Search Engine Basics

How AI Search Works: From Index to Generated Answer

How 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.

Updated 26 Oct 20269 min readChecked against Google Search Central
Quick answer

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.

Usman AliWritten by Usman AliGrowth and SEO specialist · 7 years in SEO

The basics

What AI Search Is and What Has Changed

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

How AI Search Works, Step by Step

A generated answer is the last link in a longer chain. The first steps are the same ones that feed the ordinary results page.

01IndexPages are crawled, rendered, then stored as usual.
02UnderstandThe system works out what the question is really asking.
03Fan outIt may run several related searches at the same time.
04RetrieveThe most useful passages are pulled from the index.
05GenerateA language model writes the answer, adding source links.

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 in Plain Words

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.

Retrieval

Find the right material first

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.

Augmentation

Hand the material to the model

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.

Generation

Write the answer

The model writes a response that summarizes those passages in plain language. Good systems keep the answer close to what the sources actually say.

Citation

Show where it came from

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

Query Fan-Out: One Question, Many Searches

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.

Interactive · Query fan-out demo

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.

Try

The question
Generated answerBuilt from the sources above

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

AI Overviews and Google AI Mode

Google offers two main AI features in Search. They draw on the same index, yet they behave differently on the page.

AI Overviews

A short generated summary that appears above or among the regular results for some queries, with links to supporting pages.

Shown only for some queries

AI Mode

A separate, more conversational search mode that handles longer questions with follow-ups, using query fan-out to explore subtopics.

Introduced in 2025

Regular results

The familiar list of organic links, snippets and other features, which continues to appear alongside any AI content.

Still the core of Search

Google 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

AI Search Engines Beyond Google

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

Copilot with Bing

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

An answer-first engine

Perplexity presents a written answer as its main result, with numbered citations to the pages it used. It runs its own crawler, called PerplexityBot.

OpenAI

ChatGPT search

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.

Others

A growing field

Other engines, including Brave Search, add AI summaries to their results. The details change often, so check each provider’s own documentation.

Comparison

AI Search vs Traditional Search

The two approaches share their foundations, while the output looks quite different. The table sets the main differences side by side.

AspectTraditional searchAI search
What you seeA ranked list of links with snippetsA written answer with source links
Source of contentCrawled, indexed pagesThe same index, retrieved at answer time
Typical queriesOften short keyword phrasesOften longer, conversational questions
Follow-upsA fresh search each timeFollow-up questions keep earlier context
How pages appearAs ranked resultsAs cited sources inside an answer
Accuracy riskReaders judge each page themselvesThe summary can misstate a source
What a page needsTo be crawlable, indexed and relevantThe 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

How to Appear in AI Answers

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.

  1. Answer the main question clearly near the top of the page, in a sentence or two that stands on its own.
  2. Use descriptive headings so each section covers one subtopic a fan-out search might look for.
  3. Name your sources in the text, such as an official guideline or a public study, so claims are easy to verify.
  4. Keep important text in the HTML rather than hiding it behind tabs, scripts or logins.
  5. Make sure the page is indexed, then check that no nosnippet rule stops it from appearing in snippets.
  6. Show who wrote the page along with when it was last updated, which helps readers judge trust.
  7. Keep facts current, because an outdated figure can easily be repeated in an answer.

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

What You Can Ignore, and the Role of robots.txt

AI search has attracted plenty of confident advice. Some of it is unsupported by anything the search engines themselves have said.

Schema

No special AI schema is required

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.

llms.txt

Google does not use llms.txt

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.

Shortcuts

No trick replaces being useful

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.

Tracking

Data is still limited

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

Questions About AI Search

Does AI search use the same index as regular search?

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.

Do I need special markup to appear in AI Overviews?

No. Google says there are no extra technical requirements beyond being indexed and eligible to show a snippet in Search.

What is query fan-out?

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.

Can I stop AI tools from using my content?

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.

Will AI search replace traditional search results?

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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