By Urban Gavelin, , Sales Strategy & AI Disruption
The Buyer Has Already Done Your Needs Analysis
I have been reading Victor Antonio's book, The Future of Selling, and one idea will not let go of me: the buyer's AI agent has often already compared vendors, calculated total cost, and read your references before you ever get your first meeting. That changes what a salesperson is actually for.
The Future of Selling
For more than a hundred years, the salesperson held the advantage. The salesperson knew more than the customer, about the product, the pricing, and what other customers had gotten out of it. Every sales training I ever received was built on that premise: ask the questions, find the need, present the solution.
Antonio's point is that AI levels that advantage, and sometimes reverses it entirely. The buyer's agent can compare vendors, calculate total cost of ownership, read reviews, and search for risk. It does all of this before anyone from the sales side is even invited to the table. By the time you walk into the room, the customer does not need help understanding their problem. They may have already ranked you.
What That Does to the First Meeting
Think about what this does to the classic opening line. 'Tell me a bit about your situation' used to be a strong way to start a meeting. Now it can sound like you have not done your homework. The customer has done theirs, with help from an agent that never needs a coffee break.
And the presentation sitting on your website has already been read by that agent, faster than you could ever read it yourself. The old script, where the seller arrives with questions and the buyer arrives with a problem, no longer matches how the conversation actually starts.
Clarification, Confirmation, Confidence
Antonio sums up what is left for the human in three words: clarification, confirmation, and confidence. Resolve what the AI cannot determine. Prove that the solution works under the customer's real conditions. Build trust around execution and risk.
That last part I recognize from a deal that, by all rights, should never have happened. When we started working with the major electronics retailers in the Nordics, one of them turned us down right before the holiday season. I did not push. I let the no stand. Three or four weeks later, the buyer called. Another supplier had failed to deliver what they had promised, and he asked if I could help him with a campaign package.
He already knew everything about our pricing and our range. That was not information he was missing. What he needed was someone he trusted to actually deliver, now that something had already gone wrong once. You will not find that in any price comparison.
Influence the Criteria, Not the Price
This is why I think the strongest idea in the book is about influencing the criteria. You will rarely beat the buyer's agent on price or features. But you can influence what it calculates. Delivery reliability. Implementation risk. Time to value. The cost of failure. Once a new variable enters the calculation, the whole thing has to be recalculated. Do not try to win the game as it is scored. Change how the points are counted.
That requires something the agent cannot find online. Antonio calls it your company's alpha: your actual outcomes with past customers, the mistakes you know tend to happen, the experience from companies that look like the one sitting across from you. 'We have the best implementation in the market' carries no weight in a comparison. 'Here is how our last comparable projects actually went, including the ones that went badly' carries a great deal more.
There is an uncomfortable flip side to this. If your results only live in your salespeople's heads and in half-filled CRM fields, then you do not have alpha. You have anecdotes. What is not written down cannot be counted on, not by a customer and not by an agent. So if the buyer already knows everything that is on your website, what do you actually have left to add the moment you walk into the room?
Frequently asked questions
What does Victor Antonio mean by a company's 'alpha'?
Alpha refers to the real, documented performance data a company has from past engagements: actual outcomes, common failure points, and implementation timelines. Unlike marketing claims, this information cannot be replicated by a competitor and gives buyers something concrete to weigh that an AI agent cannot find published anywhere else.
How should salespeople change their opening questions in light of AI-informed buyers?
Instead of asking customers to explain their situation from scratch, sellers should ask how far the buyer has already gotten in their research and what they still need to understand. This starts the conversation where the customer's analysis ends rather than repeating work an AI agent has already done.