How to Get Your B2B Company Into AI-Generated Answers
A big question for most B2B companies is “how do I get my company featured in AI answers?” The good news is that appearing in AI answers is easier than it seems, but it requires knowing how AI systems actually find, evaluate, and use content.
What is an LLM, and how do they recognize your company?
It may help to go technical and examine how large language models (LLMs), or an AI system trained on large amounts of source data to understand context and provide answers, work to retrieve answers. Common LLMs include Claude, Grok, ChatGPT, and Gemini, and these systems rely on training data to answer queries, although some can access web searches in real-time. Perplexity is a slightly different model, built around real-time web searches but using an LLM to synthesize its results.
Because LLMs are trained mainly on existing web content, when someone asks an AI about a company or category, the system draws on the signals present in training data to provide an answer. The training data can include a company’s earned media, authoritative mentions, company rating lists, and third-party validations. A company that has a strong earned media presence, involvement with analyst groups like Gartner or Forrester, presence on company ranking sites, and executive thought leadership in speaking opportunities or op-ed placements, will have a better chance of being mentioned.
What if a company is not in an LLM’s training data?
Many companies may not have a strong presence, or any presence, across these touchpoints. Or a company may use different taglines, descriptors, and benefits across external validators, which confuses the LLMs. When these situations happen, LLMs can react in a few ways:
The AI ignores the company: let’s say someone asks, “what are the best cloud security posture management tools?” This is the best description of the company’s current offerings, but the company has a history of being ranked as a top data loss prevention (DLP) solution provider. The AI does not see strong signals around the company being a cloud security posture management tool, so it does not include the company in the responses.
The AI gets the company wrong: there could be a situation where there are equal amounts of signals around a company being a cloud security posture management solution and a DLP provider. The AI uses the information to the best of its ability and categorizes the company as a DLP company that has cloud security posture management capabilities. This categorization downplays the true abilities of the company’s solution to potential buyers.
The AI can’t recommend the company: Let’s say the LLM has enough of a signal to rank a company as a cloud security posture management company, but not enough to give a robust response. The LLM could give a sparse answer or say that it does not have enough information on the company (if someone asked for your company by name).
Build your LLM presence
If your company is not actively building signals for LLMs, you are either missing from AI answers or being described inaccurately. The process requires time, strong content, and visibility across touchpoints.
First check: Common Crawl
The Common Crawl dataset is a primary source for training LLMs. If a company’s site is crawled and included in a Common Crawl snapshot, there's a better chance that its content becomes part of the LLM "knowledge” for training and later fine-tuning. You can’t submit your site to Common Crawl, but you can make your site easier for crawlers to find and index. Crawlers like Common Crawl like sites that are fast, cleanly structured, easy to navigate via internal links, and backed by a current XML sitemap. Your site needs to allow crawlers, too. Many companies unwittingly block the CCBot Crawler, which makes them undiscoverable to Common Crawl.
Second check: LLM-friendly content
Once your site is crawlable, the question becomes whether your content is the kind AI systems want to surface. Based on current GEO research and our own work with B2B technology clients, here’s what matters most:
Structure matters more than length. LLMs parse content that is organized clearly into short paragraphs, descriptive subheadings, and answer-first formats. Dense walls of text get deprioritized. The best way to approach the structure is to think of how your CEO would answer a question from a senior customer prospect and use that style to structure the content.
Data and authoritative elements increase your chances for LLM inclusion. Content that includes specific, quantifiable results will always outperform vague claims. A stat like 'a company using best GEO practices saw a 113% increase in LLM presence over nine months' gives an LLM something concrete to cite. 'Good GEO practices can increase your presence in as little as nine months' gives the LLM nothing.
In-depth material beats a large volume of high-level material. AI systems recommend sites that demonstrate genuine expertise in a specific area. A few deeply researched, well-written pieces in a company’s core category will outperform dozens of thin posts optimized for search keywords. This shows the difference between GEO presence, LLM rankings, and SEO. SEO rewards keyword presence, and the more that are there, the better for SEO. LLMs are looking for demonstrated topic expertise.
Clarity around what your company is and does. Your company’s purpose and offerings should be apparent and clear across your website, third-party citations, thought leadership pieces, and earned media. The more clearly your content defines who you are, what category you occupy, and how you relate to the broader ecosystem of your industry, the better AI systems can place you accurately in generated answers.
Earned Media Is Still the Most Powerful LLM Signal
Here is the thing that often surprises B2B marketers: the single most effective way to increase AI visibility is not website optimization. It is earned media.
When your company is cited, quoted, and referenced in credible third-party publications, AI systems treat that as corroboration. A quote in a tier-one technology publication, or a mention of your company as one to watch in a business publication, is valued highly by LLMs. The signals AI systems trust most are the ones that human audiences have always trusted: coverage, citation, and independent validation.
What to Do This Quarter (Q3 2026)
We are at the start of the third quarter of 2026, and here are some practical actions to take to get your company primed for LLM visibility in Q4:
Audit your current AI presence. Start by asking Claude, ChatGPT, and Gemini about the best provider for X, using the category in which you want inclusion. Then, ask about your company by name as well as your competitors. Record what they say as well as its accuracy. Note where you are missing or mispresented. This baseline shows your signal gaps. You can build an action plan to close these gaps.
Check your technical foundation. Make sure your site is crawlable, fast, and structured clearly. Remove any blocks on AI crawlers. Add schema markup where relevant.
Submit your sitemap to Google Search Console and Bing Webmaster Tools. Doing so won't get you into Common Crawl directly, but it strengthens the overall discoverability signals that do.
Build a content strategy that prioritizes in-depth knowledge. Take the two or three questions your best prospects are asking AI systems right now on the problem you solve and create authoritative, well-structured content that answers them definitively.
Invest in earned media. Get to know the top reporters who would cover your company in the technology, business, industry and broadcast media. Look for ways to engage them such as sharing trend data you have. The most important thing to note about earned media is that you have to adopt a reporter's mindset for the interaction. Many companies are stuck in sales mode and want to publicize their solution’s abilities. The reporter wants to share data and trends with their readers, and these readers will stop reading anything that looks like a sales pitch. LLMs love earned media.
The companies building these programs now will have a meaningful advantage starting Q4. AI visibility is not a future problem. It is a present one.
Anne Coyle is the founder of Coyle Emerald Narratives, a Boston-based B2B technology consultancy specializing in Generative Engine Optimization and AI visibility.