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B2B buyers are already changing how they research. Before they consider filling a form or taking a sales call, a growing share of B2B decision-makers are asking ChatGPT, Google’s AI Overviews, Perplexity, Gemini and Copilot to explain a problem, compare approaches, and shortlist the key vendors for your sector. If your brand isn’t named in those answers, you won’t be considered.
Generative Engine Optimisation (GEO) is how you change that. This playbook explains what GEO means for B2B specifically, how AI search engines decide which brands to cite, and what we found when we audited the AI-readiness of 50 B2B websites. Most, it turns out, are not ready. That is precisely why there’s an opportunity here for brands that move quickly.
Key takeaways
- AI search is now part of the B2B buying journey. Buyers use generative engines to research and shortlist vendors before contacting sales. GEO determines whether your brand appears at that moment.
- Data shows most B2B sites are not ready to be cited. In our audit of 50 B2B websites, 69% had no Organisation schema, 73% had no llms.txt file, and 10% were actively blocking AI crawlers from accessing their site.
- The fastest wins are technical and structural: add structured data, confirm AI crawlers can reach you, structure content answer-first, and earn third-party validation.
- GEO builds on SEO, not replace it. GEO & SEO work together, because AI engines retrieve much of what they cite from the same search indexes you already optimise for.
What GEO means for B2B businesses
Generative Engine Optimisation is the practice of structuring your content and online presence so that AI search engines surface, trust and cite your brand in the answers they generate. While traditional SEO aims to win a clickable position on a results page, GEO aims to make your brand the source an AI draws on when it answers a buyer’s question directly.
For B2B brands, the stakes are higher than for most consumer categories, for a few reasons:
B2B buying journeys are long, considered and involve multiple stakeholders. Buyers do extensive self-directed research before they ever speak to a salesperson (which they prefer not to do), and AI assistants are quickly becoming the front door to that research. A single AI answer can define the shortlist that an entire buying committee works from.
These are high-value, low-frequency purchases. Being included in, or excluded from, a shortlist in AI search has an outsized effect on pipeline, because each opportunity is worth far more than a typical consumer transaction.
Most buying decisions happen without a results click. A buyer can form a strong opinion about which vendors to trust without ever visiting your website. If the engine doesn’t mention you, you’re invisible at the exact moment the consideration set is taking shape, and standard web analytics won’t record the absence.
One thing that’s important to remember is that GEO is not a replacement for the SEO work you’re already doing. AI engines retrieve a large share of what they cite from conventional search results, so strong SEO foundations will feed directly into greater AI visibility. GEO simply extends that work into a new surface rather than starting from scratch.
How do AI search engines decide which B2B brands to cite?
AI search engines don’t rank ten blue links the way classic search does. AI tools like ChatGPT, Perplexity, Claude and others start by interpreting a query, conducting research around the topic, and then retrieve candidate sources, break those sources into passages to select the most relevant and trustworthy passages, and synthesise an answer – often citing a handful of sources along the way. Getting cited therefore depends on a number of factors but, in practice, a few do most of the work.
Machine-readable, structured content
Structured data (schema markup) helps engines understand exactly what your organisation is, what it offers, and how your content is organised. It turns ambiguous prose into verifiable facts an engine can lift with confidence.
Brand Authority
This is consistently the strongest single predictor of whether an AI engine cites a source. Established authority signals, such as quality backlinks, brand mentions across the web, and a recognisable entity, make an engine far more likely to surface you.
Content structure and specificity
Answer-first writing, question-led headings, short and scannable passages, and specific, entity-dense claims (real numbers, named tools, clear statements) are far easier for an engine to chunk and cite than long, vague introductions.
Crawl access
But none of the above matters if an AI engine physically can’t reach your site. If your server or robots rules block AI crawlers, your content cannot be crawled and your brand cannot cited.
As this list makes clear, technical elements such as crawlability and structured data make up some of the most important aspects of GEO visibility.
Are businesses ready for this new type of search? What the data says
We decided to measure it how many B2B brands have these foundations in place. To do this, we audited 50 B2B websites for the technical foundations that make a brand citable in AI search: structured data, crawl access, content structure and the emerging signals AI engines look for.
| What we measured | The finding |
| Have at least one type of rich result / structured data | 74% (26% have none at all) |
| Have more than one type of rich result | Only 33% |
| Have Organisation schema | Only 31% (69% don’t) |
| Have an llms.txt file | Only 27% (73% don’t) |
| Missing a readable H1 | 7% |
| Actively block AI crawler user agents | 10% |
The data tells the story: most B2B brands are only just covering the basics, while some brands are dangerously behind. Here’s a more detailed breakdown:
Structured data deployment is patchy at best
While 74% of the sites we audited had at least one type of rich result, only a third – 33% – had more than one type, and more than a quarter (26%) had none at all. More tellingly, only 31% had Organisation schema in place, meaning roughly seven in ten B2B sites give AI engines almost nothing machine-readable to verify who they are and what they do. Structured data is one of the clearest ways to tell an engine “this is the entity, these are the facts.” Most B2B brands aren’t sending that signal.
