Through four intake routes, none of which involves you filling out a form. Engines learn about businesses from their training data, the web as it existed when the model was built, from live web search at question time, from AI crawlers that visit and read your website directly, and from licensed third-party sources like the Reddit archive Google pays to train on.
The unsettling and useful part is the same fact: there is no front desk. You cannot submit your business, and you cannot opt out of being described. What the routes can read is what the engines know, which means your only lever is making the readable record clear, consistent, and confirmed everywhere those routes actually look.
- There is no submission form: engines learn from what they can read, so the public record is the only interface.
- Four routes feed the machine: training data, live search, AI crawlers on your site, and licensed sources like Reddit's archive.
- The crawlers are already visiting: GPTBot alone made 569 million fetches across one hosting network in a single month, reading sites like yours.
- Human discussion is licensed intelligence: Google pays Reddit $60 million a year to train on real conversations, which makes community mentions machine-visible evidence.
- Consistency across routes decides trust: engines cross-check what your site says against what the rest of the web says, and contradictions read as risk.
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Where does AI get its information about businesses?
From four routes, each with its own personality:
- Training data. The web as it existed when the model was trained: sites, articles, discussions, directories. This is the engine's long-term memory, refreshed only when models update, which means it can lag reality by months.
- Live web search. Search-native engines like Perplexity and Google's AI answers, and increasingly the assistants too, search at question time and read current pages before answering. This is where recent changes surface fastest.
- AI crawlers. Dedicated bots, GPTBot for OpenAI, ClaudeBot for Anthropic, PerplexityBot and others, visit websites directly to collect and refresh what the engines know.
- Licensed and structured sources. Paid deals for high-value archives, most famously Google's arrangement to train on Reddit's human conversations, plus the directories and platforms engines treat as reliable.
The strategic takeaway is that these routes cross-check each other. An engine reads your site, then looks for the rest of the web to agree. A business visible on one route and absent from the others reads as thin, which is why the fix is never a single page. It is a consistent record everywhere the routes look.
Are AI crawlers actually visiting my website?
Almost certainly, and at a scale most owners have never checked. Vercel's analysis of traffic across its own hosting network measured AI crawlers as a major new presence on the web: OpenAI's GPTBot alone made 569 million fetches across that one network in a single month, with the other AI crawlers adding substantial volume of their own, already a meaningful fraction of what Google's own crawler does.
Three practical things follow:
- You can verify it tonight. Your hosting or analytics logs will show user agents like GPTBot, ClaudeBot, PerplexityBot, and Google-Extended. Their presence means the engines are actively reading you; their absence is worth investigating.
- You control the door. Your robots.txt file can welcome or block each crawler by name. Blocking has legitimate uses, but for a business that wants to be recommended, blocking the crawlers is asking to be forgotten.
- A visit is not comprehension. Crawlers fetch what your site serves; whether they can extract meaning from it is a separate question about structure and clarity, and it is the more common failure.
What do third-party sources teach AI about a business?
The part engines trust most: what other people say when the business is not in the room. Your own website is testimony; the third-party record is the cross-examination, and engines weigh it accordingly.
The evidence for how seriously the industry takes human discussion is written in contracts. Google pays Reddit a reported $60 million a year specifically to train its AI on the platform's conversations, because millions of people candidly discussing what worked, what failed, and who they would recommend is exactly the ground truth engines cannot generate themselves.
Beyond the marquee deal, the third-party record engines read includes:
- Reviews, on the platforms your industry actually uses.
- Directories and professional listings, which confirm existence, category, and location.
- Press, articles, and podcast appearances, which attach your name to your expertise on domains with their own authority.
- Community discussion, forums, Reddit, professional groups, where recommendations happen in the wild.
Each mention is a witness. A business its own website describes one way and the third-party record confirms is verifiable; a business only its own website describes is a claim waiting for corroboration.
Can I tell AI about my business directly?
Not in the way owners hope. There is no portal where you register with ChatGPT, no form that updates Claude, no fee that gets you into Perplexity's answers. The engines deliberately learn from the open record rather than from self-submission, because self-submission is exactly the channel spam would flood.
