In 2022, the answer to “where do I start when researching a purchase?” was almost always Google. In 2026, for a growing share of commercial queries, the answer is ChatGPT, Perplexity, Gemini or Claude.
This shift is not hypothetical. It’s measurable, it’s accelerating, and for most brands it is entirely invisible — because the visitors who start on AI platforms and never reach your website don’t appear in your analytics.
What's Actually Changing
When someone asks ChatGPT “what’s the best AI consulting firm in Germany for a mid-sized manufacturing company?”, one of three things happens:
First: a set of firms are named, described and compared, and the user forms a strong initial preference before visiting any website. Second: no specific firms are named but the answer describes what to look for, shaping the evaluation criteria before the buyer talks to anyone. Third: the AI defers to a web search and surfaces results — at which point GEO and traditional SEO overlap.
In each scenario, the brand that isn’t mentioned, or isn’t described accurately, or isn’t associated with the right expertise, loses influence at the moment when preferences form. And that influence is very difficult to recover downstream — because the buyer arrives at your website with prior beliefs already shaped by an AI system you had no input into.
Why Traditional SEO Doesn't Solve This
SEO optimises for search engine crawlers and ranking algorithms. It works by increasing the probability that your page appears in a results list and earns a click. GEO is fundamentally different: you’re optimising for the training data, retrieval systems and citation patterns of large language models.
The signals that make a page rank well on Google — backlinks, keyword density, technical performance — are not the same signals that make a source credible and citable to an AI system. AI platforms weight depth, factual density, structural clarity, entity recognition and corroboration across sources. A thin page with strong backlinks can rank; it won’t earn citations.
This means your existing SEO investment does not automatically translate to AI visibility. You need a different strategy, different content, and a different measurement approach.
What GEO Actually Involves
Generative Engine Optimisation has four main workstreams, and the specifics matter enormously — I won’t detail our exact methodology here, but the categories are consistent across serious practitioners.
Content architecture: Creating content assets that are deep, structured, factually dense and designed to be cited. FAQ hubs, comprehensive guides, comparison pages and definitional content — built around the commercial queries your buyers are actually asking AI platforms.
Content architecture: Entity optimisation: Establishing your brand, key people, core expertise and service categories as recognised entities in the knowledge graphs and training data that AI systems draw from. This is technical and often overlooked.
Content architecture: Citation surface expansion: Building presence across the sources AI platforms draw from — specialist directories, third-party publications, structured data markup, Wikipedia and equivalent — to create a consistent signal of authority across multiple independent sources.
Content architecture: Query mapping and tracking: Identifying the specific queries your buyers use with AI platforms, measuring your current visibility for those queries, and tracking improvement. This requires different tooling from traditional SEO analytics.
The First-Mover Window
The reason to act now rather than later is that GEO authority compounds. Brands that establish credible, deep, well-cited content in AI systems now will be harder to displace than brands that start in 2027 — because AI citation patterns, once established, are self-reinforcing. A source that’s cited frequently becomes more likely to be cited again.
Across the sectors we work in, the picture is consistent: the vast majority of businesses have invested nothing in GEO. For most categories in most markets, the field is genuinely open.
That window will close. It closes gradually, then quickly — as it always does when a new channel opens up. The brands that move now will be the hardest to compete with later.