How search works
How search engines workThe five steps from discovery to rankingComponentsThe parts that make a search engine runCrawlingHow bots find and fetch your pagesIndexingHow a page gets stored so it can be foundCheck if indexedFour ways to confirm a page is on GoogleCrawling and indexing
Web crawlersGooglebot, Bingbot and the new AI botsGooglebotHow Google's crawler reads your siteRobots.txtRules, examples and a free testerXML sitemapCreate one, then submit it to GoogleCanonical tagPick the main version of a pageNoindex tagKeep a page out of search resultsRanking and results
Search engine rankingWhy one page appears above anotherGoogle ranking factorsWhat really matters, grouped simplyPageRankHow links pass value between pagesAlgorithmsTF-IDF, PageRank and modern rankingResults page (SERP)What each block on the page is forAI searchHow AI answers are built from the indexUnderstand
What is a search engineA plain definition with real examplesTypes of search enginesCrawler, meta, vertical, private and AIBrowser vs search engineTwo tools that people often mix upExplore
Best search enginesGoogle, Bing, DuckDuckGo and moreUses of search enginesThe everyday jobs that search handlesHistory of search enginesFrom Archie in 1990 to AI answersHow AI search works is easier to grasp once you see where it starts: with the same crawled and indexed pages that power regular results. An AI system retrieves passages from that index, then writes a summary with links to its sources, which is why the basics of being crawlable still apply.
AI search first finds relevant pages in a search index, then a language model writes an answer based on those pages, usually with links to its sources. Google's AI Overviews broadly follow this pattern, as does AI Mode, so pages still need to be crawlable, indexed and clearly written to be used.
The basics
AI search describes results where a language model writes an answer instead of only listing links. The links have not disappeared, although they now often sit beside or inside a generated summary.
A language model is software trained on large amounts of text to predict likely words, which lets it write fluent sentences. On its own it can sound confident while being wrong, so search companies connect it to their search index. The model then writes from pages it has just retrieved, rather than from memory alone.
Google rolled out AI Overviews in the United States in May 2024, then expanded them to many more countries. Microsoft’s Copilot, Perplexity and ChatGPT search offer their own versions of generated answers with source links.
The presentation has changed, along with the number of clicks some queries send to websites. The foundation is the same, because an engine can only quote a page it has already crawled and stored. If those steps are new to you, our search engine basics guide explains them from the start.
The process
A generated answer is the last link in a longer chain. The first steps are the same ones that feed the ordinary results page.
Steps one to four are search in the traditional sense. Only the fifth step is new, since a model turns the retrieved material into prose instead of showing a plain list of links. Our guide to how search engines work covers the first steps in detail.
This order explains a lot of confusing behavior. A page that is blocked from crawling, or missing from the index, cannot be retrieved, so it cannot be cited in an AI answer either.
The technique
Retrieval augmented generation, often shortened to RAG, is the general method behind most AI answers that cite sources. The name describes the two halves of the job.
The system searches a collection of documents, such as a web index, for passages that match the question. This step works much like ordinary search ranking.
The retrieved passages are added to the instructions the model receives. It now has fresh, specific text to work from instead of relying on memory.
The model writes a response that summarizes those passages in plain language. Good systems keep the answer close to what the sources actually say.
Links to the sources appear beside or within the answer. They let readers check the claims, which also sends some visitors to the cited pages.
RAG reduces mistakes, although it cannot remove them completely. AI answers can still misread a source or combine facts wrongly, so it is worth checking the linked pages for anything important.
Query fan-out
Google says AI Overviews and AI Mode may use a technique called query fan-out. The system splits a question into subtopics, then searches for each of them at once.
Imagine someone asks which hiking boots suit wet weather on a budget. Instead of one search, the system might also look up waterproof materials, price ranges, fit advice or care tips. It then combines what it found into a single answer with links to several pages.
Fan-out is one reason AI answers can cite pages that do not rank at the top for the original query. A page that clearly answers one narrow subtopic can be picked for that part of the answer.
Pick an example question or type your own, then watch how an AI search system splits it into smaller searches before writing one answer with citations. Hover over a numbered chip to see which source it came from.
