As the world waited with bated breath for Apple to release details about its 17th iPhone, the New York Times posed an intriguing question: What comes after the smartphone?

Spoiler alert: The answer varies, but it could be smart glasses or a smart watch or maybe an ambient computer in another form.

At the center of this shift are AI agents, the next generation of virtual assistants, which some of the best and brightest minds in tech believe will know us better than we know ourselves. Eventually.

They’re already starting to emerge from the retailers and tech companies we already know with a focus on shopping. And the potential is far greater, which signals big shifts for consumers, brands and retailers. First, the players in this space will have to overcome fairly massive skepticism. But, once they do, and experts think they will, they will become the target of all future brand messaging.

Here’s what you need to know about them now:

What is an AI shopping agent?

AI shopping agents are virtual assistants that help consumers find, compare and purchase products or services.

According to a report from software company Salesforce, agents can also add items to carts and assist with checkout, although it’s still very early days for this functionality.

Depending who you ask, examples include Amazon’s Rufus and Walmart’s Sparky, as well as generative AI assistants like ChatGPT, Claude and Gemini.

What’s the latest with shopping agents?

A July 2025 study from market research firm YouGov found 43% of respondents had heard of AI shopping agents, but only 14% had used one. Among those who have tried them out, 44% said they asked product questions, while 41% used them to find products and 34% sought help with pricing.

But there are signs of consumer interest: 22% said they’re willing to give AI shopping assistants a shot—mostly for finding the best deals (67%), comparing similar products (56%) and getting product information (55%).

What problems do shopping agents solve?

In traditional e-commerce, consumers type in queries and are served product results and ads. But on a site like Amazon, which has 600 million listings by some estimates, results can go on and on. 

This infinite shelf space is a double-edged sword. Yes, it enables shoppers to hunt for the exact right item at any given moment. But they have to do a lot of scrolling and research first. And this is amplified with each additional site included in the shopping journey.

The main pitch for shopping agents is this: They do the research for you—and return a handful of carefully curated options.

That’s according to Melissa Bridgeford, CEO of Wizard Commerce, a startup building an AI shopping agent slated to launch in then first quarter of 2026, who called the experience “kind of like the anti-search.”

Here, the agent does the heavy lifting in the discovery phase, researching factors like prices, shipping speed and reviews, and it can do so a lot faster than human shoppers. “It can aggregate so much more information from a wider variety of sources than we might be able to aggregate ourselves,” added Kiri Masters, an analyst and podcaster focused on retail media. 

Plus, fraudulent and counterfeit goods have become an increasing problem for online marketplaces. Amazon disclosed it removed 15 million counterfeit products in 2024 alone—and that’s just one example. Shopping agents can at least theoretically cut through this noise and help consumers make more confident purchases.

“Consumers fear getting things wrong. A bad fit, a waste of money, fake reviews, all that stuff,” said Jason Alan Snyder, chief AI officer at advertising giant IPG and co-founder of AI data startup SuperTruth. “[An agent] promises certainty across references, reviews, product data, content and your past preferences.” 

What is driving this shift?

At the International Consumer Electronics Show in 2016, appliance brand Whirlpool teamed up with Amazon to announce a smart washing machine that could reorder laundry supplies when they were running low. It reportedly came with a price tag of $1,399, or about $1,900 today, according to an inflation calculator from the U.S. Department of Labor.

Cost may have been a contributing factor as to why smart appliances like this did not take off in 2016. But it’s also true Americans were simply not yet ready to hand over purchasing decisions to inanimate objects. 

They’re closer now. 

Ordering groceries, food delivery or even car rides with strangers are much more common following the pandemic—and related consumer behavior changes. Five years after the pandemic, e-commerce is still growing. According to a recent report, U.S. e-commerce sales hit $1.19 trillion in 2024, which means they have more than doubled since 2019.

Shopping agents are also getting a boost thanks to the quick adoption of generative AI. A 2024 Harvard study found more than 39% of Americans between 18 and 64 had used gen AI in the two years following ChatGPT’s launch. By comparison, just 20% had used the internet two years after its debut and it took the same number of people in the U.S. a full three years to give PCs a shot.

“The adoption rate on [conversational interfaces] is so steep,” Bridgeford said. “And that really creates tailwinds around the adoption of the entire agent experience.”

What challenges exist with shopping agents?

According to Salesforce, shopping agents provide personalized responses and recommendations, which yield a better experience, as well as increased conversion rates and higher average order value. Yet YouGov found 56% of Americans have no interest in using them—and 41% don’t trust them. 

Like the early days of e-commerce, Masters noted consumers are still wary of handing over their payment information to agents.

Another big and growing problem is fraud. “These AI tools in general allow fraudsters to do everything better, faster, cheaper than they already do. So, identity theft, return fraud–all the permutations of fraud that we have available–can scale much faster,” Masters said. 

But YouGov remains optimistic. Per the report, the key to driving adoption is proving agents add value, like finding the best price and offering trustworthy information about the products in question.

How will shopping agents evolve?

As time goes on, agents will get to know you and your shopping habits better and will become more proactive.

“It’s the agent that knows you better than you know yourself, that remembers things for you, that’s able to suggest things,” Bridgeford said. “It knows the brands you like. It knows the price points you feel comfortable with. It knows the size of your household, so when you’re in small New York apartments, it’s not suggesting some massive coffeemaker.”

And, of course, shopping is only the beginning. Booking flights, hotels and restaurants is a natural extension. So is recommending credit cards, loans and investments or even helping you choose the lab tests, supplements and wearables most relevant to your biomarker data, Snyder said. “What’s really cool with agents is they can negotiate,” he said. “So you can have your shopping agent bargain with a seller’s agent. Everything becomes like a Moroccan marketplace.”

Think: negotiating better credit terms on your behalf—or even weeding through potential matches on dating apps. “You could have matches based on circadian rhythm compatibility,” Snyder said. “That sounds crazy, but that’s a morning person or that’s a night owl.”

What should marketers know about shopping assistants?

That negotiation component has profound implications for brands and marketers.

When agents become the intermediary between consumers and brands/retailers, advertising as we know it won’t work anymore. For Snyder, that means eventually agents will only allow brands to reach you if they pay a fair price for your attention and data.

“It’s future-proofing yourself against manipulation,” he said. “Right now, ads and algorithms are constantly pushing products at you, but an agent would act for you and would filter out all that manipulative content.”

Ultimately, brands will have to adjust messaging to appeal to agents as their recommendations will become the new sponsored search results. “Brands need to optimize for machine readability and agent trust,” Snyder added. “That means structured data provenance, ethical sourcing, health compatibility, ethical compatibility, all of those things.”

This shift to agents has huge implications for online marketing more broadly, too.

“My big existential question for retailers is if human eyeballs are not going to your website or app anymore because an agent is doing it for them, what happens to retail media? What happens to onsite sponsored product ads?” Masters asked. “You’re not going to see those ads. So that whole onsite retail media business model is threatened and, to some degree, what's called offsite retail media is threatened as well.”

Her advice to retailers is to really think about what distinguishes them from their competitors—and to invest in loyalty programs as a “moat.”

For Snyder, it will be the end of the marketing funnel, but consumer experience remains. That means brands and marketers will be wise to focus on brand communities, content ecosystems, and live events.

Lisa Lacy is a freelance writer based in Atlanta. She was formerly ADWEEK's commerce editor, focusing on retail and the growing reach of Amazon. She has covered marketing and technology for more than a decade for publications like TechCrunch, CMO.com, VentureBeat, The Wall Street Journal, Dow Jones Newswires, ClickZ and Search Engine Watch.

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