AI agents won’t kill shopping – but agentic commerce could make most of it redundant

What if 90% of shopping is a complete waste of time?

And despite what others might tell you, I don’t just say that as a mildly-unfashionable middle-aged man who hates everything to do with the experience of buying things.

Instead, this question came into focus during a recent discussion with Andrew Bialecki and Chano Fernández, co-CEOs of marketing automation company Klaviyo, about the shift from e-commerce to agentic commerce — and then further still into what they call “agentic experience.”

And while their examples are early, they point to a broader shift.

Because if agents take over the work of finding, evaluating, and purchasing products on our behalf, then most of what we think of as shopping — outside of the occasional in-person social experience — starts to look less like a meaningful activity and more like background infrastructure.

No searching. No marketplaces. No defaulting to familiar brands.

Which raises an uncomfortable possibility — what if much of today’s online shopping infrastructure exists not because shopping is valuable, but because human cognition doesn’t scale to an entire Internet’s worth of options?

Remove that human processing constraint, and the infrastructure built to scaffold it starts to look less essential — along with a significant part of today’s customer-facing operating models.

But what replaces that customer-facing infrastructure? And how might it impact tomorrow’s competitive environment?

Happy Bot-idays

Our story begins with a good old-fashioned Christmas tale — in this case the growth of agentic commerce over the 2025 holiday period.

Many of Klaviyo’s customers worked with the company to build agents that could help customers find gifts for their family and friends during one of the busiest periods of the year. Bialecki explains:

There’s an athletic brand that we work with here in the States, and over the holidays they set up what we call our customer agent. Think of it as like a ChatGPT, but scoped to the business that sits on their website or is available via voice.

At first glance, this might simply look like the deployment of an additional channel — something businesses have already done via mobile. But in practice, the ability to ask questions and add context — rather than simply browse static information — doesn’t just represent a change in form factor or location, but a change in how customers behave. As Bialecki has observed:

When people were browsing the website, they had all these questions like, how does the sizing on this gear run? What kind of climate is it better in, summer or winter? How does it perform when it gets wet?

And while much of this information already exists, traditional e-commerce infrastructure places the burden of answering these questions on the customer — by trawling through product pages, searching for reviews, or browsing forums. But as Bialecki points out, agents can significantly reduce that friction — especially for less experienced customers:

That particular business is targeted more toward non-professional athletes, so they used our customer agent technology to help people discover products, ask questions about them, and ultimately buy — all through the agent.

This means many of the questions being asked are no longer product queries but expressions of need — a shift in the center of gravity towards the customer’s jobs-to-be-done. Practically, Bialecki says he is already seeing this shift in his customer base:

We’ve got a swimwear company in Australia and people aren’t just buying swimsuits, but asking questions like: ‘I’m going on a trip for ten days, how many swimsuits should I bring?’ They’re [asking] how to plan a vacation. That’s like walking into a shop and getting a helpful shopkeeper who gives you information beyond what’s on the shelves.

What matters here is not the idea of sales agents per se but the question of what happens to existing go-to-market infrastructure.

Because when customers can start with intent instead of products, and expect the system to help them find the right answer, much of the transactional work we think of as shopping — searching, comparing, narrowing down — begins to disappear, along with the infrastructure built to support it.

And if Bialecki’s experience is typical, that trajectory is already accelerating. He tells me:

This year we'll go from thousands to probably tens or hundreds of thousands of folks using our agents to deliver customer experience. By the holiday season this year, I think the default experience will be to click to chat with that business.

Shopageddon

While agents might undermine the basic mechanisms of traditional online shopping infrastructure, they could also do something more fundamental — remove the need for that infrastructure altogether.

And this shift is already starting to show up in practice, as Bialecki describes:

Imagine a classic start to the New Year where you go to ChatGPT or your personal agent and say, ‘I’m going to train up for a half marathon. How should I do that?’ Not only will your agent help to build a plan, but it will help you find a pair of trainers, the right outfit, a water bottle.

But what follows from that is the real shift — agents won’t just surface information but will move into the market on the customer’s behalf, leading to a shift in how Bialecki sees businesses needing to engage:

Rather than looking at websites to figure out what those products are, your agent will query the agents that represent those businesses: ‘What’s your best trainer for someone starting out? What would you recommend?’ Businesses will make their pitch and then the agent will pick the best ones to show to the user.

Underpinning this is the emergence of agent-to-agent interaction, where systems act on behalf of both customers and businesses — with open standards promising to create the conditions for a new form of infrastructure. As Bialecki puts it:

There are good open standards, the right building blocks. But what does it mean for a business to offer an agent to every customer? To other agents? There are hundreds of millions of businesses that will need this technology over the next couple of years if they are to be prepared for this agentic evolution.

