of AI-supported systems such as chatbots, voice assistants and AI operators, the way in which people search for and consume information is changing. This development poses new challenges for the SEO industry - especially when it comes to measuring success.

 

Changing search behaviour: Away from classic search queries

Searching online used to be a relatively simple process: you entered a few keywords into Google, received a list of websites and clicked through to find the information you were looking for. But this search behaviour has changed dramatically. Today, users expect precise and direct answers without having to navigate through various websites for a long time.

Modern AI models such as ChatGPT or Google's Search Generative Experience (SGE) enable users to ask their questions in natural language as if they were talking to a real person. Instead of a classic keyword search such as ‘best running shoes 2024’, they now formulate more detailed and contextualised queries such as ‘Which running shoes are best for long distances?’. The AI then provides an answer directly, often without users having to visit a website.

This represents a fundamental change for the SEO industry. Pure keyword optimisation is no longer enough. Instead, it is important to provide content that search engines and AI systems categorise as particularly helpful and relevant. High-quality and well-structured content that answers specific questions in an understandable way has the best chance of being taken into account in AI-generated answers.

At the same time, semantic searches are becoming increasingly important. Search engines not only analyse individual terms, but also try to understand the actual intention behind a query. Companies must therefore not only provide their content with relevant keywords, but also present it in a broader context that corresponds to the user's questions.

 

Quality over quantity: the content focus is changing

As AI operators are designed to deliver the best answers, the quality of content is becoming more crucial than ever before. Search engines no longer just prefer well-optimised pages, but above all those that offer real added value. Factors such as expertise, relevance and comprehensibility are essential if they are to be taken into account by AI-supported systems.

Whereas in the past it was often about producing as much content as possible and optimising it with keywords, the focus is now shifting to the actual user intention. Companies need to ask themselves: What questions does my target group have? What problems can my content solve?

The following aspects are becoming increasingly important:

• In-depth and well-researched content: Superficial texts that only target keywords have little chance of being used as a relevant source by AI systems. Instead, content should be well-founded, informative and precise.

• Simple and clear language: AI systems not only evaluate how comprehensively a topic is covered, but also whether the content is formulated in an understandable way. Complex technical terms without explanation or unnecessarily convoluted sentences can have a negative impact on visibility.

• Structured and easily navigable content: Outlines, headings, lists and paragraphs not only make it easier for readers to understand, but also help search engines to better categorise the content.

• Multimedia formats: In addition to text-only content, images, videos, infographics and interactive content are becoming increasingly important. AI systems can increasingly analyse these formats and incorporate them into their evaluations.

• E-E-A-T principle: Google is increasingly emphasising the concept of experience, expertise, authoritativeness and trustworthiness (E-E-A-T). Especially for industries such as finance, health or law, it is important that content has been created or reviewed by real experts.

In addition, websites should increasingly rely on structured data, as this makes it easier for search engines and AI systems to better understand content and integrate it into responses. Schema.org markup can play an important role here.

 

Challenges in measuring success

A key problem for the SEO industry is the change in performance measurement. Traditional SEO KPIs such as page views, click-through rates and dwell time are becoming less meaningful as users are increasingly finding their information directly in AI-generated answers - without visiting a website.

This results in three main challenges:

• Increase in ‘zero-click searches’: More and more search queries are being answered directly in the search results or by AI-supported systems without users clicking on an external website. This means that organic traffic to many websites is declining, even if they provide relevant information.

• Lack of visibility data: Companies are often unable to track whether their content is being used by an AI. Current analytics tools such as Google Search Console or Google Analytics offer no insight into whether an AI has pulled a response from a particular source. This makes content optimisation more difficult.

• New metrics are missing: As traditional SEO metrics such as page views or bounce rates become less important, there is a lack of alternatives to evaluate the success of content. Companies need to develop new approaches to understand how well their content is perceived and utilised by users.

 

New measurement methods for SEO success

As conventional measurement methods are reaching their limits, the SEO industry needs new approaches to measuring success. Possible strategies could be:

• Tracking tools for AI interactions: In the future, special APIs or dashboards could emerge that show whether a website has been used as a source for AI-generated responses.

• Brand awareness as a KPI: The focus could shift more towards brand awareness. If users are aware of the brand and remember the source from which they received a valuable answer, the influence of the content will be strengthened in the long term.

• Direct user loyalty: Regardless of search engines, companies need to find ways to retain their target group in the long term - for example through newsletters, exclusive communities or interactive content.

 

Conclusion: SEO remains relevant, but is changing

SEO will not disappear, but will have to adapt. The importance of high-quality content, semantic search optimisation and structured data will continue to grow. At the same time, new measurement methods are needed to determine the success of SEO in a world in which search engines are no longer the only way to obtain information.

Companies and marketers should prepare for these changes early on and adapt their strategies. Only those who are prepared to break new ground will remain successful in the AI-driven future.