What does "adding value" mean when buyers ask AI first?

Adding value now means understanding what the buyer is trying to achieve, what each person in the decision needs from it, and helping them see their own problem more clearly than they can from the inside. The old kinds of value, knowing the product, holding the information and being the cheapest, are things a buyer's AI hands them before they ever book a call.

I first wrote about this in 2011. My line then was that if you don't add value, you're an order taker, and a customer who only sees a transaction will go to whoever quotes lowest. That still holds. What's changed is how much of the old value has been given away for free.

The information gap has closed

For most of my career, a big part of a salesperson's value was information. We knew the product, the options, the pricing and the market better than the buyer did, and they needed us to find out.

That's gone. Forrester's State of Business Buying 2026 says genAI searches are now the starting point for B2B buyers, and that those searches often give incomplete or unreliable answers, so buyers go looking for trusted sources to check them. Gartner's survey of 645 B2B buyers, published in May 2026, found that 45% said they'd used GenAI during a recent purchase, mostly to gather information on vendors and products. By the time a prospect talks to you, there's a good chance they've asked an AI who to look at and read a short briefing on you that you didn't write.

If your value was being a walking brochure, the brochure is free now, and it's more thorough than you are. Being reliably decent at the mechanics used to set a rep apart. When a machine produces decent in seconds, decent is worth nothing.

Being cheapest was always the shakiest kind of value. It counts, but it's shallow and short-sighted: it squeezes your margin, and the day a competitor undercuts you, it disappears completely. (More on that in why you should walk away from "me too" quotes.)

Find the need behind the need

The example I used in 2011 still works, so I'll keep it. Say a customer asks for a quote on 25 desktop PCs for a new office in Wellington.

An order taker quotes 25 PCs. A good salesperson asks a few more questions. What's the office for? What do the next three years look like? What information will the people in it need to reach? The answers might tell you the office exists to serve a new government client, that the team plans to grow, and that the data they need sits in a central system. The best answer to that might not be 25 desktops at all.

So you quote what they asked for, and alongside it you propose what you'd do in their position, even if it costs them less. The value sits in the gap between what they asked for and what they need. The product is only ever the means.

That gap is the one thing an AI summary can't close for a buyer. It knows your category and your competitors. It doesn't know that the person asking is about to win a contract that changes their requirements, or that the last system they bought failed because nobody asked how the team works. What research can't give buyers is an outside view of their own situation, the part they've stopped seeing because they're inside it.

Gartner's survey points the same way. Reps are still the most important information source when buyers are researching a business problem or need. Buyers can get specs anywhere. They want a person when they're working out what's wrong. (I've written about what that means for a sales team in buyers still want a human.)

Every person in the deal wants something different

People buy from people, which means you have to sell to people, plural. In 2011 I put it in IT terms: the IT manager wanted technical help and guidance, procurement wanted a clean process, low transaction cost and solid service levels, and the CIO wanted strategy and new ideas.

There are a lot more of them now. Forrester found the typical buying decision includes 13 internal stakeholders and nine external influencers, and that procurement is a decision-maker in 53% of buying cycles, involved from the start. A startup selling software into a mid-sized company might meet the person who'll use it every day, an IT or security lead worried about integration and risk, someone in finance looking at total cost, and an executive who cares about one number in the board deck.

Each of them defines value differently, and each may have asked their own AI a different question about you. Your job is to know which part of the problem each one owns, and what a win looks like for them personally.

The best version of this is helping your contacts look good inside their own company. Give your champion something that raises their profile: a business case in their numbers, an answer to the security question before it's asked, a plan finance can approve. People keep coming back to the salesperson who helps them win internally.

You're probably not a trusted advisor yet

The week before that 2011 post, I wrote one called "The 'trusted advisor' myth", and the point stands. Most salespeople who think they're trusted advisors are relationship selling. A monthly coffee and a chat about rugby is pleasant. It doesn't mean the customer would ask you to help write their RFP.

"People buy from people" is half the saying. People buy from people who deliver value. The realistic goal is to be a business partner: someone who works toward the outcomes the customer wants, doesn't sit back and quote, and usually isn't the cheapest. Trusted advisor status comes later, after a long run of being useful. It's also the part a machine can't earn for you, because trust gets built between people who both have something at stake.

What to do on your next deal

• Let AI do the homework. Company, people, recent news, what the buyer has probably read about you. It takes minutes now, and the first call doesn't get spent on things they already know. (Setting this up is a big part of our AI for revenue teams work.)
• Ask what they've already found. It tells you what they believe, and where the AI's version of you is wrong.
• Ask about the goal behind the request. What happens if this works? What changed to make it a priority now? What do the next three years look like?
• Map the people. Who's involved, what each one needs to be true, and who gets the blame if it goes wrong.
• Say what you'd do in their position. Even when it's smaller than what they asked for, and even when the answer isn't you.
• Give your champion something to take upstairs. A one-page summary of the problem and the business case, in their language.

Every one of those comes down to being more curious about the buyer's business than anyone else they talk to, chatbots included. It's the argument of my book, Curiosity, and AI has made it more valuable, because the buyer arrives knowing everything except the thing you're there to help with.

The AI can have the brochure. I never enjoyed reciting it.