What is AI search, as distinct from a search engine?

By Yamm Labs · Updated September 2026 · 6 min read

A product head at a mutual fund in Mumbai types the same question into two boxes: which flexi-cap fund suits a first-time SIP investor with five thousand rupees a month? Google Search returns a page of links, a few ads and a comparison site at the top. ChatGPT returns three paragraphs that name four funds, explain why, and cite two pages she has never seen. Her fund appears in the first box on page one. It does not appear in the second at all. The two boxes look alike, but they do different jobs, and that difference is what AI search means.

How is AI search different from a search engine?

A search engine answers with a list. You choose which result to open, and the brand’s own page does the persuading once you land. AI search answers with prose. The engine chooses the sources, decides what to say about each brand, and the buyer may never click through. What the engine writes about you is the result.

The hub for this series, AI Search Optimisation: 100 Questions Answered, holds the short version of this answer alongside the related questions on GEO, AEO and measurement.

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Does AI search replace the search engine underneath it?

No. In most cases it depends on one. The engines’ own documentation shows how closely the two layers are tied.

• Google builds AI answers from its index. Google says a page must be indexed and eligible to be shown in Search with a snippet to appear as a supporting link in AI Overviews or AI Mode, and that no extra requirements or special optimisations are needed to appear there.
• Google searches more than the buyer typed. Google says both features may use a query fan-out technique, issuing several related searches across subtopics and sources to build one response.
• ChatGPT search has its own crawler. OpenAI says sites opted out of OAI-SearchBot will not be shown in ChatGPT search answers, and that GPTBot, its training crawler, is a separate setting. Blocking every AI bot in one robots.txt rule removes a brand from both.

So classic SEO hygiene still matters: a page that cannot be crawled cannot be quoted.

A search engine sends the buyer to your page; AI search reads your page and speaks for you.

Why does AI search change the rules for banks, insurers and funds?

Indian advertising rules were written for communications a brand controls end to end. AI search breaks that assumption by lifting one passage out of its page. We have not seen SEBI, IRDAI or RBI guidance that addresses AI summaries directly, so the design decision sits with the brand: write each quotable passage so it stays accurate when read alone. These are the decisions that follow from the rules.

• The fund warning moves into the passage. SEBI requires the standard market-risk warning in mutual fund advertisements, and in audio-visual ads it must be shown and voiced for five seconds so a viewer can follow it. On a fund’s answer page we place the warning in the same section as any return, category or scheme claim, not only in the footer, so a quoted section carries it.
• The insurer’s registered name goes in the text. IRDAI’s 2024 policyholder-protection regulations require an insurer’s advertisement to show its registered name with its trade name or logo prominently. An engine does not read a logo. Every answer section that names a plan names the insurer by its registered name in words.
• Distributor pages go through the insurer. The same regulations require advertisements issued through distribution channels to carry the insurer’s written approval before they are issued. When a bank or broker publishes answer pages about a partner’s plans, we build the insurer’s sign-off into the timeline before the page goes live, not after it is already indexed.
• The APR sits next to the rate. RBI requires lenders to give a Key Facts Statement, including the annual percentage rate, before the loan contract is executed, for retail and MSME term loans sanctioned from 1 October 2024. A loan answer page that quotes only a headline interest rate invites an engine to repeat a number the borrower will not see on the KFS. We place the APR, or a line explaining that it depends on charges, beside every rate.

None of this replaces legal review. It moves the regulator to the first layout decision.

What should a buyer decide: SEO, AI search optimisation, or both?

Both, in order. Crawlability and indexing come first, because AI search sits on top of them. Then comes the work that is specific to AI search: one question per section, the answer in the first sentence, facts out of PDFs and into HTML, consistent brand facts across the web, and disclosures placed inside each quotable passage.

Start with a baseline. Take the questions your buyers type, run them on each engine, and record whether your brand is named, cited and described correctly. That shows which layer is broken. We publish our own baseline in the Yamm Labs AI Visibility Log, and the full service for regulated brands is set out on our AI visibility agency page for BFSI brands. Yamm Labs works from Gurugram; our clients include TATA AIA Life Insurance, HDFC Life, Axis Bank, Paytm Money and Aditya Birla Sun Life Mutual Fund.

A worked example: one fund question, two answers

Go back to the product head at the Mumbai fund house and her flexi-cap question. The two results tell her two different things about her brand.

In the search engine, her fund is on page one. That means the page is crawlable, indexed and eligible for a snippet. The search layer works. A buyer who scrolls, compares and clicks can reach her page, where the scheme details and the risk warning sit together.

In AI search, her fund is missing. The engine read several pages, chose four funds and cited two sources she did not recognise. Her own page was not among them. The likely reasons sit in the passage, not the ranking. Perhaps the scheme facts live in a factsheet PDF. Perhaps no section answers the buyer’s question in its first sentence. Perhaps the risk warning sits only in the footer, so the one passage worth quoting is incomplete.

