I asked three AI assistants the questions your buyers ask. Here's what they got wrong.
Over the past weeks I ran a simple test on several technical companies. I asked ChatGPT, Gemini, and Claude the exact questions a prospective buyer, partner, or investor would type, then checked the answers against what's actually true.
Three patterns kept repeating.
1. A limited claim gets inflated
A product that estimates or screens gets described as one that determines or guarantees. The distinction sounds small. It isn't. That careful wording is often the thing the company's credibility, and sometimes its regulatory position, is built on. The assistant erases it in one confident sentence, and the answer reads better for it. Fluent and wrong beats hedged and right, as far as the model is concerned.
2. A not-yet-certified capability gets presented as certified
Something offered for limited or research use gets described as fully approved and ready for production. For a buyer weighing a purchase, that isn't a nuance; it's a decision made on false information. And it cuts both ways: the buyer who discovers the truth late doesn't blame the assistant. They remember your company as the one that "wasn't what it claimed."
3. You ask about company A, the AI recommends company B
Asked for the best options in a category, the assistants listed competitors and never mentioned the company whose space it is. Not maliciously. The engines lean on whatever sources they can synthesize, and if third parties talk about your competitors more clearly than anyone talks about you, that's the answer buyers get.
Why this matters more than it sounds
Increasingly, the first opinion a buyer forms about your technology doesn't come from your website, your paper, or your demo. It comes from an AI assistant summarizing the internet about you. If that summary is wrong, or points somewhere else, you don't get a rebuttal. You may never even know you lost the room.
The part that's fixable
None of this is solved by arguing with the model. It's solved on the input side: improving the sources these engines actually draw on (your own pages, your documentation, the third-party material that describes you) and then re-measuring to confirm the answers moved.
The first step is knowing where you stand. I'll run that check for you at no cost: the real questions your buyers ask, put to the major assistants, with the transcripts and the errors laid out plainly.