Vazghen Nikolian is an expert in AI and supply chain automation.
AI agents are getting better and more widely used; almost every day, a new AI startup claims to automate another vertical. Sales agents, in particular, are getting a big chunk of public attention as one of the most disruptive and fast-growing use cases.
But I foresee a twist to this rapid AI revolution: That sales, as we know it today, may not survive AI.
The Seller’s Role
In ancient economies, the buyer was the one who had to act. When someone needed something, they would go and find someone who had it and try to trade it. This approach had two downsides: Someone had to have the needed item in surplus, and they had to be willing to trade it for the offered goods.
Later, with human specialization and the invention of money, both parties had to act. Now, sellers also wanted to sell and tried to find buyers. The greatest invention of that period was the marketplace—where buyers and sellers would show up at the same time and place to transact.
The next major shift in seller-buyer relationships happened with the Industrial Revolution. People started producing way more goods at much lower prices. In such circumstances, sellers had to act much more to win buyers. This led to another invention: Marketing, which is simply the way a company tells buyers about products and convinces them to buy them.
Then came the internet. Marketplaces became global, and buying became easier. Buyers no longer needed to go anywhere physically. They had better tools to search, compare and evaluate. This made sellers act even harder. The internet pushed them into a race for visibility—and gave them new tools to compete.
AI Is Supercharging Sales
Nowadays, the internet is flooded with ads, branding, various types of advertising and cold outreach. Sellers are putting great effort and resources into repeatedly appearing in front of users—sending emails and bringing them to websites with nice designs and slogans to convince them to buy.
All these processes involve a lot of analytics, content creation and repetitive tasks like writing outreach messages, updating CRMs and tracking leads. Transformer-based large language models (AI) are especially good at those tasks, so naturally, sales was one of the first domains to get automated. Many AI SDR and marketing agent companies have been created over the last two years—some seeing real success and quick growth. More content is being created, more cold calls are made, and more emails are sent. It feels like the seller’s side is more active than ever.
But I foresee another shift in the economy of buying and selling—perhaps even bigger than any before.
The Buyer Reclaims Power
Imagine if, at the very moment a buyer recognizes a need, they could instantly reach all sellers who offer the item, validate them and compare all parameters of the product and selling conditions. That’s what future AI purchasing agents are promising. An AI agent doesn’t care about a cold email. It doesn’t matter how many times it sees an ad. A nice slogan or website won’t convince it. In other words, the core tools of modern marketing—attention, emotion, branding—simply don’t work on AI. An agent will take the buyer’s requirements, find all available options and pick the best one. It will find all proposals on the internet—whether they’re on the first page of a search engine or buried on page 14. All it cares about is ensuring that requirements match and offer value.
I see this model as closer to our ancient one than to anything in between. With AI agents, the act is again on the buyer’s side—it has to find and communicate with sellers. But unlike in the ancient world, it doesn’t take time, costs almost no resources and can be done at scale. Instead of communicating with one seller, it can reach all of them. So why spend resources on advertising, branding and marketing? What is the purpose of a sales agent if the buyer is that powerful?
To market products in an era where the buyer is not human, marketing teams may need to start thinking from the agent’s perspective. How do we make it easier for an agent to find the relevant data? How can we describe our products with structured and complete information to support decision making? How can we make pricing clear and unambiguous? Overall, it’s a shift from a human-emotional approach to a machine-logical one.
Of course, it will take a while until a sufficient number of agents appear, and even more time for us to adopt them. At first, we’ll outsource communication to agents and, later, even decision making. I believe B2B purchases will move in this direction sooner since they tend to have clearer, more defined parameters. But consumer goods will surely follow, and as AI agents eventually learn their owners’ preferences, people will start buying through them.
All of this will not happen overnight. Meanwhile, sales and marketing tools powered by AI are more efficient than ever. But it might be the brightest sunlight before sunset.
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