B2B brands are learning that evolving from AI-generated responses is part of the challenge. AI systems are also reshaping the way sellers are ranked, compared, and recommended during the buying process.
That distinction is important because many 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 start their buying process with an AI question.
Brands emerge from these responses that AI systems can confidently interpret, validate, and position against competing vendors.
B2B purchasing is a team effort involving multiple decision makers, each entering the process with their own independent research. However, a growing share of comparison shopping now happens 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 B2B category. Ranking on the first page of Google once meant competing for 10 green links. AI-generated responses typically only appear in four to seven products.
AI tools make this short list using resource-weighted systems, business transparency, and consistency across the web. Brands need to work on those signals, or they won’t make the AI list, even if they get a solid media win.
The way forward is to use a two-pronged PR strategy and track the results of decisions to influence the AI buying environment.
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How dual-path PR works
Think of a two-way PR as a continuum that must go through the applicant tracking process. The hiring manager needs to see continuity and narrative, personality, and a clear structure. A tracking system needs to learn systematic formatting, the right keywords in the right fields, and consistent information across platforms.
A well-written CV that can’t get through the tracking system will never get through to the hiring manager. The same applies to AI systems. If they can’t parse, cite, or connect your product to a clear business, you won’t reach buyers.
The first way PR manages earned media, analyst exposure, sales of merchandise, lines, and broader brand marketing visibility – this reaches consumers directly and builds loyalty over time. Working alongside that is a second approach built between curated content, distributed presence, and consistent business signals – AI systems use this to determine if a product is trustworthy enough to appear and recommend.
Both methods draw on the same PR function, but the structures required for each are very different.
Track where the AI is coming from
Brands can appear in the AI response as a historical indicator, a small entry in a comparison list, as a counterpoint to another retailer’s position, and so on. New tools can track whether a product is appearing in responses that shape purchasing decisions. This includes questions to narrow down the vendor field or prepare a short list for internal review.
These tools measure decision outcomes by mapping product presence to all questions that contain purchase intent. They also track AI perception – how the AI system reflects the product’s position and category authority and how often the product appears in the results.
A symbol may appear consistently in AI-generated responses, but it is interpreted in a way that minimizes its true meaning. For example, it may be misaligned vertically, such as being labeled as a small business tool when it actually serves business accounts, or positioned as a secondary option compared to a competitor.
Tracking of decision results reveals inconsistencies so brands can adjust how AI systems interpret and position them.
Use a two-pronged PR strategy to gain visibility
The earned media model still works, so you shouldn’t throw away your PR playbook just yet. Installations that generate backlinks, support wider marketing visibility, demonstrate expertise across authoritative domains, and establish mutually beneficial business relationships yet to reach human buyers.
Consumers are still researching vendors across search engines, AI tools, analyst content, and industry publications. Brands that can leverage both traditional discovery and AI-generated recommendations will have a strong position throughout the shopping journey.
