What is an AI search engine? Definition and how it works

An AI search engine uses language models to understand a query, search the web and write a summarized answer with sources. How it works and its types.

  • Alvaro Peña de Luna Alvaro Peña de Luna
  • date icon

    Wednesday, Sep 30, 2026

An AI search engine is a search engine that uses large language models to interpret a query, search a live index of the web and write a summarized answer from the pages it finds, usually with links to those pages as sources.

It keeps the core of search (a crawler, an index, retrieval) and adds a layer that reads and writes. The result looks like an answer engine, but the answer is grounded in fresh search results rather than only in what a model remembers.

How an AI search engine works

  1. Query understanding. The model works out what the user actually wants, including context from earlier messages.
  2. Fan-out. It often turns one question into several searches (for example “best CRM for startups”, “CRM pricing 2026”, “CRM reviews”). This is query fan-out.
  3. Retrieval. It pulls candidate pages from its index, often using semantic search that matches meaning rather than exact keywords.
  4. Generation. It writes the answer from the retrieved passages, ideally staying faithful to them (grounding).
  5. Citation. It shows some or all of the pages it used as sources.

Types of AI search engines

  • AI-native engines, built around the generated answer from the start. Perplexity is the clearest example, and ChatGPT works this way when it searches the web.
  • AI layered on classic search, where a traditional engine adds generated answers. Google’s AI Overviews appear above the organic results for some searches, and AI Mode offers a separate conversational view.

Both types can answer the same question differently, because they use different indexes, retrieve different pages and phrase the answer in their own way.

Why AI search engines matter for brands

In an AI search engine, the sources are chosen by the system and the user often reads only the summary. That changes what success looks like. Your page can be retrieved and quoted without earning a click, and your brand can be named on the strength of a third-party review you did not write. Visibility now has three parts: being retrieved, being cited as a source and being named in the answer. For the practical side of winning here, see our guide to AI search optimization.

How to measure your visibility in AI search engines

Because AI search engines show sources, you can measure how much of that source list belongs to you:

Citation share = sources from your domains ÷ all sources cited × 100

If 100 answers cite 600 sources in total and 30 of them are pages on your site, your citation share is 5%. Track it next to how often you are named in the text, since the two do not always move together. The citation share entry covers the metric in more detail.

Common mistakes

  • Assuming classic rankings carry over. Strong organic positions help, but AI search engines can quote pages that sit lower in the results.
  • Measuring only traffic. Referral visits from AI search are real but partial. Many users act on the answer without clicking.
  • Ignoring which sources are cited. The domains that keep appearing as sources for your topics are where your brand needs to be described well.
  • Testing one engine and generalizing. Perplexity, ChatGPT and Google retrieve and weigh sources in their own way, so a win on one does not guarantee the others.

How Mencoro tracks AI search engines

Mencoro tracks ChatGPT, Perplexity, Google AI Overview and Google AI Mode, plus the Google SERP top 10, for the prompts, keywords and countries you choose. For each AI answer it records the text and the sources; a source is yours when it points to one of your domains or their subdomains, even if the answer never names your brand. You get your Link position among the sources, your Coverage in the text and your share of voice against competitors, and you can compare them with your classic SERP position for the same topic. For Google specifically, see the Google AI Overview tracker, or check a single query with the free AI Overview checker. The methodology page explains every metric.

FAQ

Frequently asked questions

A chatbot can answer purely from what its model learned in training. An AI search engine searches a live index of the web for each question and builds the answer from the pages it finds, usually showing them as sources. Many assistants now do both, searching only when they judge the question needs it.
The best known are ChatGPT with search, Perplexity, and Google’s AI Overviews and AI Mode, which sit inside the world’s most used search engine. Usage shifts quickly, so check current figures for your market rather than relying on a fixed list.
Yes. AI search engines retrieve pages from a search index before they write, so a page that cannot be crawled or indexed cannot be cited. What changes is what you optimize for: being retrieved and quoted, not only being clicked from a list.

Start tracking your brand in AI search today

Monitor how AI engines cite your brand, track keyword positions, and benchmark against competitors, all in one platform.