Your Buyers Already Asked an AI About You.
Do You Know What It Said?

A buyer evaluating your category opened a chatbot last week, typed in their problem, and read back a list of three vendors. Maybe you were on it. Maybe a competitor was, described in flattering detail while your name never came up. Maybe the AI mentioned you but got your product wrong, placed you in the wrong category, or quoted positioning you abandoned eighteen months ago.

You will probably never know which of those happened. That is the problem Compass's 2026 GEO and AI Visibility Survey of 150 U.S. B2B tech marketers puts numbers to. The numbers are not comfortable.

"Providers need to evolve from driving traffic through search engine optimization to driving visibility through answer engine optimization." — Forrester, B2B Buyers Make Zero-Click Buying Number One

The boardroom noticed before the marketing team got ready

Buyers are already using AI as a vendor-research layer. Responsive's 2025 Inside the Buyer's Mind study found that two-thirds of B2B buyers rely on AI chatbots as much as or more than Google or Bing when evaluating vendors; in technology and software the share reached 80 percent.^[1] Forrester's 2026 business-buying research found that 94 percent of B2B buyers use AI during the purchase process and named generative AI or conversational search as a more meaningful information source than any other option.^[2]

Boards and CEOs have caught on. In Compass's survey, 88 percent of senior marketing leaders said leadership or the board had asked what they were doing to show up in AI answers.^[3]

That question lands on teams that mostly cannot answer it. Across all marketers, 34 percent said they had a defined strategy and felt prepared to shape how AI engines describe and recommend their brand. Another 43 percent were running informal efforts with no real plan. Even among CMOs and VPs, only 52 percent claimed a defined approach.

Marketers can feel the shift, even if they cannot act on it

Ask these teams what matters most in 2026 and brand awareness tops the Compass list at 44 percent, ahead of lead generation. That would have sounded strange a few years ago. It makes sense in an AI-mediated buying journey.

When a buyer asks a model which vendor to consider, the model pulls from years of accumulated signals: editorial coverage in trusted outlets, analyst citations, thought leadership, clear entity data, and a brand that shows up consistently across the places it reads. A company with thin coverage gives the model little to work with.

Muck Rack's May 2026 What Is AI Reading? study makes the mechanism visible: after analyzing more than 25 million links cited by ChatGPT, Claude, and Gemini, it found that earned media accounted for 84 percent of AI citations, while paid and advertorial content accounted for just 0.3 percent.^[4]

"About 84% of citations come from earned media." — Muck Rack, What Is AI Reading? May 2026

Most teams are flying without a map

Half the marketers surveyed by Compass pointed to limited internal GEO expertise as their biggest obstacle. Four in ten cited poor coordination across content, PR, and web teams. About a third struggled to measure results.

Centerfield's 2025 Gen-AI Search Readiness Survey found that 63 percent of marketers were not investing time, budget, or staff in GEO, and that only about one-third reported good or expert understanding of GEO compared with 72 percent for SEO.^[5]

The knowledge gaps are sharp. Only 36 percent of Compass respondents knew which content pieces — theirs or a competitor's — AI engines cite in their market. Just 26 percent knew which outlets those engines crawl. Fewer than three in ten actively tracked their AI visibility at all.

The ownership question reveals the confusion. Asked who should run GEO internally, 47 percent picked digital marketing and SEO. Only 17 percent named PR and communications. That instinct treats AI visibility as a technical tuning job, when the evidence increasingly points to brand authority, third-party validation, and credible mentions as core inputs.

Ahrefs' 75,000-brand study found that branded web mentions had the strongest relationship with AI Overview visibility among the factors it tested — much stronger than backlinks.^[6] Stacker and Scrunch found that distributing content through earned-media channels produced a 239 percent median lift in AI search visibility in a 30-day study.^[7]

Leaders think their teams are further along than they are

The Compass survey split senior leaders from the directors and managers who do the daily work — and the two groups described different companies.

