SEO agencies in 2026: From Google searches to AI-generated answers

The search engines we knew in 2024 are barely recognisable two years on. Google now serves AI-generated answers directly in search results, and users are less likely to click through to websites. For businesses that have invested heavily in traditional search engine visibility, this feels like an earthquake. The question is no longer just how to rank highly on Google, but how to become the source that AI models refer to when formulating their answers. An SEO agency in 2026 must therefore work in a completely different way than just a couple of years ago: the journey from Google searches to AI answers has been faster than most anticipated.

The SEO landscape in 2026: The shift from clicks to answers

The figures tell a clear story. According to SparkToro and Datos, over 60 per cent of Google searches in 2024 already had zero clicks. In 2026, the proportion is even higher, because AI Overviews now cover a wide range of search intent. Users get answers without leaving Google. This means that the traditional model, where you wrote content, ranked on page one and got traffic, has fundamentally changed.

For Norwegian businesses, this has concrete consequences. A local dentist who previously attracted patients through informative articles on teeth whitening now finds that Google itself summarises the answer. Traffic to the website falls, but the need for teeth whitening does not disappear. The challenge is to become visible within the AI answer itself, not just below it.

Generative Engine Optimisation (GEO) is taking over from traditional SEO

GEO is the term used to describe the work of making content visible within AI-generated answers, whether it be Google’s AI Overviews, ChatGPT, Perplexity or other models. The difference from classic SEO is significant. Traditional search engine optimisation was all about links, keywords and technical structure. GEO is about being recognised as a reliable source by large language models (LLMs).

In practical terms, this means your content must be structured so that AI models can easily extract facts, quotes and data points. Short, precise paragraphs with clear statements work better than long, vague texts. Source references and clear author information strengthen credibility. And your brand must be mentioned in enough reliable contexts for the models to ‘know’ who you are.

SGE and AI Overviews: How Google has changed user habits

Google’s Search Generative Experience (SGE), now known as AI Overviews, was rolled out globally throughout 2025. For Norwegian-language searches, this means that an ever-increasing proportion of information queries are answered directly in the search results. Users have adapted quickly. They scan the AI response and only click through if they need more in-depth information or wish to make a purchase.

This behavioural shift is similar to what happened when featured snippets were introduced, but on a much larger scale. Companies that understand this are adapting their content strategy. They are focusing less on ranking for broad information searches and more on owning the specific topics where AI models need expert sources. It is a shift from volume to precision.

The new role of an SEO agency

An SEO agency that still primarily delivers keyword analysis and link building is operating with an outdated model. That doesn’t mean these disciplines are irrelevant, but they are now just pieces of a larger jigsaw puzzle. The agency’s role has expanded to include AI strategy, data structuring and cross-platform branding.

Think of it as the difference between a general practitioner and a specialist. A traditional SEO agency was the general practitioner: a bit of everything, good enough for most people. In 2026, you’ll need a specialist who understands how language models select sources, how structured data influences AI responses, and how your brand can become the one the models trust.

From keyword specialists to data and AI strategists

The best SEO agencies today have staff who understand machine learning, not just marketing. They analyse how different LLMs weight sources, and they use this insight to shape content strategies. It’s not about ‘tricking’ the AI, but about making the business’s expertise available in formats the models understand.

At Mediabooster, we have witnessed this development first-hand through over 15 years of digital marketing. The transition from pure SEO to what we call AEO (Answer Engine Optimisation) requires a combination of technical understanding and strategic thinking. We work with everything from structured data and schema markup to content architecture designed to be cited by AI models. The point is that this isn’t something you set up once and forget about. It requires continuous fine-tuning based on how the models evolve.

Optimisation for LLM models and chatbots

ChatGPT, Gemini, Claude and Perplexity gather information from various sources and weight them differently. Becoming visible in these models requires an approach that goes beyond traditional Google ranking. Here are some specific steps that work:

• Publish content with clear, fact-based claims that are easy to cite
• Ensure your brand is mentioned in relevant industry publications and databases
• Use structured data consistently across your entire website
• Create a Wikipedia page or Wikidata entity for your business if one does not already exist
• Update content regularly, as LLMs favour fresh sources

These steps aren’t magic, but they give the models what they need to include you as a source. That’s 80 per cent of the job. The remaining 20 per cent is about monitoring the results and making ongoing adjustments.

E-E-A-T as the key competitive advantage

Google’s E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness) has evolved from being a guideline to becoming the very foundation of visibility. When AI models choose which sources to cite, they place great weight on credibility. An anonymous blog post with no author information loses out to an article written by a named expert with documented experience.

Verification of human expertise in an AI-generated world

The paradox is clear: the more AI-generated content there is online, the more valuable content backed by verifiable human expertise becomes. Google and other platforms are investing heavily in distinguishing between generic AI text and content based on real-world experience.

For businesses, this means that employees’ expertise must be made visible. Author profiles with links to LinkedIn, professional publications and lectures send signals that bolster credibility. An accountant who writes about tax planning and can demonstrate 20 years’ experience will be preferred by AI models over a generic text with no author. It is about proving that a person with relevant knowledge is behind the content.

Building authority through entities and brand strength

Entities are Google’s way of understanding the world. An entity can be a person, a business, a concept or a place. When Google and other models recognise your business as an entity with distinct characteristics and relationships, the likelihood of you being referenced in AI responses increases.

