AI Search: How It Works and the Main AI Search Engines Compared
AI search answers in sentences and cites sources. How it works, how ChatGPT, Google AI Mode, Perplexity and others compare, and what 99,000 answers show.
Key Takeaways: AI Search
5- AI search is search that answers in written sentences. Instead of ten links, you get a summary that names options and shows the sources it used.
- The main AI search engines are ChatGPT search, Google AI Overviews and AI Mode, Gemini, Perplexity, Microsoft Copilot, Claude, Grok and Brave Search. All of them can be used for free, with limits.
- Most AI search follows the same steps: understand the question, decide whether to search, run several related searches, read a few pages and write an answer with citations.
- Engines behave very differently. In nearly 100,000 answers we measured, Perplexity cited about 15 sources per answer and OpenAI models about 5, and two engines answering the same question on the same day shared only around one in ten of the sites they cited.
- For brands, the question changes from "where do we rank?" to "are we in the answer, on which engine, and which sources put us there?"
AI search is search that answers you in full sentences. You ask a question the way you would ask a person, and instead of a list of ten links you get a written answer that compares options, names products or brands and shows the pages it relied on. ChatGPT search, Google’s AI Overviews and AI Mode, Gemini, Perplexity, Microsoft Copilot, Claude, Grok and Brave Search all work this way.
It feels like one step, but behind the answer the engine runs several searches, reads a handful of pages and decides what to include. Those steps explain why the same question gets different answers on different engines, and why some brands appear in AI answers while others do not.
What is AI search?
AI search, also called generative search or generative AI search, combines a language model with a search system. The search system finds current pages; the language model reads them and writes the answer. The technique behind it is called retrieval-augmented generation (RAG).
The simplest way to see the difference:
- Traditional search says: “Here are pages that might answer your question.”
- AI search says: “Here is the answer, and here is where it came from.”
People also use AI search differently. Questions get longer and more specific (“which CRM works best for a 10-person agency that already uses Google Workspace?”), and follow-up questions continue the same conversation instead of starting a new search.
The main AI search engines in 2026
There is no single AI search engine. There are several, built by different companies on different search indexes, which is the main reason their answers differ.
| AI search engine | Made by | Where it gets its results |
|---|---|---|
| ChatGPT search | OpenAI | Search partners plus OpenAI’s own crawler, OAI-SearchBot |
| Google AI Overviews, AI Mode | Google’s search index | |
| Gemini | Google Search, when Gemini decides a question needs it | |
| Perplexity | Perplexity | Live web search on every question |
| Microsoft Copilot | Microsoft | Bing |
| Claude | Anthropic | Web search, when Claude decides a question needs it |
| Grok | xAI | The web and posts on X |
| Brave Search (Answer with AI) | Brave | Brave’s own independent index |
All of them show their sources as links, and all can be used for free with limits; paid plans add more searches, longer research modes or stronger models. Official descriptions: ChatGPT search, Google AI features, Perplexity, Copilot web search and Brave Search.
Which ones matter most depends on where your customers ask. ChatGPT and Google’s AI features reach the most people. Perplexity is popular for research because it searches on every question. Copilot sits inside Windows, Edge and Microsoft 365. Grok is used heavily on X.
How does AI search work?
Every engine has its own details, but most go through the same five steps.
1. Understanding the question
The model reads the whole question, including context from earlier messages, and works out what is really being asked: a definition, a comparison, a recommendation or a step-by-step answer. “Best laptop for video editing under $1,500” is understood as a shopping comparison with a budget, not as four keywords.
2. Deciding whether to search
Not every question triggers a web search. If the answer is stable general knowledge, the model may answer from what it learned in training. If the question involves recent events, prices, products or anything that changes, the engine searches the web first. This is why the same engine can cite sources for one question and none for another. In our data, OpenAI models searched and cited sources in 73% of answers, while Perplexity did so in every one.
3. Running several searches at once
For most questions, the engine does not run one search. It breaks the question into several related searches, for example “best video editing laptops 2026”, “laptops under 1500 for video editing” and “MacBook vs Windows for editing”, and runs them in parallel. This is called query fan-out. Where engines report their searches, Gemini ran about 3.9 searches per answer, Grok 3.3 and Claude 1.5. It is why a page can be cited for a question it never mentions directly.