Among CMOs and VPs, 59 percent said they felt very confident in their PR and content strategy and its effect on AI visibility. Among the practitioners executing that strategy, 37 percent agreed. Senior leaders were roughly twice as likely as their teams to say the company knows which channels influence models, which outlets the engines crawl, and which third-party sources those engines trust.

That matters because the market is moving fast. Walker Sands' 2026 B2B AI Search Visibility Benchmark analyzed nearly 45 million relevant search keywords across 828 enterprise B2B companies and found that AI Overviews appeared on nearly half of the relevant results pages where those brands ranked. But the typical enterprise B2B brand was cited in only a small share of relevant AI-generated answers.^[8]

"Ranking breadth alone doesn't predict citation inclusion." — John Fairley, SVP at Walker Sands

The AI is also getting your story wrong

Discoverability gets most of the attention. There is a quieter risk that hits just as hard. Nearly three-quarters of Compass respondents had watched an AI tool describe their company, category, or value proposition in ways that were wrong, stale, or incomplete.

Gartner's 2026 B2B buyer survey found that 45 percent of buyers used GenAI in a recent purchase, primarily to gather information on vendors and products — while 69 percent preferred to validate AI-generated insights with sales reps.^[9] A buyer who gets a wrong answer about you may decide you're not a fit and never visit your site to find out otherwise. You lose the deal before you know there was one.

The Tow Center for Digital Journalism tested eight AI search engines across 1,600 queries and found that the systems failed to retrieve correct information more than 60 percent of the time.^[10] Brands going through a pivot or a category-creation push face the sharpest version of this: the signals the models learned from may describe a company that no longer exists.

What separates the teams seeing results

AI visibility is already producing pipeline for the companies that took it seriously. In the Compass survey, 40 percent of marketers reported that visibility in AI search and chatbots lifted qualified inbound pipeline by 5 to 10 percent over the past year. Another 19 percent saw growth above 10 percent. Nearly six in ten reported measurable impact.

Strategy sorts the two groups cleanly. Of the marketers reporting flat or declining pipeline, 6 percent had a defined plan. Of those seeing growth, 53 percent did. Among the no-growth companies, 38 percent described themselves as still dabbling. Among the growth group, 7 percent did. And among the pipeline-growth group, 55 percent knew which channels carried the most influence over models in their market. Among companies seeing no impact, 15 percent did.

Seer Interactive reported that AI-referral traffic converted at higher rates than Google organic traffic in a B2B SaaS case study — while noting that absolute volume is still much smaller than organic search.^[11]

Your agency might be the bottleneck

If you outsource PR, this part deserves a hard look. Only 37 percent of Compass respondents said their agency was prioritizing AI visibility and building it into strategy. Forty-five percent said the agency had raised the topic and was trying but lacked the expertise to make a difference. Among companies not seeing pipeline growth, half described their agency exactly that way.

Muck Rack found that only 2 percent of the journalists PR teams pitch overlapped with the journalists most cited by AI engines — a painful mismatch for teams that still measure media relations only by human readership or domain authority.^[12]

Spend that flows to an agency that cannot tell you which publications the engines crawl, which journalists cover the topics models prioritize, or how to engineer coverage that builds authority is spend that gets your name in front of human readers while doing little for how machines understand you.

Where to start this quarter

Run your own audit first. Type your company name, your category, and your main differentiators into the major chatbots and write down what comes back. If the answers are wrong, treat that as a live pipeline risk, not a curiosity.

Then commit to a strategy built on your specific market rather than generic best practices. Learn which channels and sources actually move the models in your space. Put PR and thought leadership at the centre of the plan instead of the edges. Set up shared accountability across content, PR, SEO, and web so they work from one playbook and one set of metrics.

Your buyers are already asking AI which vendor to pick. The teams pulling pipeline out of that moment are not lucky. They mapped the territory, fixed what the models got wrong, and built authority in the places those models trust. The ones still waiting are handing the recommendation to whoever did the work.