The AI-researched buyer is a different animal than the Google-researched buyer.
Don’t correct them first. The AI-researched buyer arrives with a conclusion and reasoning behind it, not a pile of links, and they’re proud of the work. Validate the method before you question any of the information: ask which platform they used and what prompt they wrote, because the answer is the best discovery you’ll get all week. Then refine their research with them, using your own knowledge and your own AI, rather than arguing against it. And understand that none of this matters unless the research pointed them at your company in the first place, which is a different problem with a different fix.
Last year, I decided to buy a new video camera for my business. Until then, everything had been shot on my phone, and it was starting to show. I needed better video, and especially better audio.
The problem was that I knew exactly nothing about video cameras. Even the thought of Googling it was intimidating, because I’d have landed on six review sites run by people trying to sell me something, with no way to judge any of them.
But I work in Claude every day, so I figured, why not. I fed in my budget and the features I thought I needed. About twenty minutes later — some of which was Claude gently letting me know that my budget wasn’t realistic, because I didn’t know what I didn’t know — I had the right camera for my needs, with the best reviews and reliability record in that range.
Then it did something else. It found that camera in stock, on the shelf, at a shop fifteen minutes from my house. So I could go see it, touch it, and talk to a human being before I bought it.
Think about that for a moment. Customer buying habits have changed, and you and your company should care about that.
How is this different from the pre-researched buyer we already know about?
I’ve spent a decade telling salespeople that buyers do their research before they ever talk to us. That was true, and most of us adjusted to it, more or less.
But that buyer showed up with a dozen tabs open and a head full of half-digested specs. They had information. They usually didn’t have a conclusion, and they usually knew it.
This isn’t a niche behavior anymore. 6sense surveyed nearly 4,000 B2B buyers for its 2025 Buyer Experience Report and found that 94% of them used AI during their buying process. The interesting part is what that didn’t change: those buyers had about the same number of conversations with vendors as buyers did before AI. They’re not talking to fewer salespeople. They’re arriving at those conversations further along.
The AI-researched buyer shows up with a conclusion. Not just what to buy, but often where to buy it, and why that one instead of the other one. The reasoning arrived with the answer – that’s what AI does. It tells you what you ask it to tell you, and it tells you why. Google search never told you why – it gave you sources to figure it out for yourself. The AI researched buyer doesn’t have to sort through twelve sources and decide who to trust, because something already did that and explained itself along the way.
AI is now defining what to buy and where to buy it. You’d better be ready for both ends of that transaction, because that’s not the old Google search.
Why does correcting them backfire?
Here’s what I see happening, from salespeople, sales managers, and owners alike. They’re intimidated by this, and the intimidation comes out as pushback.
“Well, there’s a lot that AI doesn’t know and can’t do, and it leads people in the wrong direction.”
That statement is frequently true, and the person saying it usually has the expertise to back it up. It is also almost always the wrong thing to say, because of what it does to the conversation.
What the salesperson is trying to do is re-establish authority. I’m the expert here, not the machine. What the buyer hears is that they’re being scolded for having done their homework. Keep in mind that in many cases, the salesperson genuinely is the expert, and is justified in thinking this – but scolding is the wrong approach.
Nothing kills a buyer’s motivation faster than being scolded for doing their own work. And make no mistake — a researched buyer is a motivated buyer. Nobody spends an evening working through options for a purchase they’re lukewarm about. That buyer is closer to buying than any cold prospect your team will talk to this month, and the instinct to correct them first is the fastest way to cool them off, or send them elsewhere (and “elsewhere” might even be back to AI to find a better source).
What should my salespeople say instead?
That buyer is proud of the work they did, and they expect some validation for it. Give it to them.
To make this work, you must validate the method without validating all of the information.
“Wow, that’s great — you’ve done a lot of our work for us. You researched this with AI? Which platform? I work with AI a lot, but I’m not an expert in all of them. What prompt did you use?”
Ask it with genuine curiosity, because there’s real information in the answer. Their prompt tells you what they believe their problem is, what constraints they think they’re operating under, and what they left out entirely. I’ve never gotten better discovery from a single question than “what did you ask it?”
And notice what your rep just became. A partner in the process, instead of an obstacle to it.
What if their AI gave them the wrong answer?
Do all of the above even when — especially when — you can see the solution they arrived at isn’t what they actually need.
You will not redirect that buyer by arguing with their work. You redirect them by working with their momentum. They’ve built up speed in a direction. The job is to bend the path, not to stand in front of it. Think “gentle curve,” not “stop sign” or “U-turn.”
