How AI Search Engines Pick Which Businesses to Recommend

Search behaviour is changing. A growing share of people ask ChatGPT, Google's AI Overviews or another assistant for a recommendation instead of scrolling through search results themselves. That shifts the question from "how do I rank on page one" to "how does an AI decide which business to mention at all." This guide explains how that decision actually gets made, how to check where your own business stands today, and what to fix first.

The short answer: clear, structured, accurate information

AI search tools generate answers by reading across many sources and extracting facts, rather than sending a visitor to browse a list of links themselves. What gets a business mentioned is content an AI can read confidently and extract without guessing — clear statements of what you do, where you are, what you charge and how to contact you, ideally backed by structured data that labels those facts explicitly. A business with vague, inconsistent or outdated information online is far less likely to be surfaced, no matter how good the underlying product or service actually is.

What AI search tools actually look for

• Clear, factual statements. Direct sentences ("We offer X starting from RM Y") are easier for an AI to extract and repeat accurately than vague marketing copy.
• Structured data (schema markup). Code that labels your business name, services, pricing, hours and location explicitly, rather than leaving an AI to infer it from prose.
• Consistency across the web. The same name, address, phone number and details on your website, Google Business Profile and other listings, so an AI isn't reconciling conflicting facts.
• Content that's actually crawlable and current. Pages that load reliably and reflect up-to-date information, since AI tools work from the same indexed content traditional search does.
• Answers to the actual questions customers ask. A page written as a direct answer to "how much does X cost" or "does Y do Z" is more quotable than a page written purely to sell.

How different AI assistants source information

The specifics vary tool to tool, but they converge on the same underlying signals above. ChatGPT answers from training data with a fixed cutoff unless browsing or search is enabled, in which case it pulls in live web results similar to a search engine. Perplexity searches the live web for every query and displays its sources alongside the answer, so being a cited source can drive a direct click. Gemini draws heavily on Google's own search index, so the same signals that help traditional Google visibility carry over. Copilot is built on Bing's search index, rewarding similar fundamentals — clear content, structured data, an accurate Bing or Google business listing. None of this calls for a separate playbook per tool; getting the fundamentals above right once carries across all of them.

What this means in practice is that a business doesn't need to chase every tool separately or guess which one its customers happen to use. A Malaysian business owner might assume customers mostly use Google, while their customers are actually asking ChatGPT or Gemini for a recommendation directly — and since the same underlying facts (clear services, consistent listings, accurate pricing, structured data) feed all of these systems, fixing them once pays off regardless of which assistant a given customer reaches for.

How this differs from traditional SEO

Good SEO fundamentals — fast pages, clear content, accurate information — still matter and form the foundation of AI visibility too, so you're not starting from scratch. The difference is that traditional SEO optimises for ranking in a list a person scrolls through, while AI search optimises for being confidently extracted and stated as fact in a generated answer. That puts more weight on structured data and unambiguous, well-labelled information than on keyword density or backlink count alone. A page can rank reasonably well in classic search while still being a poor source for an AI to quote, if its facts are buried in dense paragraphs rather than stated plainly.

There's also a difference in how success is measured. Traditional SEO gives a business a position — first page, third result, top of the local pack — that's visible and trackable. AI search doesn't offer an equivalent ranking; a business is either mentioned accurately, mentioned inaccurately, or not mentioned at all, and the only way to know which is to ask the assistants directly, since there's no dashboard yet that reports it the way Google Search Console reports rankings.

Outdated information is worse than no mention

An AI assistant reading a page with a disconnected phone number, a discontinued service, or last year's pricing may repeat that outdated information with full confidence — which does more damage to a business than not being mentioned at all. A customer who shows up expecting a price that no longer applies, or calls a number nobody answers, blames the business, not the assistant that misquoted it. Keeping core facts (contact details, services, pricing, hours) current across a website and its listings is one of the simplest, highest-leverage things a business can do here.

This is a genuinely different risk from traditional search, where an outdated page mostly just ranks worse over time. An AI assistant doesn't signal uncertainty the way a search results page does — it states the answer as fact, with no obvious indication to the customer that the underlying source might be stale. That makes a quarterly review of prices, services and hours worth treating as routine maintenance rather than an afterthought, especially for anything with a price attached.

Does a Google Business Profile still matter?

