AI agents are ready to shop. Some retailers are wary

Using an AI agent to shop for you is a strange experience. Tech companies have marketed them as personal assistants — the democratizing of labor that ordinarily would only be available to the rich and powerful. In practice, at least for buying things, it’s more like sending an anxious and apologetic teenager out to the store: They require an inordinate amount of instructions and specifications, run into technical problems regularly, and come back with solutions that are not exactly what you asked for. They did, technically speaking, complete a task, just not the specific one you asked them to, and often not in the way you would have approached it.

Meta, Google, OpenAI, and others have all introduced some version of agentic shopping tools that promise to make buying things even easier than it already is. Demos show AI agents that can seamlessly book flights and hotels, browse billions of products to find the right one, and secure tickets to sporting events on a human’s behalf. But as AI companies — and their users — are finding out, buying things requires that the other party is willing to sell them in the first place.

The most prominent example of a retailer or service provider refusing to let an AI agent in has been Amazon. The retail giant sued Perplexity, with Amazon saying the AI company had ignored its requests to stop its agent from shopping on the site. More recently, Amazon blocked Meta’s Muse agent from shopping on Amazon. E-commerce sites aren’t the only platforms walling off agents: JPMorgan Chase CEO Jamie Dimon said the bank wouldn’t allow outside agents to access accounts, saying it was “too risky” for clients and the company, and some users report they’ve been unable to use agents to book trips from providers like Delta and Amtrak. AI agents can also get caught in the web of general bot blocking systems, meaning that even if a site doesn’t have a blanket ban, existing firewalls can make agents inconsistent — and by extension, less useful for the types of tasks tech companies tout as the future.

Even without hard blocks, agents’ access to retailers is spotty. For example, Muse, which I instructed to look for a specific face moisturizer, was caught in Target’s bot check one day but was able to get through the next. It suggested a listing from a grocery chain that doesn’t ship to my address when I searched for the best price on granola bars. When I asked for mattress recommendations under a certain price point, Muse was once again blocked by Target, despite being able to pull from the site just a few minutes prior.

How successful an agent is at accessing a site may depend on how it went about the task and what safeguards are in place, Target spokesperson Loni Monroe told The Verge in an email. (Target has AI shopping partnerships with OpenAI, Google, and Microsoft.) Agents may be able to access one part of the site but not another, as a way to protect customer data and the shopping experience. In addition, Monroe said that Target has safeguards preventing unauthorized agents and bots from accessing customer accounts and initiating transactions on a human’s behalf.

The lack of Amazon options within agents is also impossible to ignore. Sometimes, the agents will say as much: When I asked Muse to find the best per-piece granola bar price, it offered options from Sam’s Club, Walmart, and Costco, but acknowledged a big caveat: Amazon might have had the lowest-priced option, but it was hard-blocked from browsing, so Muse couldn’t confirm. Between waiting for a response, directing Muse to search for more sites, and clarifying that a West Coast-based retailer wouldn’t ship to New York, it likely would have been faster to search myself. It also explains why agentic AI companies would really like to have Amazon on board — and why Amazon is so fiercely protective of how customers shop on its platform. It’s not that Amazon is against robots shopping in place of humans — the company has its own on-platform agentic shopping feature that monitors prices, automatically reorders items, and purchases products based on rules set by human users. Another feature that uses an agent to purchase products from other sites without leaving Amazon angered smaller businesses, who say they didn’t consent to having their storefronts scraped and featured on Amazon.

Amazon spokesperson Maxine Tagay confirmed that the company “requested that Meta remove Amazon” from Muse.

“We think it’s fairly straightforward that third-party applications that offer to make purchases on behalf of customers from other businesses should operate openly and respect service provider decisions about whether or not to participate,” Tagay said in an email.

It’s one thing for agents to offer comically spotty, disjointed services — but it’s another, potentially more frustrating experience when they actually do work, because of the implications for humans. In order to test a shopping task that I actually would like to automate, I unleashed Muse on The RealReal, a secondhand luxury fashion retailer. As secondhand shopping has exploded in popularity, shopping on The RealReal has gotten increasingly competitive, so much so that the company sells a $12-per-month subscription allowing shoppers to get early access to new items. On The RealReal, part of the shopping process is zero-sum: Placing an item in your cart reserves it for you for 20 minutes, making it impossible for other people to swipe it. I instructed my Muse agent to bulk-add all 10 of the newest listings from a favorite brand to my cart, effectively blocking other shoppers from purchasing them before I got the chance to review the latest selections. I had no intention of buying any of these items, but I prompted Muse to keep re-adding the items to my shopping bag each time the 20-minute hold had expired. On and on this went, all day (I eventually ended the task).

If I were a less honest, pure-hearted person, I would deploy an agent to run this personalized, technically allowed reserve system endlessly. But as I watched the items continuously pop back into my cart, exasperation flooded my psyche — on behalf of the other shoppers interested in these items, but also for my future self, who may soon be competing with someone else’s agent doing this same thing. Perhaps I already am.

The RealReal sees AI agents as an opportunity, and is investing in its own AI-powered services while protecting the integrity of the platform, chief technology officer Luke Friang told The Verge in an email.

“Our approach is to remain open to third-party AI agents, allowing them to browse, log in and interact with our marketplace, while maintaining safeguards against automated activity that could disrupt the customer experience,” Friang said.

To be sure, normal online shopping can be tedious, too — the endless array of options on the web can make finding the right thing feel like looking for a needle in a haystack. Agentic shopping is the inverse: It’s like looking at the world through a pinhole. If I don’t like the five options Muse has curated for me, I must ask it to find five more, and on and on. I must give the agent specific parameters and rules, and expand and tweak them as needed, little by little. A more rote task like finding the absolute lowest price on a product you already know you want is where an agent could be truly useful. Without Amazon, though, even that feels like the task was carried out with incomplete information.

If you have preferences about literally anything you spend money on — the price, the return policy, the shipping rates, the ethical standards of a company, the fabric composition — an agent is just another entity to express those preferences to. With the time and patience for hand-holding, Muse could help deepen a search for something specific: For example, I uploaded photos to Muse of a vintage dress I’ve been hunting for, along with the specific year it’s from, a list of keywords associated with it, notes about similar items, and secondhand platforms to start searches on. Muse could not find the dress for sale anywhere, but it did alert me to an upcoming auction of items from the same brand.

In an email, Meta spokesperson Tracy Clayton emphasized the partnerships the company has forged with retailers and the control human users have over the agent’s actions.

“Importantly, users can take over at any time, Muse is designed to always ask permission before buying, and it applies ethical browsing principles when asked to do things that a human could not - like buying all the tickets to an event,” Clayton said. “The response from retailers has been overwhelmingly positive, and we look forward to working with them as we continue to grow Muse and improve the purchasing experience.”

There’s another thing that nags at me no matter how long I tinker with agentic shopping: The joy and thrill of discovery is largely gone. Buying things is an American pastime. We do it in person, online, from strangers on Facebook, and from professional salespeople on livestreams. We buy things we need and we buy things we don’t, things we know we want and the things we’ve never seen until now that have suddenly become very important. It’s not a stretch to say that for many, shopping is a hobby — one that has become solidly entangled with another, more modern hobby of scrolling on a phone. We don’t just lust after material belongings; we imbue them with identity markers and social status. Buying things is intensive — in resources, in labor, in emotion. AI companies see this pastime as something that can be optimized. Many people would probably prefer that it not be.