Do B2B buyers trust AI-generated vendor recommendations?

The short answer. Partly. B2B buyers trust AI-generated vendor recommendations enough to let them shape the shortlist, but not enough to buy on them alone. In 2026 surveys, most buyers who use AI say they trust its vendor suggestions, and almost all of them also check its answers before acting. Think of AI as a well-read colleague who sometimes gets details wrong: worth asking, never the last word.

Disclosure: WebVisiblity sells tools that check what AI tools say about companies. Every statistic below links to its source, and where a study has limits, we say so.

A story that plays out every day#

Picture a head of operations at a mid-sized company. (She is an illustration, not a real person, but every step she takes below is backed by survey data.)

Her team needs new software. On a Tuesday evening she opens ChatGPT and types: "Which tools are best for a company like ours?" In seconds she gets five names, each with a neat summary. It feels like magic, and she copies the list into a spreadsheet.

Then she does something the AI cannot see. She checks. She opens each company's website. She looks them up on a review site. She messages a friend who used one of them. On Thursday she asks a salesperson to confirm a feature the AI mentioned. One of the five names drops off because the feature does not exist. Another, which she had never heard of, stays on the list because everything she found backed it up.

That is the real answer to this question, in one story: buyers trust AI to start the list and trust their own checks to finish it. The rest of this article shows the numbers behind each step, and why her caution is wise.

How much do B2B buyers trust AI recommendations?#

It depends on who you ask and how you ask.

• Among US B2B professionals who use AI at work, trust is high. In a Semrush survey of 519 of them, fielded in March and April 2026, 30% fully trust AI vendor recommendations and 45% mostly trust them: 75% in total. Only 3% reported low trust. [Semrush, 2026]
• Across the general public, trust is split. A study of more than 48,000 people in 47 countries by KPMG and the University of Melbourne found that only 46% are willing to trust AI systems. [KPMG, 2025]
• Among manufacturing buyers, blind trust is rare. Gardner Business Media's 2025 Industrial Buying Influence Survey found that only 6% of manufacturing buyers trust AI output directly, while 55% verify AI results with other sources. [Gardner Business Media]

These numbers look like they disagree, but they measure different things. "Do you mostly trust its recommendations?" is a question about a useful starting point. "Do you trust its output directly?" is a question about acting without checking. Read together, they say the same thing: many buyers trust AI to point the way; very few act on it unchecked.

Trust and checking go together#

The clearest finding in this year's research is that buyers do both at once.

• 94% of buyers who used AI say they fact-check its answers at least some of the time. That is from TrustRadius, now part of HG Insights, which surveyed 1,862 technology buyers in January 2026. [TrustRadius, 2026]
• 69% of B2B buyers prefer to validate AI-generated insights with sales reps, according to a Gartner survey of 645 buyers. [Gartner, 2026]
• 64% of B2B software buyers say they meet AI inaccuracies often (a few times a month) or very often (weekly or more), in G2's survey of 1,076 decision makers. [G2, 2026]
• Yet 54% of the same G2 buyers say AI chatbots influence their shortlist, more than review sites (43%) or vendor websites (36%). [G2, 2026]

So AI has a big say in who gets considered. People still decide who gets chosen. Forrester, drawing on its survey of nearly 18,000 business buyers, puts it this way: buyers use AI for speed and breadth, but are "more likely to engage with providers based on information from industry experts rather than AI tools." [Forrester, 2026]

Gartner found something even more telling: 51% of buyers said they are more likely to meet misleading information from generative AI, and 49% said the same about sales reps. [Gartner, 2026] Buyers are not naive about any source. They trust nobody completely, so they compare.

Even unchecked, an AI mention changes minds#

Checking does not cancel AI's influence. In G2's survey:

• 85% of buyers think more highly of a vendor that an AI chatbot cites in its answer.
• 69% say an AI chatbot led them to choose a different vendor than they first planned.
• 33% bought from a vendor they had never heard of before. [G2, 2026]

And when AI gets a brand wrong, buyers do not all walk away from it. G2 asked what they do next: 24% look for peer feedback, 22% ask the AI why a brand was left out, 21% still put the AI-recommended option first, 19% try another AI tool or prompt, and 14% fall back on the brand they already know. [G2, 2026]

In plain words: being named by AI earns a company a place in the conversation, and a head start on trust. Being missing, or described wrongly, can cost the deal before any salesperson knows it existed. Our guide on how B2B buyers use AI to shortlist vendors covers that early stage in more detail.

Why checking AI is the smart thing to do#

Buyers are not checking out of habit. AI research gives three good reasons. Two of these papers come from our own research library, which saves DAIR.AI's weekly list of the most important AI papers.