Yes, and possibly more than before. AI tools frequently draw on the same business listing data — name, address, opening hours, category, reviews — that powers Google Maps and local search results. Keeping that profile accurate, complete and regularly updated remains one of the highest-value, lowest-effort things a local business can do, whether the recommendation comes from a person searching or an AI generating an answer. Our guide to setting up and optimising a Google Business Profile in Malaysia covers exactly what to fill in and keep current.

Does an llms.txt file help?

It's an emerging convention rather than a guarantee — a small text file at a website's root that summarises key pages in plain language for AI tools to read. Some AI crawlers reference it; others ignore it entirely, since it isn't a universal standard the way a sitemap is for search engines. It's worth adding as a low-cost extra, but it doesn't replace clear content and structured data as the fundamentals. Think of it as a short, direct briefing document for a machine reader, sitting alongside — not instead of — the structured data and plain-language facts already discussed above.

A 10-minute AI-visibility check you can run today

Before changing anything, it helps to see where a business actually stands. This takes about ten minutes and needs nothing but a browser:

• Step 1 — Ask the assistants directly. Open ChatGPT, Perplexity and Gemini and ask each one a question a real customer would ask, such as "recommend a [your service] in [your city]." Note whether your business comes up at all, and whether what it says about you is accurate.
• Step 2 — Read your own homepage as a machine would. Can you find your services, your starting prices and your contact details stated as plain sentences within the first screen or two, or are they buried in a slideshow or a vague tagline?
• Step 3 — Check consistency across listings. Compare the name, address and phone number on your website, your Google Business Profile and any directory listings. Any mismatch is a fact an AI has to guess between.
• Step 4 — Look for structured data. View your page's source (or use Google's Rich Results Test) and check whether your business, services and FAQ content are marked up with schema, or whether it's plain text only.
• Step 5 — Check your Google Business Profile. Confirm the category, hours, services and photos are current, and that recent reviews haven't surfaced an outdated fact you've since corrected on your website but not there.

Most businesses that run this check find at least one of the five failing — usually inconsistent contact details or a complete absence of structured data. Both are fixable without a full redesign: updating a phone number everywhere it appears takes an afternoon, and adding schema markup to an existing page is a focused, bounded piece of work rather than a rebuild. The bigger the gap between what the assistants say and what's actually true, the higher the priority to fix it.

Traditional SEO vs GEO fundamentals side by side

Common mistakes

• Burying prices and services in a slideshow or PDF brochure. An AI can't extract facts from an image carousel; it needs plain, crawlable text.
• Letting listings drift out of sync. A phone number changed on the website but not on Google Business Profile leaves an AI with two conflicting facts to choose between.
• Writing only for a human scanning, not a machine extracting. Vague taglines read fine to a person but give an AI nothing concrete to quote.
• Assuming one AI tool's behaviour applies to all of them. Optimising only for ChatGPT and ignoring Gemini's reliance on Google's own index leaves half the picture unaddressed.
• Treating llms.txt as a silver bullet. It's a useful extra, not a substitute for clear content and schema markup.
• Never checking what the assistants actually say. Without running the check above, a business has no idea whether it's being recommended, misrepresented, or ignored.

Where Gotka Technologies fits

Gotka offers Generative Engine Optimisation as an add-on to web design packages — structuring a site's content and adding schema markup so AI search tools and assistants across ChatGPT, Perplexity, Gemini and others can read and represent the business accurately. On the package builder, this is offered as GEO Basic (from RM1,200) or GEO Advanced (from RM4,200), built on top of the basic SEO — meta titles, alt text, an XML sitemap — included free in every package, whether that's the Starter package from RM5,300, Business from RM9,800, or Growth from RM14,300.

Key terms used in this guide

• GEO (generative engine optimisation): structuring and writing content so AI answer engines can extract and cite it accurately.
• Schema markup: structured code added to a page that labels facts like price, hours or service explicitly, rather than leaving them in plain prose.
• AI Overviews: Google's generated summary shown above normal search results, built from crawled and indexed pages.
• llms.txt: an emerging convention, a plain-text file at a site's root summarising key pages for AI crawlers to read.
• NAP consistency: keeping a business's Name, Address and Phone number identical across a website and all listings.
• Extractable fact: a statement specific and plain enough that an AI can quote it confidently without inferring or guessing.
• Google Business Profile: the free Google listing showing a business's hours, location, category and reviews on Maps and local search.
• Rich Results Test: Google's free tool for checking whether a page's structured data is valid and readable.