In practical terms, this means you should actively work on your digital presence across platforms. Google Business Profile, Brønnøysundregistrene, industry directories, Wikipedia, Wikidata and social media should all tell a consistent story about who you are and what you do. Inconsistencies between these sources create uncertainty for the models, and uncertainty means they will choose a different source.

Content production in 2026: Quality over volume

The strategy of publishing hundreds of mediocre blog posts to cover as many keywords as possible is dead. AI models don’t need ten articles saying the same thing in slightly different words. They need one thorough, up-to-date and authoritative source. Companies that continue to mass-produce thin content are throwing resources out the window.

That doesn’t mean content production is any less important. On the contrary: it’s more important than ever, but quality standards have risen dramatically. A good post that covers a topic thoroughly, with original data or insights, is worth more than 50 generic texts.

Multimodal content for visual and voice-based searches

Text is no longer the only channel. Video, images, podcasts and interactive elements all play a role in how AI models understand and present information. Google Lens searches have increased by over 30 per cent annually, and voice searches via smart speakers and mobile assistants account for an ever-increasing share of total searches.

For Norwegian businesses, this means that content strategy must be multimodal. An article on cabin maintenance should include an accompanying video, infographics and perhaps a downloadable checklist. These formats provide AI models with multiple entry points to your content, and they make you visible in search types that plain text does not cover.

Real-time personalisation and user intent

AI models are getting better and better at understanding context and intent. A search for ‘best restaurant’ yields different results depending on where you are, what time it is, and what you’ve searched for previously. Content that takes different user intents into account performs better than general texts.

In practical terms, this means you should structure your content around clear user scenarios. Instead of one long article on ‘insurance’, create separate, in-depth resources for ‘car insurance for young drivers in Oslo’, ‘home contents insurance for students’ and ‘business insurance for entrepreneurs’. Specificity beats generality, because AI models can match specific content with specific queries.

Technical SEO in an era of headless CMS and AI crawling

The technical side of SEO has become more complex, not less so. Headless CMS solutions such as Sanity, Contentful and Strapi offer great flexibility, but they require extra attention regarding rendering and crawlability. If your content is rendered exclusively on the client side without server-side rendering, you risk neither Google nor AI models being able to index it properly.

AI crawlers from OpenAI, Anthropic and others operate differently from Googlebot. They have their own user agents and their own rules for how they fetch content. Many websites block these crawlers without realising it, through robots.txt rules written before AI crawling became relevant. A technical review of how your website handles these crawlers should be high on your priority list.

Structured data (schema markup) has gone from being ‘nice to have’ to being critical. FAQ schema, HowTo schema, Organisation schema and Article schema provide AI models with the context they need to understand and cite your content. Through over 450 delivered web and marketing solutions, Mediabooster has seen time and again that websites with thoroughly implemented schema markup achieve significantly better visibility, both in traditional search results and in AI responses.

Speed and Core Web Vitals remain important signals, but they alone do not determine anything. It is the combination of technical robustness, structured data and quality content that delivers results.

Measuring success as traditional clicks disappear

Here’s the elephant in the room: if users get answers directly in the search results, how do you measure whether your SEO efforts are working? Organic traffic as the sole KPI is outdated. That doesn’t mean traffic is irrelevant, but it paints an incomplete picture.

New KPIs: Visibility in AI answers and brand mentions

The most forward-thinking businesses now measure visibility in AI responses as a separate KPI. Tools such as Otterly.ai, Profound and Peec AI allow you to track how often your brand is mentioned in responses from ChatGPT, Perplexity and Google AI Overviews. This provides a whole new data set for assessing the impact of your content strategy.

Brand mentions across the web are another key indicator. How often is your business mentioned in articles, forums, podcasts and social media? These mentions directly influence how AI models perceive your authority. Traditional PR metrics and media monitoring thus take on new relevance in an SEO context.

Share of Voice in AI responses is perhaps the most interesting new KPI. It measures the proportion of relevant AI responses that include your brand compared to your competitors. This provides a strategic picture that raw traffic data could never provide.

Attraction and conversion in a zero-click reality

When fewer users click through to your website, you need to think differently about conversion. Brand recognition becomes more important because the user might see your name in an AI response, remember it, and search for you directly later. This indirect conversion path is difficult to track with traditional analytics tools, but it is real.

Your strategy should include more direct touchpoints. Newsletters, social media, webinars and physical events build relationships that aren’t dependent on Google clicks. SEO work then becomes about ensuring your brand is visible and credible in those moments when potential customers ask their AI assistants questions.

Conversion optimisation on the website itself is also becoming more important. When the incoming traffic is more qualified (because users have actively chosen to click past the AI response), the conversion rate should actually increase. Ensure your landing pages live up to expectations.

Future-proofing your digital strategy

It is tempting to wait and see how things develop, but businesses that wait are losing ground to competitors who are acting now. The shift from traditional search results to AI answers is not a trend that is likely to reverse. It is a structural change in how people find information.

The most important steps you can take right now are to invest in proven expertise, structure your content for AI models, and start measuring visibility in AI answers as a primary KPI. None of these things require you to abandon what you’re already doing. They require you to build on your existing work with new perspectives.

At Mediabooster, we work as part of your team to translate these strategies into measurable results. With offices in Oslo and Lillestrøm, and experience from over 450 projects across the Nordic region, we help businesses navigate the transition from traditional SEO to AI visibility. Would you like to discuss how your business can adapt? Book a meeting with us for a no-obligation chat about the way forward.