Customer Impact

SEO & GEO

What is a generative search engine?

Copy for AI

A generative search engine is a search system that answers your question with a written text, generated by an AI model, instead of a list of links you have to choose from yourself. You ask a full question, and you immediately get a summarised answer back. In this article you will learn exactly what a generative search engine is, how it differs from classic search, how it works under the hood, which ones you already use today, and what that means for your business’s visibility.

What exactly is a generative search engine?

A generative search engine combines the search for information with a language model that turns that information into a readable answer. The word “generative” refers to generative AI: technology that creates new text based on what it has learned and on what it finds online at that moment. Where a classic search engine shows you ten blue links, a generative search engine writes an answer in full sentences, often with a few sources alongside.

The difference lies in what you get back. With Google you traditionally got a referral: here are the pages, choose for yourself. With a generative search engine you get a conclusion: this is the answer, and these are the sources it is based on. To the user it feels like a conversation with a well-informed colleague rather than a visit to a library catalogue.

How does a generative search engine differ from Google?

The core difference is that a generative search engine gives an answer, while classic search gives a choice. With the blue links, you decide which page is relevant and click through to the source. With a generative search engine, the model largely makes that choice for you and summarises the information.

That has a few concrete consequences:

  • You phrase things differently. In Google you typed loose keywords like “compare accounting software”. To a generative search engine you ask a full question, such as “which accounting software suits a small B2B company in Belgium”.
  • You click less. Because the answer is already there, many users no longer move on to a website. The mention in the answer becomes more important than the click.
  • Sources are selected, not listed. The model picks a handful of sources to draw on and possibly cite, instead of showing a ranking.

Important: these two worlds exist side by side. Google itself has become a generative search engine by showing AI Overviews above the regular results, while the blue links remain below them. The boundary between “search engine” and “generative search engine” is therefore blurring. If you want the full difference between the two disciplines, read our explanation of GEO vs SEO.

How does a generative search engine work?

A generative search engine usually works in three steps: it understands your question, it pulls in current information, and it writes an answer with it. That middle step is crucial and is called retrieval: the model first looks up relevant sources on the web or in an index, and uses them to support its answer.

In practice it looks like this. You ask a question. The system turns it into one or more search queries and fetches a set of pages. Next, the language model reads those pages, filters what is relevant, and formulates an answer in natural language. Finally, it often adds a few source references, so you can check where the information comes from.

Pulling in current sources prevents the model from drawing purely on its memory, because that memory is frozen at the moment of training and can be outdated. The process by which an AI anchors its answer in verifiable, current sources is called grounding. How exactly that determines whether your information is picked up, you can read in grounding: how AI decides what is true. For your visibility this is the crux: if your page is not retrieved and understood during that retrieval step, you simply do not end up in the answer.

UNDER THE HOOD How a generative search engine builds its answer Step 1 Understands your question turns it into search queries Step 2 Fetches sources retrieval of pages Step 3 Writes the answer with source citation If you don't make it into the retrieval step, you're not in the answer.
A generative search engine understands your question, pulls in current sources and writes an answer with them.

Which generative search engines are there?

The best-known generative search engines are ChatGPT, Google Gemini, Perplexity and the AI Overviews within Google Search. They do essentially the same thing, but make different choices in how they show and weigh sources.

  • ChatGPT from OpenAI can search the web directly and support answers with sources. It has grown into one of the most-used entry points for questions people used to ask Google.
  • Google Gemini and the AI Overviews in Google Search bring generative answers to the world’s largest search platform. Google also has a more extensive AI Mode in which search becomes fully conversational.
  • Perplexity positions itself as the answer engine that leans heavily on visible source citations, with multiple citations per answer.
  • Microsoft Copilot brings generative answers to Bing and the Microsoft environment.

Each of these systems picks its sources in its own way, so being visible in one does not automatically mean being visible in another. We wrote separate guides on getting found in ChatGPT and on getting found in Google AI Overviews. Keep in mind that this landscape moves fast: names, features and market shares change often, so check the current situation before you base decisions on it.

Why is a generative search engine important for your business?

The importance for your business is simple: a growing share of your future customers begins their search with a generative search engine, and if it does not name your brand, you do not exist in that answer. The buyer then draws up their first shortlist without you.

This mainly affects the orientation and comparison phase. Someone who asks “which approach suits a B2B company” or “what is the difference between option X and Y” gets a summarised answer and often no longer looks at ten links. If you are named in that answer, you are early in the buyer’s line of thinking, even before they start comparing names. If you are not named, your competitor who does appear gets a free assist.

Staying honest is part of it here: not every search shifts to AI, and for local or strongly purchase-driven searches, classic search remains dominant for now. The sensible response is therefore not to panic, but to start being present in both places now, while many competitors are still waiting. For B2B companies, we worked this out further in our approach to getting found in ChatGPT.

How do you become visible in a generative search engine?

You become visible through content that answers a real question directly and clearly, structured in a way a model can easily read and cite. This field is called generative engine optimization, and the full approach is in our complete guide to GEO. The basic principles are recognisable:

  • Answer the question at the top. Put the answer in the first sentence of a section, not only after three introductory paragraphs. Models pick up that direct phrasing faster.
  • Structure for readability. Use headings that are real questions, short paragraphs and lists. What a human scans easily, a model can extract easily.
  • Build authority. A brand that is mentioned in multiple trustworthy places is chosen as a source more often. Mentions and consistency weigh more heavily than tricks.
  • Be concrete and factual. Definitions, clear figures in context and unambiguous wording give a model something to hold on to when citing you.

The common thread: don’t write for the machine, but for the reader, and then make it as easy as possible for the machine to pick up your clear answer. This is not a separate set of tricks, it is simply good, honest content that is built just a bit more sharply.

The short summary

A generative search engine gives a written AI answer instead of a list of links, based on sources the system retrieves and weighs itself. ChatGPT, Gemini, Perplexity and Google AI Overviews are the best-known examples. For your business, the goal shifts from winning a click to being named in the answer, and you win that with clear, well-structured content and a brand that shows up in multiple places. Visibility is not a goal in itself: it must ultimately lead to leads and revenue.

Want to know whether your business already shows up in these answers today, and where your opportunities lie? Book your free intake and you will hear within 24 hours where you stand.

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