As agents move from channel to infrastructure, it’s not only the transactional mechanics of shopping — browsing, filtering, or comparing — which have been bypassed. More importantly, agents will hold the most valuable context — past preferences, current intent, and purchasing authority — and use that context to make decisions and execute purchases on our behalf. At that point, much of what we think of as shopping begins to look less like a fundamental human activity and more like an inconvenient chore that can be handed off to networks of agents.

And the bootstrapping of that agent-to-agent infrastructure is now becoming a cross-industry effort, as Bialecki outlines:

We're now working with a lot of the AI labs on what the agent-to-agent experience looks like. Today we often think about agents as something a human interacts with — but increasingly, we’re going to be happy to delegate to agents that pull things together.

In this new world, therefore, brands will no longer be competing for human attention within environments they control — pages, listings, storefronts — but competing for selection by agents operating beyond their control.

Which, as Bialecki outlines, forces a different approach to competition:

It's going to be very important that a business gives answers using context about who that person is — ‘I used to run back in university but I haven't done it in ten years. I'm trying to get back into it,’ or, ‘My friends got me into this. It's my first time.’ That could be based on information the customer agent passes through, or information the business already has about its user. You need to be an expert in value-add.

Faced with these demands, the familiar structures of e-commerce start to look like artefacts of an earlier model — a shift Bialecki is already preparing for:

We even envision a world where agents are the real source of business truth rather than websites — with websites being auto-generated on demand based on what you're looking for.

Taken seriously, this begins to point to an experience layer that may no longer be anchored in websites, apps, or product catalogs. Instead, experiences become fluid, generated, and contingent on the request being made — assembled dynamically by a network of agents beyond the control of the participating company.

In that world, a significant amount of the work we think of as shopping — and the infrastructure brands have built to facilitate it — will be absorbed by networks of agents, forcing brands to compete for selection within systems they do not control.

A shift that, if it takes hold, could demand a new technical and operational infrastructure for commercial engagement.

My take

What began to crystalize from my conversation with Bialecki and Fernández is this — most shopping, outside of a small slice of social activity, is a chore rather than a choice. And as a mildly unfashionable middle-aged man, I could have told you that already.

In that sense, agents don’t kill shopping — they just reveal that most of it was never worth doing in the first place.

But what I find even more interesting is that when we run with the potential implications of agents, it feels like much of the infrastructure we’ve built to facilitate that unwanted 90% is really just a set of workarounds for a single problem — the cognitive bandwidth constraints of humans.

Brands, search engines, marketplaces, intermediaries — all of them are, in one way or another, hacks. Mechanisms for capturing, directing, and retaining our scarce human attention by scaffolding our limitations — reducing the effort required to find what we need through trust signals, discovery shortcuts, or breadth of offering under one roof.

But none of that is necessary if agents can simultaneously find and evaluate an infinite number of offerings on our behalf.

Instead of needing an aggregation layer to make selection manageable, agents simply become the aggregation layer — one that is tuned to our goals rather than those of the intermediary. Which helps explain why online giants are now scrambling to own that layer — and avoid losing visibility into our wants and needs.

Because while in the short term, what Bialecki is describing is co-option — agents being added as just another owned channel for brands to distribute offers and engage customers — the longer-term implication is potentially far more disruptive.

Not a new channel, but a reversal of power.

Today, brands compete for attention — and once they have it, they benefit from the fact that customers don’t have the time or context to fully explore alternatives. That constraint creates an asymmetry in which customers rely on brands to reduce uncertainty — and accept the margin embedded in that convenience because they don’t have the capacity to evaluate the whole market.

But agents do.

With effectively unlimited capacity to search, compare, and evaluate, an agent can see more of the market than the customer ever could — and more than any individual brand would want them to. At the same time, the agent’s evolving understanding of the customer’s preferences has the potential to create a new asymmetry — one which favors the customer over the brand.

Because companies are no longer competing for the attention of a constrained human — they are competing for selection by a system that, if it lives up to its promise, has greater knowledge of the customer’s goals and an ability to evaluate the entire market in real time.

And that shift — from optimizing for attention within environments you control to being evaluated within systems you don’t — quietly inverts control away from the brand and towards the customer and their agent.

Perhaps not completely. Perhaps not immediately. But directionally.

So agents don’t destroy shopping as a choice — for enjoyment, identity, or social signaling.

But they do threaten to eliminate shopping as a chore.

And in doing so, they may start to erode the e-commerce infrastructures, data moats, and operating models that have grown up around it.