4. Reading and choosing sources
From the results, the engine picks a small number of pages to read. Pages that load quickly, show their main content in the HTML, state facts clearly and come from sources the engine trusts are more likely to be chosen. Pages it cannot access, because they block its search bot or only show content after JavaScript runs, are skipped.
Reading is not the same as citing. Grok looked at about 30 pages per answer in our data but cited only one in four of them. Claude looked at about 13 and cited a little over 40%.
5. Writing the answer with citations
Finally, the model writes the answer from what it read, often naming specific products or brands, and attaches citations to the pages that support each part. The answer is generated fresh each time, so asking again can produce different wording, a different order and sometimes different brands.
How AI search engines differ: what nearly 100,000 answers show
Brantial asks the questions our customers track on each engine every day or every week, and records the answer and every source it cites. Between 21 September and 21 October 2026 that came to 99,626 answers to 6,156 questions. Here is how the engines that search the web compared.
| Engine (models measured) | Answers | Answers with sources | Sources per answer | Different sites per answer |
|---|---|---|---|---|
| Perplexity (Sonar) | 11,790 | 100% | 14.9 | 11.3 |
| Claude (Haiku 4.5, Sonnet 4.6) | 9,657 | 90% | 11.6 | 9.5 |
| Gemini (2.5 Flash, 2.5 Pro, 3.1 Pro, 3.5 Flash-Lite) | 24,647 | 86% | 8.8 | 7.7 |
| Grok (4.3) | 11,751 | 99.7% | 7.3 | 6.6 |
| OpenAI (GPT-5, GPT-5 mini, GPT-5.6 Luna) | 17,662 | 73% | 4.7 | 4.2 |
Sources per answer are averaged over all answers, including the ones that cited nothing. Three things stand out.
Engines cite very different numbers of sources. A Perplexity answer leans on three times as many sources as an answer from an OpenAI model. On an engine that cites four or five pages, there is much less room for your page in each answer.
They favour different kinds of sites. The share of answers citing at least one page from each platform:
| Engine | Wikipedia | YouTube | |
|---|---|---|---|
| Claude | 32.7% | 1.1% | 0.0% |
| OpenAI | 6.1% | 0.5% | 2.0% |
| Grok | 4.1% | 1.1% | 0.3% |
| Perplexity | 3.4% | 1.4% | 2.2% |
| Gemini | 2.5% | 8.8% | 7.1% |
Claude cited Wikipedia in a third of its answers. Gemini, which searches with Google, was the only engine that regularly cited YouTube and Reddit.
They rarely agree on sources. We compared answers to the same question from two engines on the same day. On average only 9% to 13% of the sites they cited were the same, depending on the pair. ChatGPT-family answers and Perplexity answers shared even one site in only 46% of cases; Gemini and Perplexity in 72%. Being cited on one engine says little about the others, which is why AI visibility has to be measured per engine.
How we measured: each question is sent through the provider’s API with web search turned on where the provider offers it. Mistral, Llama and DeepSeek answered without web search in our setup, so they are left out of the source figures. 93% of the questions were tracked for Turkey and the rest mainly for the US, the UK and the Netherlands. Answers in the consumer apps can differ from API answers, and the figures describe these questions, not every question people ask.
How do Google AI Overviews and AI Mode work?
Google has two forms of AI search.
AI Overviews appear above the normal results for some searches. Google generates a short summary from pages in its index and shows links to the sources beside it. The regular results still appear underneath.
AI Mode is a separate, conversational search experience. Google describes it as using query fan-out: it breaks your question into subtopics, searches each one and combines the findings into a longer answer with links. You can ask follow-up questions in the same thread.
Both draw on Google’s own index, so the basics of being indexed and crawlable still apply, and Google says there are no extra technical requirements. The difference is that being in the top ten results is no longer the whole story: what matters is whether your page is one of the few sources the summary is built from. What triggers AI Overviews covers which searches show them.
Does AI search the web in real time?
Often, yes. When ChatGPT, Perplexity, Gemini or AI Mode search before answering, they read current pages at the moment you ask, which is how they can answer questions about this week’s prices or news. They use their own crawlers to fetch those pages; OpenAI’s, for example, is called OAI-SearchBot. Our search bot guide lists which bot belongs to which engine.