Her fix follows from the difference. She keeps the search layer as it is, then rewrites the scheme page into question-led sections, moves the key facts from the PDF into HTML, and places the SEBI warning in the same section as any return or category claim. Then she asks the same question again and records the answer.

Common mistakes when AI search is treated like a search engine

Most errors come from measuring or writing for the old layer only. These are the ones we see most often at banks, insurers and fund houses.

• Reading rank as presence. A page-one listing in a search engine says nothing about whether AI search names the brand. They must be checked separately.
• Keeping facts in PDFs. Rates, scheme details and plan features locked in a PDF are harder for an engine to lift as a clean passage.
• Leaving disclosures in the footer. An engine quotes a passage and drops what sits around it. The warning, registered name or APR has to sit in the passage.
• Blocking every AI crawler at once. OpenAI treats its search crawler and its training crawler as separate settings. One blanket rule can remove a brand from ChatGPT search answers without anyone intending it.
• Skipping the search layer. Google’s AI features draw on its index. A page that cannot be crawled or indexed cannot be cited there.
• Writing for keywords, not questions. AI search answers a question in prose. A section that opens with its answer is easier to quote than one that builds up to it.

A step-by-step checklist for an AI search baseline

A baseline shows which layer is broken before any money is spent. This sequence keeps it simple.

1. List the buyer questions. Take the questions buyers type before choosing a fund, policy or loan.
2. Check the search engine layer. Confirm the pages that should answer them are crawlable, indexed and eligible for a snippet.
3. Check crawler access. Review robots.txt for each AI crawler, including OAI-SearchBot, and record a deliberate decision for each one.
4. Ask each engine. Put the same questions to Google’s AI Overviews and AI Mode, ChatGPT search, Perplexity and Gemini.
5. Record three things. Whether the brand is named, whether it is cited, and whether what is said is correct.
6. Find the broken passage. For each miss or error, find the page section the engine should have used and see why it could not.
7. Fix and repeat. Rewrite the section with the answer first and the disclosure inside, then ask again on a fixed schedule.

Where a fix touches a regulated claim, confirm the current SEBI, IRDAI or RBI text with your compliance team before the page goes live.

How to brief an agency or team on AI search

A good brief separates the two layers so each can be measured. Include these points:

• The buyer questions you want to be named for, ranked by business value.
• The pages that should answer them, and any facts that sit only in PDFs.
• Your current robots.txt and who owns crawler decisions.
• The engines to track and how often.
• The regulators whose rules apply to you, and who in compliance signs off each page.

Ask for results in two parts: search engine health, and AI search presence. A team that reports only rankings is measuring one layer. Be wary of anyone who promises a place in an AI answer. The engine chooses its sources, and no one outside it controls that choice.

People also ask

Is Google a search engine or AI search?

Both. Classic Google Search returns a ranked list of links, while AI Overviews and AI Mode write an answer on top of the same index and cite supporting links. A page must be indexed and eligible for a snippet to be cited there.

Is ChatGPT a search engine?

ChatGPT search behaves like AI search: it looks up sources and writes an answer with citations rather than returning a list of pages. It uses its own crawler, OAI-SearchBot, so a site that blocks that crawler will not be shown in its search answers.

Do SEBI, IRDAI and RBI rules apply to AI answers about my brand?

The rules apply to your communications, and an engine quotes those communications. We have not seen guidance aimed at AI summaries, so the safe design is to place the required warning, registered name or rate disclosure inside every passage an engine might quote.

Why is my brand on page one of a search engine but missing from AI search?

Because the two layers judge different things. A search engine ranks pages. AI search picks passages it can quote and names the brands in them. A page can rank well and still have no single section that answers the buyer’s question clearly, or keep its key facts in a PDF. Check the passage, not the rank.

Does AI search send traffic to a brand’s website?

Sometimes. AI search cites a handful of sources, and a buyer may click one. But the answer itself often satisfies the question, so the buyer may never visit. That is why being named and described correctly inside the answer matters as much as the click. For a regulated brand, what the engine says is the brand’s first impression.

Is Perplexity a search engine or AI search?

Perplexity works as AI search. It looks up sources, writes an answer and shows the sources it cited, rather than returning a ranked list of pages for the buyer to read. Like other AI search tools, it depends on being able to find and read pages, so crawlability and clear, quotable sections still matter.

Do I need separate content for AI search and a search engine?

Usually not. One well-structured page can serve both: crawlable and indexed for the search engine, and written in question-led sections with the answer first for AI search. What changes is the discipline inside the page. Each section should make sense alone, with any regulated disclosure placed inside it.

Will AI search replace the search engine?

Not on the evidence of how it works today. Google builds its AI Overviews and AI Mode on top of its search index, and ChatGPT search relies on its own crawler to find pages. The two work as layers. A buyer may see a written answer first, but that answer still depends on pages a search engine or crawler can reach and read.