94% of AI-Assisted Buyers Fact-Check the Machine, TrustRadius Finds

Ninety-four percent of technology buyers who used AI during a purchase fact-checked its answers at least some of the time. That figure comes from the TrustRadius 2026 B2B Buying Disconnect report, which surveyed 1,862 technology buyers in January 2026. Buyers no longer doubt only vendors. They doubt the research tools they use to evaluate vendors.

The mechanism is simple. Software now writes the pitch, sends it and personalizes it. A decent cold email, a tidy case study, a landing page full of confident claims each take a tool and about 10 minutes to produce, the author notes. When claims cost nothing, buyers price them accordingly — and every competitor sounds equally polished.

What do the numbers say about buyer behavior?

Three findings from the TrustRadius survey frame the problem:

• 94% of AI-using buyers fact-checked the AI's answers.
• 74% of buyers use reviews to inform decisions.
• 83% shortlist three or fewer products.

Buyers check outside sources, then narrow the field fast. A claim that cannot survive that check loses before the first conversation. The survey covers technology buyers, but the author argues the habit now extends to anyone selling anything.

A separate Gartner survey of roughly 645 B2B buyers, run in August and September 2025, found that 67% prefer a buying experience without a sales rep. A second release from the same survey found that 69% prefer to check AI-generated insights with a sales rep. The two numbers sound opposed. They say one thing: buyers want to evaluate alone first, then talk to a person who will stand behind the answer.

Why doesn't personalization fix it?

Mentioning a buyer's recent post or funding round used to signal attention. It no longer does. When software writes the first line, a personal detail only proves the sender has a decent data source. A pattern with your name filled in is still a pattern.

Even the new tactic of sending "real work" can be faked. Marketer Dennis Yu described receiving a seven-page AI-written audit in a cold email, with no real headlines or screenshots and a case study he says was made up. He saw through it.

The fix is verifiability. The author's test: real work names something only someone who looked would know, includes one concrete fix, can be checked in a minute, and has a named person willing to answer questions about it.

What works instead of claims?

The author's prescription rests on one idea: when words are cheap, the only signal left is effort the buyer can see. He recommends:

• Send a marked-up version of the buyer's landing page, a one-page teardown of their pricing, or a short sample made from their own material.
• Let the buyer evaluate it without replying, booking or talking to anyone.
• Send fewer pitches — 20 studied prospects beat 2,000 scraped ones.
• Put a person behind the follow-up, reply fast and answer the hard question directly.

What happened when free trials stopped converting?

The author's own video-editing business supplies the strongest evidence. New clients could get one edited video before paying anything. Conversion started at 91.5%. As paying clients multiplied and their work came first, trial edits got squeezed. Conversion fell to 67% over three years.

The remedy was a small fee for a single video, plus a short fit call in front of it. Conversion from paid trial to customer returned to roughly 87%.

His read: free work does not scale because it competes with paid work for the same people's time. A small fee pays for that time and filters for serious buyers. A paid audit or a one-page plan works the same way — kept small, with the next step set before anything is sent. A sample with no next step is a favor, not a sales process.

The broader lesson for sellers: verification now beats persuasion, and priced effort beats free effort.