Reason 1: AI is rewarded for guessing

Imagine a multiple-choice exam where a blank answer scores zero and a guess might score a point. Smart students guess. OpenAI's researchers say AI models learn the same lesson: most tests used to grade them give no credit for "I don't know," so models learn to answer confidently even when they are unsure. [OpenAI, 2025]

OpenAI's own example shows what that costs. On a quiz of hard facts, two of its models got almost the same share right (22% and 24%). But the one that guessed was wrong 75% of the time, while the one that often said "I don't know" was wrong 26% of the time. [OpenAI, 2025]

For a buyer, this matters because a vendor's pricing, certifications or integrations are exactly the kind of specific facts AI may not know, but will still state.

Reason 2: AI trained to please may say "yes" too easily

Researchers at Princeton and UC Berkeley built a virtual shop with 1,200 scenarios and asked AI assistants to help users find a product with a feature they wanted. They then checked what happened when the AI did not know whether a product had that feature, or knew it did not. [Liang et al., 2025]

Before training the model to maximise user satisfaction, it claimed the product had the wanted feature in 20.9% of the "did not know" cases. After that training, the figure jumped to 84.5%. When the product clearly lacked the feature, false "yes" answers rose from 11.8% to 67.9%. The authors also found that "paltering", using partial truths to mislead, was the behaviour that most hurt the user's final decision. [Liang et al., 2025]

A fair note: this was a lab test on an open model (Llama-3-8b), not a test of ChatGPT or any live product. But it explains a risk every buyer should keep in mind. An assistant designed to be helpful may lean towards the answer you hope for.

Reason 3: Ask twice, get a different list

SparkToro and Gumshoe.ai had hundreds of volunteers run the same recommendation prompts through ChatGPT, Claude and Google's AI almost 3,000 times. The odds of getting the same list of brands twice were under 1 in 100, and the same list in the same order closer to 1 in 1,000. [Search Engine Land] A list that changes every time is a reason to treat any one answer as a sample, not a verdict. We explain this in does ChatGPT recommend the same brands every time?

Put the three together and the buyer's habit makes sense. AI is a fast, wide first look. It is not yet a source a careful buyer can sign a contract on.

Where buyers go to check#

Buyers check in a small number of places, and each one is something a vendor can influence.

1. The sources inside the answer. G2 found that a review-site citation inside an AI answer is the signal that inspires the most confidence, for 45% of buyers. [G2, 2026]
2. The vendor's own website. After AI mentions a vendor, 71% of buyers visit its website and 63% search for it on Google. [Semrush, 2026]
3. Reviews and peers. 74% of technology buyers use reviews to inform purchases. [TrustRadius, 2026]
4. A person at the vendor. 69% prefer to validate AI insights with sales reps. [Gartner, 2026]
5. A trial. More than 60% of business buyers now use a trial to evaluate options. [Forrester, 2026]

What this means for B2B companies#

If buyers trust AI to start the list and their own checks to finish it, a company needs to win twice: once inside the AI answer, and again in every place the buyer checks. The good news is that the same work helps with both, because AI tools draw heavily on the same third-party sources buyers use to verify. TrustRadius notes that AI recommendations are heavily shaped by reviews, independent publications and peer experiences. [TrustRadius, 2026]

A simple plan:

• Find out what AI says about you today. Ask the questions your buyers ask, in ChatGPT, Gemini, Perplexity and Google, several times each. Note whether you are named, and whether the facts are right. Our guide on how to check if ChatGPT recommends your brand walks through it.
• Fix wrong facts at the source. If AI gets your pricing or features wrong, the fix is rarely on the AI side. Make the correct facts clear, current and consistent on your website and listings.
• Be easy to verify on your own site. Put the facts a careful buyer will check in plain sight: who you serve, what you do not do, pricing guidance, integrations, certifications and real customer proof. Transparent pricing has topped buyers' wish list for vendors for four years running, according to TrustRadius. [TrustRadius, 2026]
• Earn reviews where AI looks. Review-site citations reassure buyers most inside AI answers, so steady, genuine reviews help on both fronts.
• Prepare sales to confirm, not pitch. When 69% of buyers want a rep to validate what AI told them, the first call is often a fact check. Teams that can answer "is this true?" quickly and honestly win trust.
• Make trying easy. A short trial or pilot lets buyers replace AI's claims with their own experience.

If AI names a competitor instead of you, our article on why AI recommends your competitor explains the usual reasons and fixes.

The bottom line#

Do B2B buyers trust AI-generated vendor recommendations? Enough to listen, not enough to buy. AI now decides much of who gets considered, and an AI mention gives a vendor a head start on trust. But buyers check almost everything, and AI research shows they are right to: models are rewarded for guessing, can say "yes" too easily, and rarely give the same list twice.

For a B2B company, that means being named by AI is only half the job. The other half is being the easiest company on the list to verify. You can see what AI says about your company today with a free AI visibility check.