Almost nobody has adopted an llms.txt
Just 27% of sites had an llms.txt file, the emerging standard for telling AI crawlers what your site contains and how to use it. While it’s an early signal, it’s also a low-effort one and recently signalled by Google Lighthouse as an important factor. The fact that 73% haven’t adopted it makes it a genuine first-mover opportunity.
One in ten sites have locked themselves out entirely
10% of the sites we audited were actively blocking AI crawler user agents from accessing their content. In many cases this is unintentional, perhaps a default setting or an over-cautious rule, but the effect is the same: those brands cannot be cited in AI search at all, no matter how good their content is.
The basics still trip people up
7% of sites lacked a readable H1. That’s a fundamental content-structure failure that hurts both traditional SEO and the way AI engines parse and chunk a page to find citable passages.
What GEO strategies should B2B brands use to get cited?
Here are the levers that move the needle, ordered roughly by impact and ease. Several map directly to the gaps our audit exposed.
1. Confirm AI crawlers can actually reach you.
This is the most urgent fix, because it’s binary. Check your robots.txt and server rules for the major AI user agents, including GPTBot, ClaudeBot, PerplexityBot and Google-Extended, and make sure you’re not blocking them. If you’re in the 10% that are, nothing else you do matters until this is resolved.
2. Implement structured data.
Add the schema types that help engines verify and quote you: Organisation schema sitewide, Product or Service schema on your offering pages, FAQPage schema on relevant pages, and Article schema with a named author (Person) on your content. This directly addresses the biggest gap we found: the 69% with no Organisation schema and the 26% with no rich results at all.
3. Publish an llms.txt file.
It’s low-effort, lives at the root of your domain (/llms.txt), and tells AI crawlers what your site contains and which content matters most. With 73% of B2B sites yet to adopt it, this is an easy way to send a signal almost none of your competitors are sending.
4. Structure content answer-first.
Lead each section with the answer, use clear question-led headings, keep paragraphs short and scannable, and make sure every page has one readable H1. This is exactly how engines chunk a page and select passages to cite, and it fixes the kind of structural gap that left 7% of audited sites without a usable H1.
5. Write with specificity and named entities.
AI engines cite precise claims, not vague ones. Use real numbers, name the tools and methods you reference, and make clear, declarative statements. Entity-dense, specific content is far more likely to be lifted into an answer than general thought leadership.
6. Build third-party validation.
In B2B, independent proof carries disproportionate weight. Claim and optimise your profiles on G2, Capterra and Trustpilot, pursue inclusion in independent “best B2B [category]” listicles, and invest in digital PR and expert authorship. These off-site signals are among the strongest drivers of whether an engine decides your brand is worth mentioning.
7. Measure your AI visibility.
You can’t improve what you don’t track. Monitor your share of voice in AI answers, watch for referral traffic from AI assistants in GA4, and use a citation-tracking tool to see which queries surface your brand and which surface competitors. Treat it as an ongoing programme, not a one-off fix.
Find out how ready your brand is for AI search
We audited 50 B2B websites and found most aren’t ready to be cited in AI search. If you’d like to know exactly where your brand stands, and what to fix first, POLARIS offers GEO and AI search services built for B2B. Get in touch with our experts to get started.
Frequently asked questions about GEO for B2B
Is GEO the same as SEO?
No. SEO optimises your visibility in traditional search results pages, where the goal is a clickable ranking. GEO optimises your visibility inside AI-generated answers, where the goal is to be the source an engine cites. They share foundations, but the objective and the tactics differ.
Which AI search engines matter most for B2B?
ChatGPT, Google’s AI Overviews and AI Mode, Perplexity, Gemini and Microsoft Copilot are the priorities. Copilot is worth particular attention in B2B given how many buyers work inside the Microsoft ecosystem. The most reliable approach is to optimise for the signals these engines share rather than chasing any single one.
How do I know if AI search engines are citing my brand?
We use a three-method test to get a grasp on AI visibility. First, run your key buyer questions through the major engines and record where you appear, watch GA4 for referral traffic from AI assistants, and use a dedicated AI-visibility or citation-tracking tool to monitor share of voice against competitors over time.