This is a simplified demo with made-up example sites. Real systems choose their own searches, while typed questions here follow a fixed template.
Google offers two main AI features in Search. They draw on the same index, yet they behave differently on the page.
A short generated summary that appears above or among the regular results for some queries, with links to supporting pages.
Shown only for some queriesA separate, more conversational search mode that handles longer questions with follow-ups, using query fan-out to explore subtopics.
Introduced in 2025The familiar list of organic links, snippets and other features, which continues to appear alongside any AI content.
Still the core of SearchGoogle describes both features as ways to help people with more complex questions, while pointing them to the web for further reading. It states that a page only needs to be indexed and eligible for a snippet to be shown as a supporting link, with no extra technical requirements.
Answer engines
Several other services build answers in a similar way. Each one runs its own retrieval system, so the sources they cite can differ for the same question.
Microsoft’s Copilot draws on Bing’s search index to ground its answers. Pages that Bing can crawl and index are the ones it is able to cite.
Perplexity presents a written answer as its main result, with numbered citations to the pages it used. It runs its own crawler, called PerplexityBot.
ChatGPT can search the web for current information, then answer with links to its sources. OpenAI uses a crawler called OAI-SearchBot for this feature.
Other engines, including Brave Search, add AI summaries to their results. The details change often, so check each provider’s own documentation.
Comparison
The two approaches share their foundations, while the output looks quite different. The table sets the main differences side by side.
| Aspect | Traditional search | AI search |
|---|---|---|
| What you see | A ranked list of links with snippets | A written answer with source links |
| Source of content | Crawled, indexed pages | The same index, retrieved at answer time |
| Typical queries | Often short keyword phrases | Often longer, conversational questions |
| Follow-ups | A fresh search each time | Follow-up questions keep earlier context |
| How pages appear | As ranked results | As cited sources inside an answer |
| Accuracy risk | Readers judge each page themselves | The summary can misstate a source |
| What a page needs | To be crawlable, indexed and relevant | The same, plus clear passages that are easy to quote |
For site owners, the practical point is that both systems reward many of the same qualities. Solid SEO basics still decide whether a page is available to be quoted at all.
Visibility
Nobody outside the search companies knows exactly how sources are chosen. These practices line up with what Google publishes, along with what seems to help in practice.
None of these steps guarantees a citation. They make a page easier for people to understand first, which is the goal Google says its systems are built to reward.
Fact and hype
AI search has attracted plenty of confident advice. Some of it is unsupported by anything the search engines themselves have said.
Google states that no special markup is needed to appear in AI Overviews or AI Mode. Structured data still helps with rich results, although it is not an entry ticket for AI features.
An llms.txt file is a proposed plain text summary of a site for AI tools. Google has said it does not use the file, so it has no effect on Google Search.
Rewriting every page in a special AI style is unlikely to help on its own. Clear, accurate content that answers real questions remains the safer investment.
Search Console counts AI feature traffic within the overall Web search data, which makes it hard to separate from regular results. Treat any outside estimate of AI traffic with caution.
The robots.txt file tells crawlers which parts of a site they may visit. For Google, the normal Googlebot rules control access for Search, which includes its AI features. A separate token called Google-Extended lets you opt out of some Gemini model uses without affecting how your pages appear in Search.
Other providers publish their own user agents, such as GPTBot for OpenAI model training or OAI-SearchBot for ChatGPT search. Blocking a search crawler can remove you from that engine’s answers, so decide carefully before adding a rule. Our guide to the web crawler explains how these rules are read.
FAQ
For Google, yes. AI Overviews and AI Mode draw on pages from Google’s search index, which is why a page must be indexed before it can be cited.
No. Google says there are no extra technical requirements beyond being indexed and eligible to show a snippet in Search.
It is a technique where the system splits one question into several related searches, then combines the results into a single answer. Google says its AI features may use it.
You can block specific crawlers in robots.txt, although blocking a search crawler may also remove you from that engine’s results. In Google Search, snippet controls such as nosnippet limit what can be shown.
Nobody outside the search companies can say for certain. For now, AI answers sit alongside links to websites, while both depend on the same crawled pages.
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