What does exist is narrower and still worth doing:
- Make your site maximally legible to the crawlers that visit: clear answers, structured data, no walls between them and your content. This is the closest thing to telling the engines directly.
- An emerging convention called llms.txt lets a site offer AI systems a plain-text guide to its most important content. Adoption is early and uneven, but it costs little and signals current stewardship.
- Feed the surfaces engines already trust: complete professional profiles, accurate directory listings, active presence where your industry gets discussed.
The mental shift that helps: you do not tell the engines about your business. You publish evidence where their routes already look, and the routes carry it in. Anyone selling guaranteed AI placement is selling something the architecture does not offer.
How do I find out what AI currently knows about me?
Ask the engines themselves, the same way a prospect would, and audit what comes back in layers.
- The direct lookup. 'Tell me about [your business]' on two or three engines. You are grading four possible states: rich and accurate, thin, outdated, or wrong, and each points at a different intake route failing.
- The buyer's question. 'Who should I hire for [what you do] for [who you serve]?' Whether you appear, and what reasons get attached, shows how your evidence competes, not just whether it exists.
- The source check. On engines that cite, note where their information about your category comes from. Those domains are the third-party surfaces worth showing up on.
- The crawler check. Your own logs, for GPTBot, ClaudeBot, and friends, confirm whether the reading route is even reaching you.
Run the layers quarterly and screenshot everything, because the answers move as the routes refresh. Running all four layers systematically, across engines, with the failing route identified and the fix ordered, is exactly what our free AI Visibility Scan does.
The PLB Perspective
The question always arrives with a hint of disbelief, as if there must be an office somewhere that assigns businesses to AI answers, and someone forgot to file the paperwork. What actually exists is stranger and more democratic: the engines learn about you the way a diligent stranger would, by reading your site, checking what others say, and noticing whether the story holds together. There is no desk to petition. There is only the record.
I find owners consistently overestimate the exotic routes and underestimate the mundane one. They ask about training data cutoffs and licensing deals while their own website, the surface every single route eventually reads, still describes their business in riddles. The crawlers are already visiting, at a scale that shocked even infrastructure companies. The question was never whether the machines would come looking. It is what they find when they arrive.
And notice the compounding kindness of feeding all the routes at once: the same clear answer that helps a crawler helps the live search; the same podcast appearance that earns a mention seeds the next training run; the same consistency that satisfies one engine's cross-check satisfies them all. This is not four marketing programs. It is one honest public record, maintained, and every route drinks from it. The businesses that grasp that stop optimizing for machines and start documenting for the stranger, which was always the better strategy anyway.
Cindy Anne Molchany · Founder
For a business that wants clients, blocking is usually self-sabotage: a crawler that cannot read you cannot recommend you, and being absent from AI answers costs far more than content reuse does. The nuance is real for publishers monetizing content itself. For a service business, your expertise being quoted with your name attached is the marketing, not the theft.
Fragments, at best. Engines can assemble a partial picture from directories, reviews, and mentions, but without an owned site there is no authoritative source to anchor the story, so answers about you stay thin, stale, or wrong, and buyer-question appearances become unlikely. A website is no longer a brochure; it is the primary document the machines read to decide you exist.
It depends on the route. Live-search engines can reflect changes within days of crawlers re-reading you; training data can lag months behind reality. This split is why a business that recently rebranded or moved sees engines confidently reciting its past. Consistent updates everywhere the routes look, plus patience for the slower route to catch up, is the whole remedy.
Not personally, and ham-fisted self-promotion there backfires with both the community and the engines. What matters is that genuine discussion of your category happens on platforms engines demonstrably value, Google pays for Reddit's archive precisely because the conversations are unscripted. Earned mentions, where real people recommend you unprompted, carry the weight. That comes from being recommendable, not from posting.
Because the engines cannot verify enough about you to stake a recommendation on it. Here is what AI checks before it names a business, and how to find out where you fall short.
Through a verification pipeline: interpret the question, retrieve sources, check what holds up, and assemble an answer with reasons. Understanding each step shows you exactly where businesses get filtered out.
First, understand what you just saw: not a quality verdict, a verification verdict. Then use the answer itself as your repair map, because the engine just showed you exactly what it rewards in your category.