How B2B Buyers Use AI When Researching Vendors

The AI buyer journey data is better than most marketing teams realize, and what it shows changes the brief for how brands need to be present. The question is not whether B2B buyers use AI in their research. The data settles that. The question is where in the purchasing process AI appears, and what kinds of brand presence it rewards.

Key takeaways

• Forrester's 2025 research finds 90% of B2B organizations already use generative AI in their purchasing process. B2B buyers are adopting AI search at three times the consumer rate.
• AI is most used in two buying stages: early discovery ("what kind of solution do I need?") and shortlist evaluation ("which vendors should I consider?"). Both stages precede the first sales contact.
• Brands that appear only in branded queries miss the discovery stage entirely. Category-level and informational queries are where AI visibility has the most leverage in B2B.
• The GEO priority order for B2B: own the category definition first, build evaluation-stage third-party coverage second, monitor branded queries third.

Where AI fits in the B2B buying journey

The traditional B2B buying model assumed a long, sales-rep-mediated process that began with an outbound touch or inbound inquiry. That model increasingly misrepresents how enterprise and mid-market decisions start.

A large fraction of the pre-purchase research phase, particularly the initial exploration and vendor identification steps, now happens without any contact with a sales team. Buyers arrive at the first sales conversation with a shortlist already formed. The question is how that shortlist was built.

Forrester's 2025 research found that B2B buyers use AI primarily for two activities: understanding what category of solution addresses their problem, and building a preliminary list of vendors to evaluate. Both activities typically happen before any direct vendor engagement.

For brands not appearing in AI answers to these early-stage queries, the practical effect is that they are not on the shortlist before the sales conversation begins. Being better on the call does not recover from not being invited to it.

The discovery stage: category queries dominate

The discovery stage query pattern looks different from what most B2B marketing teams optimize for. Buyers at this stage are not searching for brand names. They are asking category and problem-framing questions: "what tools handle competitive intelligence at scale?", "how do enterprise teams monitor brand mentions?", "what is the best approach for tracking AI search visibility?"

These are the queries where AI visibility has the most leverage. A brand that appears consistently in answers to category questions earns a place in the buyer's frame of reference before the buyer has formed preferences. A brand that does not appear at this stage has to overcome a shortlist disadvantage in every subsequent conversation.

The implication for GEO content strategy is direct: prioritize category-level, informational queries over branded or bottom-of-funnel comparison queries. The highest-leverage queries are the ones that shape the buyer's understanding of the category itself.

The evaluation stage: comparison and validation queries

Once a buyer has a preliminary shortlist, the query pattern shifts to evaluation: "how does [Brand A] compare to [Brand B]?", "does [Brand] work for agencies managing ten or more clients?", "what do analysts say about [Brand]?"

AI engines are heavily used for evaluation queries because they synthesize across multiple sources quickly. A buyer asking Perplexity to compare three vendors is effectively asking it to read and synthesize dozens of review articles, analyst summaries, and documentation pages in seconds.

Brand performance in evaluation queries depends on a different set of signals than discovery query performance. Third-party validation matters most here: analyst coverage, review site depth, case study specificity, and press mentions that confirm particular use cases. Brands with strong self-published content but weak third-party validation underperform in evaluation queries even when their SEO is solid.

Why B2B is ahead of consumer on AI adoption

The Forrester finding that B2B buyers adopt AI search at three times the consumer rate is not intuitive, but it makes sense on reflection. B2B purchasing decisions are research-intensive by nature. They involve more stakeholders, more due diligence, and more written documentation than consumer decisions. AI tools that accelerate research, summarize options, and synthesize comparisons map directly onto the existing B2B research workflow.

Consumer buyers are more likely to transact directly from a Google result or a social recommendation. B2B buyers were already doing extensive pre-purchase research. AI just makes that research faster and more thorough.

The practical implication: B2B marketing teams should assume AI is already a significant input to their buyers' discovery process, not something to prepare for in the future.

The GEO priority order for B2B

Most B2B GEO strategies default to optimizing for branded queries because those are the easiest wins to show internally. The data suggests a different priority order.

First, own the category definition. The brand that the AI engine uses as its reference explanation of the category has a structural advantage across every discovery query. This is typically earned through the most authoritative guide to the category, comprehensive coverage of category sub-topics, and entity signals that place the brand at the center of the category's knowledge graph.

Second, build evaluation-stage third-party coverage. Analyst mentions, G2 reviews that name specific use cases, and press coverage that validates particular applications are the citation sources AI engines draw on for evaluation queries. These take time to build but have long shelf lives.

Third, monitor branded queries as a baseline. How the brand appears when its own name is used in AI queries matters, but it is the least leveraged GEO activity for B2B teams at the growth stage.

For teams building the internal case for GEO investment, the CMO's guide to justifying AI visibility spend covers the frameworks that land with finance and leadership.