What is AI search? How AI-driven search works, and what it means for your business

For twenty years the search engine's contract with the user stayed the same: you ask a question, get ten blue links and do the work yourself (clicking, reading, comparing). That contract is being rewritten. More and more often, the answer is written for you by a language model that has fetched and weighed up sources in a second or so. For companies that depend on being found in search, it is the biggest change since the shift to mobile. This guide sets out what is actually happening.

What is AI search?

AI search is search in which an AI model interprets your question, fetches information from a search index and writes a coherent answer, rather than just showing a list of links. The term covers both AI features inside traditional search engines, such as Google's AI Overviews and AI Mode, and standalone AI assistants such as ChatGPT, Perplexity, Gemini and Microsoft Copilot.

One distinction needs making straight away, because the two terms are often mixed up. AI search is the phenomenon: what the user does and experiences when the answer is generated by an AI. AI SEO is the discipline: the work companies do to be visible in those answers and described correctly. This article is about the phenomenon: what AI search is, how it works and what it changes. The methods (how you adapt content, structure and technology) belong under AI SEO and related disciplines such as AEO and GEO.

How does AI search differ from traditional search?

The difference lies in what you get back. A traditional search engine ranks pages and leaves the rest to you. AI search goes a step further: it reads a selection of sources, weighs them up and delivers a synthesised answer – often with source references, sometimes without. The user no longer has to visit five websites to compare; the comparison has already been made. For anyone who wants to be visible in AI search, this means queries carry far more context, so keyword research for AI SEO calls for a much more inventive process.

A common misconception is that AI "reads the whole internet in real time". It does not. AI search services are built on search indexes (pre-collected copies of the web), and for each question they fetch a small number of existing sources to build the answer from. That has a direct practical consequence: if your information is not indexed and retrievable, it is not in the answer. The AI does not invent knowledge about your business; it reproduces what it finds.

How often do users see AI answers in Google? It depends on who is measuring. Different tools put the figure anywhere from around 16 to nearly 48 per cent of searches, depending on method and industry, with commercial sectors generally at the higher end. Whatever the exact figure, the direction is clear: a growing share of searches begin with an AI-generated answer.

How does AI search work technically? An overview

The core technology is called RAG (retrieval-augmented generation): relevant source documents are fetched from an index and handed to the language model while it writes the answer, so it does not have to rely on what it "remembers" from training. That is why AI answers can contain fresh information even though the model was trained long ago – and why the choice of sources determines what the answer says.

On top of that, several platforms use query fan-out: your question is broken down into several sub-questions that are searched in parallel, and the results are woven into one answer. In practice, one search can become ten. That is why AI answers often cover angles you did not explicitly ask about.

That mental model is enough to follow the rest of the article. If you want to dig deeper into how generative engines choose sources, we have broken down the mechanics step by step: see how generative engines choose sources and how AI answers are actually built.

The platforms: Google's AI Overviews and AI Mode, ChatGPT, Perplexity, Gemini and Copilot

Google: AI Overviews and AI Mode. AI Overviews is the AI summary above the regular search results, and it reached Sweden when Google rolled the feature out to more than 200 countries in May 2025. AI Mode is a fully conversational search experience in Google Search, and it launched in Sweden on 8 October 2025. Both are built on Google's regular index: content that ranks well in traditional SEO and answers concrete questions clearly has the best chance of being cited.

ChatGPT. The world's largest AI assistant, with 900 million weekly active users (OpenAI, February 2026). It searches the web when a question calls for it and favours established, well-structured sources. In Profound's analysis of 680 million citations (August 2024 to June 2025), Wikipedia accounted for nearly half of the citations among ChatGPT's ten most-used sources. But that is a snapshot, not a constant: which sources carry most weight shifts as the models and their search integrations are updated.

Perplexity. Built as an AI search engine from the ground up: every answer is drawn from the web and shows its sources openly. Perplexity has clearly leaned towards fresh content and online communities: in the same Profound analysis, Reddit accounted for almost half of the citations among Perplexity's ten most-used sources. That, too, is a snapshot from a single measurement period, not a rule to build on.

Gemini. Google's standalone AI assistant, closely tied to Google's index and services. Its strength is that it combines search retrieval with Google's ecosystem, and it broadly shares Google's preference for authoritative, well-structured sources.

Microsoft Copilot. Microsoft's assistant, powered by the Bing index and built into Windows, Edge and Office. For B2B companies it is relevant for a simple reason: it is the default in environments where many office workers spend their working day.

So the platforms reward different things, and the overlap is smaller than many people think. Across 100,000 analysed prompts, only 11.0% of the domains were cited by both ChatGPT and Perplexity; 37.4% were cited only by ChatGPT and 51.6% only by Perplexity, according to Profound. For a run-through of what each platform rewards, see our deep dive into the platform differences between AI Overviews, ChatGPT, Perplexity, Copilot and Gemini. The next layer is already on its way: agentic search, where the AI does not just answer but carries out tasks for the user (booking, comparing and ordering).

If you want your business to be visible and cited in AI answers, the conclusion has two parts. The mix of sources differs between platforms, and it also shifts over time as models are updated and new content deals are signed. So never build your strategy on a single source or channel. Going all in on Reddit visibility, for example, because Reddit carries a lot of weight in one particular measurement can work in the short term, but rarely in the long term, once the next model version reweights the sources. What lasts is breadth: content and mentions that hold up whichever source a platform happens to favour right now.

What does AI search do to search behaviour and traffic?

Two things are happening at once: fewer clicks per search, and more questions that are also longer. Zero-click searches (searches that never lead to a click) become more common when the answer is delivered directly. Pew Research Center analysed 68,879 Google searches by 900 US adults (March 2025): when an AI summary was shown, users clicked on a regular search result in 8% of visits, compared with 15% when there was no summary.

The questions themselves are changing too. When people can type whole sentences, they ask longer, more specific questions; the long tail is growing sharply, and the visitors who do click through are often further along in their decision. We have written about how the longer tail changes keyword work in How does AI affect SEO?.

A third change is harder to measure but at least as important: the brand carries more and more weight. An analysis by Ahrefs of 75,000 brands shows that brand mentions on the web correlate at 0.664 (Spearman) with how often the brand is mentioned in AI Overviews – more strongly than backlinks (0.218) or Domain Rating (0.326). We explore what that means strategically in Preferred Sources and brand signals.

What does AI search mean for your business?

The most important point first: AI search is not a threat you can wait out but a channel your potential customers are already using. And it has an awkward quirk. When someone asks an AI whether your product can do X and the information is missing, the AI tends to answer "no" rather than "I don't know". A wrong "no" at that moment costs you the deal outright. So visibility in AI search matters for more than traffic: it decides whether AI describes your offering correctly. That is the very core of AEO, and the reason the work needs both citable copy and a technical structure that machines can read – one without the other is not enough.

Where do you start? Measure your AI visibility first: ask the questions your customers ask, on the platforms they use, and see what is actually said about you. From there, there are three natural next steps:

• Concrete steps to appear in AI Overviews: the tactical work, step by step.
• AI SEO 2026: the guide: a structured plan for the first 90 days.
• The four places on Google's first page: the big picture of where visibility is now decided.

If you are thinking about bringing in help, we have also written honestly about what an AI SEO agency costs and what you should expect from one. And if you want help with your AI visibility, read about how we work as an AI SEO agency.