Getting Found in AI Search: What B2B Companies Need to Know

A buyer who would once have typed “industrial filtration suppliers Ontario” into Google now often asks an AI assistant instead. They get back a paragraph naming three or four companies, with a short explanation of what each one does well.

If your company isn’t in that paragraph, you were never in the running. The buyer didn’t scroll past you. They never saw a list to scroll.

This is the other half of the AI question. We’ve written about whether you should let AI build your website, where our answer is mostly no. Being found by AI is a different matter entirely, and the sensible position there is pragmatic rather than skeptical.

What has changed, and what hasn’t

Let’s start with the reassuring part. AI answers are assembled from the same web that search engines have always crawled. There is no separate AI index you need to buy your way into, and no secret file that opens the door to one.

Everything in our guide to B2B SEO basics still applies. A site that is slow, poorly structured, thin on content, or invisible to crawlers will fail at AI visibility for exactly the reasons it fails at ordinary search.

What has changed is the unit of competition. Traditional SEO asks whether your page ranks for a query. AI search asks something narrower. Does your page contain a clear passage that answers one small part of what someone asked?

That shift matters more than it sounds. A page sitting outside the top ten can still be quoted, if the passage is good. A page ranking first can be skipped entirely, if its answer is buried three paragraphs into a section.

The engines don’t share an index

Here’s the part that surprises people. There is no single AI search to optimize for, because the major assistants retrieve from different places.

• Google’s AI Overviews and AI Mode run on Google’s own index
• ChatGPT retrieves through Bing
• Claude retrieves through Brave
• Perplexity runs its own crawler alongside other sources

The practical consequence is that the same question, asked in four places, can return four different sets of companies. If you’ve only ever checked how you appear in Google, you have a quarter of the picture. It might be worth ten minutes of your time to ask each of those four assistants the same question a buyer would ask about your category, and write down who gets named. That’s your actual competitive position in AI search, and most B2B companies have never looked at it.

How the answers get built

Google’s AI Mode does something called query fan-out. It takes one question, breaks it into several smaller sub-questions, retrieves passages for each, and assembles the reply.

This is why topical depth pays. A single strong page might answer one sub-question. A cluster of related articles covering a subject properly can answer several, which puts you in the response more than once.

It also explains a finding that unsettles people who have spent years chasing rankings. Only about half the domains cited in AI Mode match the top ten organic results for the same query, and barely a third of the exact URLs do. Ranking well helps, because it signals the quality that retrieval systems look for. It does not guarantee a citation, and its absence doesn’t rule one out.

What makes a passage citable

The good news is that writing for AI retrieval and writing for a busy human reader turn out to be nearly the same job.

1. Answer the question early. Put a direct, complete answer in the first hundred words of a section, before the context and the caveats. A reader skimming on a phone wants this too.
   
   
2. Use headings that match real questions. “How long does a website redesign take?” is retrievable. “Timelines” is not.
   
   
3. Be specific and attribute it. Named figures, dated standards, and concrete ranges get quoted. Vague claims get passed over. A page that says “most B2B marketing sites run fifteen to thirty thousand dollars” is more citable than one that says pricing varies.
   
   
4. Keep passages self-contained. A paragraph that only makes sense after reading the two before it is hard to extract. Each section should stand on its own.
   
   
5. Use tables and lists for comparisons. Structured content is easier for a retrieval system to parse, and easier for a person to scan.
   
   
6. Say when you last checked. Freshness signals matter, particularly on topics where the facts move.

None of that is a trick. It’s the same advice you’d get from a good editor, which is roughly the point.

The llms.txt question

You may have read that you need a file called llms.txt on your site, a plain-text summary telling AI systems what your site contains. It seems to be the most common piece of AI SEO advice going around and to be honest, it’s half wrong.

For Google, it does nothing. Google has said on the record, repeatedly, that it does not use llms.txt for Search, for AI Overviews, or for AI Mode. Its 2026 guidance names the file directly as a tactic that doesn’t help. Publishing one won’t hurt your rankings either, but if Google visibility is your goal, this is not where the effort belongs.

For other assistants, it’s a different story. Perplexity and Claude do retrieve the file today, and adoption is common among documentation and developer-tool companies. Stripe, Cloudflare and Anthropic all publish one.

So do you really need it? The recommendation depends on your business:

• Skip it if you’re a typical B2B manufacturer, distributor, or professional services firm whose buyers arrive through Google. Spend the time on content and structure instead.
  
  
• Consider it if you sell software, publish technical documentation, or have an API that developers build against. It costs almost nothing to produce, and your audience is the one using the assistants that read it.

How to utilize Preferred Sources

One genuinely new lever arrived in 2026. Google’s Preferred Sources feature, which previously affected only Top Stories, extended into AI Overviews and AI Mode in a rollout announced in late May 2026.

It works differently from everything else in search. A reader actively chooses your site in their Google settings, and from then on your content is favoured and visibly labelled for that person, including inside AI answers. Google reports that preferred links are roughly twice as likely to be clicked, though it hasn’t published independent verification of its adoption figures.

You can’t optimize your way into it. You can only ask, which suits B2B companies with a real audience better than it suits most tactics. If you publish regularly and have clients, prospects, and partners who read what you write, adding a “make us a preferred source” link to your articles is a small job with a long tail.

There are two limitations worth knowing about. It works at the domain or subdomain level, not for individual sections of a site. And it only helps with readers who already know you, so it compounds an existing audience rather than creating one.

Measuring any of this

Measurement in AI search is genuinely immature, and you should be suspicious of anyone selling certainty about it.

What you can rely on is modest. Google Search Console has counted AI Mode data within its Web search type totals since June 2025, so a page with rising impressions and a falling click-through rate is a reasonable sign that answers are being read without the click. Manual spot checks across the four assistants, done monthly, tell you more than most dashboards.

Dedicated AI visibility tools exist and the category is growing quickly. For a small or mid-sized B2B company, we’d suggest waiting. The tools are expensive, the metrics aren’t standardized yet, and the actions they recommend are the ones in this article anyway.

There’s a harder truth underneath the measurement problem. Ahrefs found that AI Overviews reduce clicks on the first organic result by around a third. Some of the visibility you earn will never show up as a visit at all, because the buyer got what they needed from the summary.

Being named in the answer still shapes who makes the shortlist, and that is the stage of the buying journey where B2B deals are won or lost.

What not to bother with

• Stuffing your pages with questions and answers in the hope of matching prompts. Retrieval systems read meaning, not keyword density.
  
  
• Buying “AI optimization” packages that won’t explain what they actually change.
  
  
• Blocking AI crawlers by accident. Check that a well-meaning robots.txt edit hasn’t removed you from the assistants you want to appear in.
  
  
• Rewriting your whole site for machines. The pages that get cited are the ones written clearly for people in the first place.

Results are closer than you think

AI search rewards the same things good web strategy always rewarded. Clear answers, real expertise, honest specifics, and a site built so both people and machines can find their way around it.

The companies struggling with this are mostly the ones that were already struggling to be found. If your site says little, says it vaguely, or says it using words that your buyers don’t use, no amount of AI optimization will rescue it. If your site is genuinely useful, you are closer than you think.

If you’d like to know how your company currently shows up when buyers ask an assistant about your category, book a discovery call and we’ll run those searches together – no pitch, and no pressure.