FROM THE INDUSTRY
If the teams responsible for telling the company’s story are not working from a shared narrative, the market receives conflicting signals.
The most useful thing AI has done for communications strategy is to make a long-standing gap visible. For decades, B2B companies have crafted messaging, built websites, and run PR campaigns designed to shape how the market perceives them. Yet the same fundamental question remained difficult to answer: How does the market perceive us? Companies could piece together part of the answer through analyst input, win/ loss interviews, customer research, and sales feedback. But the process was time-consuming, expensive, and ultimately incomplete. AI now offers a practical way to inspect the gap between how a company wants to be understood and how public information represents it, making that gap easier to close through messaging, content, and media strategy. Ask any major AI tool for a list of vendors, a market category, or the problem a potential customer is trying to solve. The response offers a useful snapshot of how a company is represented across the sources the system synthesises. Sometimes the results align with the company’s intended positioning. Often, they do not. A company may be missing from relevant conversations, associated with outdated strengths, or framed more narrowly than it sees itself. That matters beyond internal analysis. The same AI-generated narrative is increasingly shaping how prospective buyers discover, compare, and evaluate vendors. In a March 2026 survey of 1,076 B2B software buyers, G2 found that 51% began their research with an AI chatbot, nearly 70% choose a different vendor, based on AI guidance, than they initially planned, and one in three purchased from a vendor they had never heard of before. What Changed, and What Didn’t AI-powered search tools like ChatGPT, Google Gemini, Claude, and Perplexity do more than return a list of links. They synthesise information into an answer. When a buyer asks who the credible vendors are in a given market, the response reflects the patterns, sources, and authority signals the AI system weighs when generating its answer.
The comparison to SEO is intuitive, and some of it holds up. Companies can test AI discoverability by running relevant queries and seeing whether they surface. But AI-visible authority is not built through optimisation alone; it depends on sustained presence in credible, independent sources and content substantial enough to be cited, compared, and trusted. The shift also gives renewed value to substantive material. White papers, technical reports, detailed case studies, and well-supported thought leadership can provide the factual structure AI systems draw on. In an environment built around summarised answers, clarity, specificity, sourcing, and depth matter more than short-form volume.
The Common Misalignment
Ask most B2B technology companies how they are approaching AI discoverability and they will describe separate initiatives: someone handling SEO, a content team, a public relations agency managing earned media, and increasingly, someone assigned specifically to GEO. The structure may make sense internally, but it breaks down in how companies are represented externally. AI systems synthesise across all of it, drawing on what independent sources say about the company over time. When earned media positions a company one way while its thought leadership suggests another, buyers don’t see separate programmes. They encounter a fragmented narrative. A company may be known for one narrow capability in editorial coverage, promote a broader platform story on its website, and describe something different again in executive commentary. AI can reflect those inconsistencies when buyers ask who the credible vendors are and what each one does. If the teams responsible for telling the company’s story are not working from a shared narrative, the market receives conflicting signals. AI makes that disconnect easier to see and more consequential. Buyers increasingly encounter the resulting narrative while researching options, often before they visit a vendor website or speak with a sales team. The programmes that build AI-visible authority need to operate as one coordinated communications strategy, not as a collection of separate initiatives.
Volume 48 No.23 SEPTEMBER 2026
59
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