The data on how B2B buyers use AI is better than most marketing teams realize, and it changes the brief. Whether B2B buyers use AI in their research is settled.
The open 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 matters most 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 does AI fit in the B2B buying journey?
AI shows up at two stages of the B2B buying journey, both before a buyer talks to sales. In early discovery, buyers ask what kind of solution they need. In shortlist evaluation, they decide which vendors to consider. Forrester's 2025 research found 90% of B2B organizations already use generative AI in this process.
The old B2B buying model assumed a long process run by a sales rep, starting with an outbound touch or an inbound inquiry. That is less and less how enterprise and mid-market decisions start.
Much of the research before a purchase, above all the first look around and the search for vendors, now happens with no sales contact at all. 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 mainly for two jobs: working out what kind of solution fits their problem, and building a first list of vendors. Both happen before they talk to any vendor.
A brand missing from AI answers at this early stage is not on the shortlist when the sales conversation begins. Being better on the call does not recover from not being invited to it.
What happens in the discovery stage?
In the discovery stage, buyers ask about the category and the problem, not about brands. Brands that show up in these answers again and again enter the buyer's thinking before preferences form.
These questions look different from what most B2B marketing teams plan for. Buyers are not searching for brand names. They ask questions like: "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 matters most. A brand that keeps showing up in category answers is in the buyer's mind before preferences form. A brand that is missing here starts every later conversation behind.
For GEO content, the lesson is direct: put category and how-to queries ahead of branded or late-stage comparison queries. The queries that matter most shape how the buyer sees the category itself.
What happens in the evaluation stage?
In the evaluation stage, buyers ask comparison and validation questions once a shortlist exists, such as how two vendors compare or what analysts say about a brand. G2's 2026 research found 51% used AI to assess total cost of ownership, 51% to build a shortlist, and 46% to evaluate shortlisted vendors.
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 10 or more clients?", "what do analysts say about [Brand]?"
Buyers lean on AI engines for evaluation because the engines pull many sources together fast. A buyer who asks Perplexity to compare three vendors is asking it to read dozens of reviews, analyst notes, and help pages in seconds.
G2's own 2026 research on B2B software buyers puts numbers on the evaluation stage specifically (G2, 2026):
| Evaluation activity | Share using AI |
|---|---|
| Assess total cost of ownership | 51% |
| Build a shortlist | 51% |
| Evaluate shortlisted vendors | 46% |
The same research found review sites had just overtaken AI chatbots as the single top source shaping a buyer's shortlist:
| Top source shaping the shortlist | Share |
|---|---|
| Review sites | 38% |
| AI chatbots | 37% |
Third-party validation and AI visibility both matter; neither replaces the other.
Evaluation answers depend on different signals than discovery answers. Outside proof matters most here: analyst coverage, deep review profiles, specific case studies, and press that confirms use cases. Brands with strong content of their own but little outside proof do worse here, even with solid SEO.
Why is B2B ahead of consumer on AI adoption?
B2B buyers adopt AI search at three times the consumer rate because B2B buying runs on research. AI tools that speed up research and sum up comparisons fit work B2B buyers already did.
The Forrester finding is not obvious, but it makes sense. B2B purchases involve more people, more checks, and more written documents than consumer ones.
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.
What is the GEO priority order for B2B?
The GEO priority order for B2B runs category first, evaluation second, and branded third. Own the category definition first. Then build outside coverage for the evaluation stage, and watch branded queries as a baseline.
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.
| Priority | Focus | Why it matters |
|---|---|---|
| First | Own the category definition | The brand the engine uses to explain the category gains an edge on every discovery query, usually earned with the best category guide, full coverage of sub-topics, and clear entity signals |
| Second | Build evaluation-stage third-party coverage | Analyst mentions, G2 reviews that describe use cases, and press coverage are what engines cite for evaluation queries; they take time to build but last |
| Third | Monitor branded queries as a baseline | Branded answers matter, but they are the weakest use of GEO effort 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.
The wider public data on AI search adoption is collected in the state of AI search, mid-2026.
Zumi is an AI Search Intelligence Platform built to track exactly this priority order: mention rate, share of voice, average position, and citation share, each measured on its own for the category and evaluation queries that shape a B2B shortlist. Book a demo to see the discovery-to-evaluation breakdown for a real category.