A survey of more than 600 United States business professionals, released by Semrush in mid-July 2026, found that only 7% of B2B buyers say brand recognition determines whether they notice a vendor named in an AI-generated response. What drives attention instead is how precisely a vendor matches the buyer's stated use case, a shift that reorders long-standing assumptions about the commercial value of a well-known name.

The finding sits at the center of a study titled "How AI tools shape the B2B buying process," which Semrush conducted across March and April 2026. The research reached 643 respondents, removed 21 who failed a quality check, and based its published figures on the 519 who confirmed they use AI tools for work. That subset represents 83% of the valid sample. The company shared the report with press contacts on July 14, 2026.

Semrush operates as part of Adobe following a $1.9 billion all-cash acquisition. Adobe agreed to buy the search visibility platform at $12 per share on November 19, 2025, a transaction the company framed around helping brands manage visibility across large language models and traditional search engines at the same time. The B2B buying study is one of a series of research outputs published under that combined ownership.

What the survey measured

The sample skews toward decision-making authority. According to Semrush, 54% of respondents are final decision-makers, 41% form part of a decision-making group, and 5% act as evaluators or influencers. Company size varied: 24% work at organizations of up to 50 employees, 22% at firms of 51 to 200, 29% at 201 to 1,000, 15% at 1,001 to 5,000, and 10% at 5,001 or more. Technology and SaaS accounted for the largest industry share at 20%, followed by manufacturing at 15%, professional services at 14%, and e-commerce and retail at 13%.

Roles represented in the survey span business executives, chief executives, business owners and founders, product managers, marketing directors, operations managers, IT managers, chief financial officers, chief information and technology officers, and procurement managers. The breadth matters because it places AI use across the functions that typically sit inside a B2B buying committee rather than in a single department.

Daily use, not experimentation

The headline usage figure is 84%. That share of professionals surveyed use AI tools for work, and among them, 69% do so daily. A further reading shows 95% using the tools at least once a week. Semrush frames this as habitual rather than exploratory behavior, comparing the act of reaching for AI to opening a browser or checking email.

The functional spread is wide. Researching topics or trends leads at 72%, writing or editing content follows at 63%, and data analysis or summarization sits at 60%. Researching products and services registers at 54%, learning or upskilling at 52%, and brainstorming at 51%. Automating tasks accounts for 41%, while only 14% describe themselves as still testing what the tools can do.

That habit carries directly into purchasing. According to Semrush, 66% of respondents regularly use AI specifically to research products, vendors, or solutions for their job, and another 29% do so occasionally. The vendor-research pattern, in the company's framing, has already settled into routine.

AI appears at every purchase stage

The study rejects the idea that AI functions only as a top-of-funnel discovery tool. Buyers pull it into the process throughout. Early research, scoping the category, or defining requirements draws 72% usage. Actively comparing vendors sits at 62%. Narrowing the shortlist accounts for 48%, and supporting the final decision reaches 45%. Post-purchase evaluation registers at 29%, while just 2% report not using AI in the process at all.

When buyers turn to AI for vendor research specifically, the tasks are substantive. Exploring possible solutions leads at 66%, comparing vendors directly follows at 61%, and understanding a problem or category more deeply sits at 59%. Summarizing options accounts for 55%, and asking for recommendations reaches 53%. Identifying pros and cons registers at 41%.

The pattern of AI arriving before a buyer visits a company website echoes a structural argument PPC Land has tracked across multiple studies. Research covered in March 2026 documented how most B2B marketers cannot prove AI's role in their pipeline, with buyers using ChatGPT, Gemini, Microsoft Copilot, and Perplexity to define categories and shape shortlists before generating a single trackable visit. The Semrush data quantifies how deep that upstream influence now runs.