The most effective move I’ve seen is to lean further in rather than pull back. Have your own AI thread, trained on your tribal knowledge: your product line, your application history, the failures you’ve seen, the things your company knows that never made it onto a spec sheet. Feed their prompt and their conclusion into it.
“Mind if we refine this a little? I’ve got an idea for a refinement prompt.”
Now your rep is doing the research with the buyer, in the tool they already trust, with knowledge only your company has. That buyer will respect that enormously more than they’ll respect a veteran salesperson waving a hand and saying, “ah, that AI stuff never gets it right.”
Then you overlay your own experience on top of it. That’s where your people earn their keep now — not in gatekeeping information, which is finished, but in knowing which of those answers survives contact with a real application, a real installation, and a real budget cycle.
None of this matters if the research doesn’t point them at you
Everything I just described assumes something: that the buyer’s research sent them to your company in the first place.
That’s the part owners should be losing sleep over. When a buyer asks an AI who can solve their problem, the answer gets assembled from what the engines can find and trust about you. Not from your billboard, not from your years in business, and not from how well your reps sell once they’re in the room.
I’ve been doing a lot of work on this lately, measuring what the AI engines actually say when a buyer asks about a company and about the problems that company solves. It’s become part of my Sales Audit work. I’ll write more about the method another time, but a few things are already clear.
Your website has to answer the questions your buyers actually ask, in their words rather than your marketing language. The pages that get pulled into AI answers are the ones that answer a real question directly, near the top. This can be hard; we like our marketing language a lot. The problem is that it’s often not the buyer’s language. The buyer’s language trumps yours.
Specifics beat adjectives. “We serve small and midsize manufacturers with twenty to fifty field service trucks” does more for you than three paragraphs about your commitment to excellence or your company history.
What other people publish about you matters more than what you publish about yourself. Associations, trade publications, event pages, reviews, interviews. That’s what the engines treat as evidence. Get involved and be part of those publications.
Go ask them yourself. Open ChatGPT, Claude, Perplexity, and Google and ask what they know about your company, and who they’d recommend for the problem you solve. What comes back will either reassure you or ruin your morning (the first time I did it, it ruined mine). Either way, you’ll know where you stand, which is more than most of your competitors can say.
Make “we’re AI-friendly” part of your marketing
Here’s what you should act on this week, and it costs nothing.
Say it out loud. On your website, in your marketing, and in your sales conversations: we welcome customers who’ve done their research, including research with AI, and we’ll work through it with you.
Almost nobody is saying this yet. Your competitors are hoping their salespeople can talk buyers out of their own conclusions. Meanwhile, the buyer who spent an evening working out what they need is actively looking for a supplier who won’t make them feel foolish for it.
I was that buyer with the video camera. I walked into a store fifteen minutes from my house knowing exactly what I wanted and why. What I needed from the guy behind the counter was confirmation, a couple of things I hadn’t thought of, and a reason to buy from him instead of ordering it online.
He got the sale. It wasn’t hard. He just didn’t argue with me.
If what you really want to know is what the AI engines are telling buyers about your company, and what to do about it, that’s a piece of the Navigator’s Sales Audit. It’s a paid engagement, and it goes considerably deeper than a conversation: what the engines say when a buyer describes your problem, who gets recommended instead of you, and where the gap actually is.
Questions owners ask about this
Is an AI-researched buyer really different from one who Googled it?
Yes. The Google-researched buyer brought information and knew they hadn’t sorted it out. The AI-researched buyer brings a conclusion with reasoning attached, and often a preferred source to buy from. You’re joining the process much later, and much closer to the decision.
What if the AI gave them flat-out wrong information?
Refine it with them rather than correcting them. Ask what they asked, add what your company knows, and run it again together. Same destination, no bruised pride, and you look like the expert instead of the skeptic.
Should my salespeople be using AI in front of customers?
If they’re prepared, yes. A thread trained on your company’s knowledge, used openly with a buyer, is a powerful thing. Winging it with a public chatbot in front of a customer is not.
How do I know whether AI engines are recommending my company?
Ask them. Describe the problem you solve the way a buyer would and see who gets named. Do it on more than one engine, because they don’t agree with each other.
Doesn’t this make salespeople less important?
It makes information-delivery salespeople less important, and that was already happening. It makes judgment more valuable, because a buyer holding a confident answer still needs someone who knows which answers hold up in the real world.