When an engine does not search, it answers from training data, which has a cut-off date and can be months or years old. That is the main source of outdated facts in AI answers: an old price or a discontinued product the model learned about long ago.
AI search vs traditional search
| Traditional search | AI search | |
|---|---|---|
| You type | Keywords or short phrases | Full questions, with context and follow-ups |
| You get | A ranked list of links | A written answer with a few cited sources |
| What you do next | Open several pages and compare | Read the answer, maybe open one source |
| How sources are used | Each page competes for a position | A few pages are read and combined into one answer |
| Consistency | Results change slowly | The answer can change each time you ask |
The last two rows matter most for brands. In traditional search, ten pages share the first page. In AI search, a handful of sources shape the answer, and the brands those sources mention are the ones that get named.
Which AI search engine should you use?
It depends on the job.
- Research where you want to check every claim: Perplexity, which searches on every question and cites the most sources.
- Everyday questions inside Google: AI Mode, or the AI Overview at the top of the results.
- Long conversations, writing and follow-up questions: ChatGPT, Gemini or Claude, which decide per question whether to search.
- Work inside Microsoft 365: Copilot, which can combine web results with your own files.
- What people are saying right now: Grok, which also searches posts on X.
- Privacy: Brave Search, which answers from its own index without a Google or Bing account.
If you are asking for your business rather than for yourself, the better question is which engines your customers use. That is usually more than one.
Why AI search matters for brands
When people ask an AI engine for recommendations, the answer usually names a few options. If your brand is not among them, you are not part of the decision, even if your site ranks well on Google. Many people never click through to a source at all; they read the answer and move on.
That changes what success looks like. Clicks still matter, but so does being named in the answer, being named early and being described accurately. This is what AI visibility measures, and improving it is the goal of generative engine optimization (GEO).
How to see your brand in AI search
You cannot see AI answers in Search Console, so measuring them takes a different approach:
- List the questions your customers ask, from early research to direct comparisons. If you want to know which of these questions people ask most, prompt volumes estimate demand for questions the way keyword volumes do for searches.
- Ask them on each engine you care about, and repeat on a schedule, because answers change and, as the data above shows, engines rarely agree.
- Count who gets named and which pages get cited. The share of answers that name your brand is your AI visibility score.
- Read the answers that leave you out. The sources they cite show where your brand is missing.
Frequently asked questions
What is AI search?
AI search is a way of searching where an AI model looks up current web pages and writes a direct answer from them, with links to its sources, instead of showing a list of results. ChatGPT search, Google AI Mode and Perplexity are common examples.
What are the main AI search engines?
The most widely used are ChatGPT search, Google AI Overviews and AI Mode, Gemini, Perplexity, Microsoft Copilot, Claude, Grok and Brave Search. Each searches a different index, so the same question can get different answers and sources on each.
Is there a free AI search engine?
Yes. All of the engines above have a free version. Google’s AI Overviews and AI Mode, Brave Search and Microsoft Copilot are free to use, and ChatGPT, Perplexity, Gemini, Claude and Grok offer free plans with daily limits.
Which AI search engine cites the most sources?
In our measurement of nearly 100,000 answers, Perplexity cited the most, about 15 sources per answer, followed by Claude at about 12. Answers from OpenAI models cited about 5 on average and did not search at all for about a quarter of questions.
What is the difference between AI search and a chatbot?
A chatbot answers from what it already knows. AI search adds a live search step: it looks up current pages before answering and shows them as sources. Most assistants, including ChatGPT and Gemini, now do both and decide per question whether to search.
Is AI search replacing Google?
Not replacing, but changing it. Google itself now shows AI answers in AI Overviews and AI Mode, and many people use ChatGPT or Perplexity alongside it. Will AI search replace SEO looks at what this means for search work.
How does AI search choose which sources to cite?
It cites the pages it actually read to write the answer. Those are usually pages that match the searches it ran, can be crawled and read easily, state facts clearly and come from sources it considers reliable. Being in that small set matters more than ranking first for a single keyword.
Can I see how my brand appears in AI search?
Yes. Ask your customers’ real questions on each engine and note who is named and which pages are cited, or use a tool that does this on a schedule. Brantial’s free BrandScore gives a quick first read.