The impact on final decisions

Semrush measured AI influence across three distinct points in the funnel. On discovery, 97% say AI has helped them find new vendors, and 44% say this happens frequently. On shortlisting, 92% say AI has shaped their vendor shortlist, with 45% describing that influence as significant. On the final choice, 83% say AI influenced their vendor decision, and 32% say it carried major influence.

Buyers are not blind to the technology's limits. According to Semrush, 66% say they have spotted vendors absent from AI results, and 26% report this happening frequently. That awareness of blind spots runs alongside the trust figures rather than against them, suggesting buyers treat AI output as a strong signal that still requires checking.

Budgets on the table

The purchases these buyers research are not trivial. Semrush found that 43% typically evaluate purchases between $1,000 and $10,000, and 42% evaluate purchases between $10,000 and $100,000. A further 14% operate in enterprise territory above $100,000. Taken together, 84% of respondents use AI to inform purchases of $1,000 or more, decisions the company characterizes as deliberate and multi-stakeholder with real budget consequences.

The categories being researched span the full B2B landscape. Agencies and service providers top the list at 51%, followed by SaaS and software tools at 46%, marketing tools at 45%, infrastructure and technical tools at 44%, and enterprise platforms at 43%. B2B financial and legal services appear in 25% of cases.

Adoption is uneven inside buying teams, however. Only 39% say most stakeholders in their company actively use AI during vendor research, while 52% describe adoption as mixed. Semrush notes that this creates information asymmetry within committees: the person who discovered a vendor through AI may not be the final decision-maker, and colleagues may be working from different information.

Two platforms dominate, but buyers move between many

ChatGPT remains the most-used tool, with 76% of respondents using it for work and 71% for product research. Google Gemini follows at 62% for work and 61% for product research. Microsoft Copilot reaches 53% and 45%. Meta AI ranks fourth at 31% for work and 24% for product research, a level Semrush attributes partly to its integration into Facebook and WhatsApp. Perplexity registers 22% for work and 18% for product research, Claude 20% and 14%, and Grok trails at 13%.

The relative standing of these platforms tracks a competitive picture PPC Land has documented in detail. Similarweb data covered in June 2026 showed ChatGPT's worldwide traffic share falling to 52.7% while Gemini climbed to 27.3% and Claude tripled to 8.9% over twelve months. Earlier tracking recorded ChatGPT holding two-thirds of United States chatbot traffic in late 2025 before that erosion accelerated. Gemini, meanwhile, reached 900 million users as it narrowed the gap. According to Semrush, the practical takeaway is that cross-platform visibility now matters more than performance in any single engine, because buyers increasingly consult several tools within one decision.

Fit beats familiarity and position

The study's most direct challenge to conventional marketing wisdom concerns what makes a vendor stand out when AI returns several names. Close matching of the buyer's specific use case leads at 53%. A clear and detailed description follows at 50%. Highlighting clear benefits or outcomes sits at 38%. Appearing early or being mentioned first registers at only 36%, and brand recognition trails at 7%.

That 7% figure carries weight for smaller and lesser-known vendors. According to Semrush, a vendor with a precise, use-case-specific presence in AI can outperform a better-known competitor, which the company frames as a leveling of the playing field. The finding aligns with earlier measurement work showing how narrow the top of the visibility funnel has become: a Semrush analysis of 126 million United States AI search prompts found that only 36 of more than 1,200 tracked brands held consistent visibility across every platform studied, with a far larger share vanishing from at least one engine's citations.

Buyer prompting behavior reinforces the fit argument. According to Semrush, 61% describe their specific use case or problem when researching vendors in AI, 56% ask for direct vendor comparisons, 45% include constraints such as budget, required features, or compatibility, and 43% refine their query through follow-up questions.

What buyers say AI gets wrong

The frustrations respondents report map onto the same theme from the other direction. The top complaint, cited by 33%, is that AI recommendations are too generic for their specific use case. Responses lacking depth or accuracy follow at 28%. A further 27% say recommendations do not reflect real pricing or contract structures, and another 27% flag credibility concerns. A quarter, 25%, say AI missed vendors they knew were relevant, while 30% report no major issues.

