B2B brands are learning that showing up in AI-generated answers is only part of the challenge. AI systems also shape how vendors are framed, compared, and recommended during the buying process.
That distinction matters because more software buyers are now turning to AI tools before they consult analyst reports or search engines. According to a March 2026 G2 survey of more than 1,000 B2B software buyers, 71% use AI chatbots to research vendors, and more than half begin their buying process with an AI query.
Brands appear in these responses when AI systems can confidently interpret, verify, and position them against competing vendors.
B2B buying is a group activity that involves many decision-makers, each entering the process with their own independent research. However, a growing share of buying comparisons now takes place within an AI tool before anyone sits down to compare notes.
Research from Magenta Associates found that just five brands capture 80% of the top AI-generated responses in any given B2B category. Ranking on the first page of Google once meant competing for 10 blue links. AI-generated answers often surface just four to seven brands.
AI tools generate these shortlists using systems that weigh source authority, entity clarity, and consistency across the web. Brands need to optimize for those signals, or they won’t make the AI list, even if they’ve secured strong press wins.
The way forward is to adopt a dual-path PR strategy and track decision outcomes to earn influence in an AI-mediated buying environment.
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How dual-path PR works
Think of dual-path PR like a resume that has to go through an applicant tracking system. A hiring manager needs to see a resume with a narrative, personality, and a clear structure. The tracking system needs to read structured formatting, the right keywords in the right fields, and consistent information that matches across platforms.
A beautifully written resume that can’t make it through the tracking system won’t reach the hiring manager. The same applies to AI systems. If they can’t parse, cite, or connect your brand to a clear entity, you won’t reach buyers.
The first path PR manages is earned media, analyst coverage, trade placements, bylines, and broader brand marketing visibility — these reach buyers directly and build credibility over time. Working alongside that is a second path built around structured content, distributed presence, and consistent entity signals — AI systems use these to decide whether a brand is trustworthy enough to surface and recommend.
Both paths draw on the same PR activity, but the architectures required for each differ substantially.
Track what AI surfaces
Brands can surface in an AI answer as a historical reference, a minor entry in a comparison list, as a counterpoint to another vendor’s positioning, and more. New tools can track whether a brand appears in responses that shape purchasing decisions. These include queries to narrow a vendor field or draft a shortlist for internal review.
These tools measure decision outcomes by mapping a brand’s presence across queries that carry buying intent. They also track AI perception — how an AI system characterizes a brand’s positioning and category authority and how frequently the brand appears in results.
A brand might surface consistently in AI-generated answers, but is described in a way that undercuts its actual positioning. For example, it may be categorized incorrectly in a vertical, such as being labeled a small-business tool when it actually serves enterprise accounts, or framed as a secondary option compared to a competitor.
Decision outcome tracking surfaces misalignments so brands can refine how AI systems interpret and position them.
Use a dual-path PR strategy to gain visibility
The earned media model still works, so you don’t have to throw out your PR playbook just yet. Coverage that generates backlinks, supports broader marketing visibility, signals expertise across authoritative domains, and establishes consistent entity relationships will still reach human buyers.
Buyers are still researching vendors across search engines, AI tools, analyst content, and industry publications. Brands that can influence both traditional discovery and AI-generated recommendations will have a stronger position throughout the buying journey.
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