Semrush characterizes each frustration as a gap a vendor can close through use-case pages, documented outcomes, accurate pricing signals, and third-party coverage. The consistency-and-credibility dynamic behind AI citations has been examined before. Research Semrush published in June 2026 found that AI search tools cite sources based on consistency and credibility signals across trusted platforms rather than the raw authority of any single large publication.

Trust, then verification

B2B buyers extend meaningful trust to AI recommendations without treating them as final. According to Semrush, 75% fully or mostly trust AI vendor recommendations, split between 30% who trust them fully and 45% who mostly do. Neutral respondents account for 22%, and only 3% express low trust.

An AI recommendation typically triggers a more focused investigation rather than ending it. When AI mentions a vendor, 71% visit that vendor's website, 63% search for the company on Google, 46% compare the recommendation against alternatives, 41% return to the AI with follow-up questions, 38% check reviews on G2 or similar platforms, and 14% ask colleagues. Alongside AI, 75% still use Google or other search engines as part of their vendor research.

The sequence of channels has shifted. According to Semrush, 41% now start with AI and validate via search, 35% start with search and turn to AI for synthesis or comparison, and 20% switch between both throughout. The company frames the combined behavior as AI narrowing the field while search validates the answer, which means a vendor with strong AI visibility but a weak website, poor reviews, or limited search presence can lose the buyer at the very next step.

Why the marketing community should care

The commercial stakes attach to the shortlist. If AI shapes which vendors a buyer considers before any salesperson is aware the opportunity exists, absence from AI answers translates into pipeline that never forms. This is the argument the report's PR outreach emphasized, and it aligns with a pattern PPC Land has documented across the broader answer-engine category. HubSpot data covered in June 2026 showed AI search overtaking product demos as a driver of CRM purchase intent, alongside a 27% organic traffic decline across nearly 300,000 of the company's customers.

The response from vendors has been measurable spending. Research covered in May 2026 found AI search pushing 44.8% of brands to increase PR investment as third-party content influence on LLM answers became quantifiable. A parallel wave of tooling has followed, including HubSpot's answer engine optimization product priced at $50 per month. Semrush itself sits inside that market, and the report closes by pointing readers to its own AI visibility tracking, a commercial interest worth noting when weighing the survey's framing.

The survey is the work of an interested party. Semrush sells AI visibility products, and the study's recommendations point toward the behaviors those products support. The underlying figures, however, are specific and drawn from a defined sample of 519 respondents, which places them among the more granular datasets on B2B buyer behavior in AI published to date. Looking forward, 89% of respondents expect to rely on AI more for work decisions, with 45% expecting to do so significantly and fewer than 1% expecting to use it less. On the study's own evidence, the behaviors it documents are set to deepen rather than reverse.

Timeline

Summary

Who: Semrush, the search and generative engine optimization platform acquired by Adobe in November 2025, conducted the research among 519 United States B2B professionals who use AI tools for work.

What: A survey titled "How AI tools shape the B2B buying process" found that AI shaped 92% of respondents' vendor shortlists and influenced 83% of final decisions, while only 7% said brand recognition determined whether they noticed a vendor in an AI response. Use-case fit led at 53%.

When: Semrush fielded the survey across March and April 2026 and shared the report with press contacts on July 14, 2026.

Where: The study covers United States B2B professionals across technology, manufacturing, professional services, e-commerce, finance, healthcare, and marketing, spanning companies from fewer than 50 to more than 5,001 employees.

Why: The findings matter because AI increasingly determines which vendors reach a buyer's shortlist before a sales team is aware of the opportunity, with 84% of respondents using AI to research purchases of $1,000 or more and 14% on deals above $100,000. Absence from AI answers can remove a vendor from consideration entirely, though the survey is the work of a company that sells AI visibility tools.