AI Shopping Agents Retail Media: Inside the $74B Disruption

Amazon and Walmart built two of the most profitable advertising businesses in the world on a simple bet: shoppers scroll, shoppers see ads, shoppers buy. That bet is now being tested by software that does not scroll, does not get distracted, and does not click on sponsored listings. AI shopping agents retail media disruption has moved from theoretical to measurable in a matter of weeks, and the numbers behind it are big enough to force two of the world's largest retailers into opposite strategic bets.

Together, Amazon and Walmart control an estimated 88% of the $74.4 billion U.S. retail media market, according to projections from research firm eMarketer. That business depends on one unspoken assumption: a human is doing the looking. Consumers can outsource the search and purchase of products using these platforms, potentially limiting their exposure to sponsored items on retailers websites. When the buyer is an algorithm instead of a person, the entire monetization model built around attention and impulse starts to wobble.

This is not a distant, hypothetical shift. A new 2026 Peak Benchmark finds AI agent sessions grew 25x in under a year, and more than 1 in 4 AI-related sessions now come from AI assistants that browse alongside shoppers. Morgan Stanley analysts go further, projecting agentic software could handle a meaningful share of all U.S. online spending within a few years. According to estimates by Morgan Stanley analysts, by 2030, AI agents could account for 10–20 per cent of e-commerce spending in the US.

Matt Britton has spent two decades tracking exactly this kind of inflection point, where a new technology moves from novelty to P&L threat almost overnight. As founder of Suzy and author of Generation AI, Britton built his reputation studying how emerging consumer behavior forces boardrooms to rethink strategy before the data fully catches up. He argues this retail media story is the clearest proof point yet that agentic AI is not a marketing trend, it is a governance problem that touches every Fortune 500 category, not just retail.

This post breaks down what AI shopping agents actually are, why Amazon and Walmart chose opposite paths in response, and what the governance question at the center of this shift means for CMOs, CFOs, and boards watching from adjacent industries.

What AI Shopping Agents Retail Media Disruption Actually Means

An AI shopping agent is software, often built on a large language model, that researches products, compares prices, and in some cases completes a purchase on a consumer's behalf, with little or no human browsing involved. Unlike a search engine that shows a human a list of options, an agent evaluates those options itself and acts. That distinction is the entire source of the disruption.

Retail media, the business of selling placement and sponsored listings to brands, only works if a human eyeball passes over the ad. AI shopping agents could erode that business, because an agent that researches and buys products for a consumer has little reason to look at an ad. That single sentence explains why a $74.4 billion business is suddenly on edge.

The scale of the retail media market makes the stakes concrete. Emarketer forecasts that brands will spend 22.6% more on retail media in 2026 than the $60.7 billion recorded last year. That growth trajectory assumes the current model, humans browsing, humans clicking, humans getting nudged by a sponsored product, stays intact. Agentic commerce is the first real-world test of whether that assumption still holds.

Britton frames this as the opening chapter of a much longer story he covers in his AI keynote presentations for enterprise audiences: every industry built on human attention, from media to finance to real estate, will eventually face its own version of this moment. Retail just happens to be first because the purchase transaction is the easiest thing for an agent to automate.

Amazon vs. Walmart AI Strategy: Two Opposite Bets on Agentic Commerce

Faced with the same threat, Amazon and Walmart chose almost opposite responses, and that divergence is itself a case study every CMO should study closely. Amazon moved to restrict outside access. Amazon blocked Meta's AI shopping agent Muse from accessing its website in September, alleging that it had accessed the platform without authorisation and captured and stored customer credentials. The message was clear: Amazon wants to control exactly how AI interacts with its storefront, on its own terms.

Walmart went the other direction. On October 21, the retailer introduced infrastructure allowing third-party AI agents to browse its store through profiles linked to shoppers' Walmart accounts. Rather than fight the shift, Walmart built guardrails around it. Walmart launched infrastructure that lets third-party agents browse, with profiles linked to shoppers' accounts; consumers can approve purchases or set spending limits.

Both companies are also hedging by building advertising directly into their own AI tools. Amazon has already incorporated advertising into its own AI shopping tools, while Walmart is experimenting with sponsored content inside Sparky, its shopping assistant. That is a telling detail: neither company believes retail media disappears, both believe it has to move inside the agent experience itself rather than live on the webpage around it.

So far, the business impact looks modest but not zero. Amazon's CEO Andy Jassy stated last week that third-party AI agents are not yet having a significant impact on the company's advertising business. But Amazon's own ad numbers tell a slightly different story underneath the surface. Amazon's ad revenue grew 11% in the third quarter, its slowest pace in nearly four years. That slowdown alone will not be blamed entirely on agents, but it is the kind of early signal that gets a board's attention.

Britton's take, delivered frequently on The Speed of Culture podcast, is that the Amazon-versus-Walmart split previews a decision every brand will eventually face: do you build a moat around your customer relationship, or do you build a bridge to the agents your customers are already trusting with their money?

The Real Governance Question: Who Owns the Customer When the Customer Is an Algorithm

The technology headlines focus on bots and browsers. The real strategic question, the one Britton pushes Fortune 500 audiences to confront, is about control. When an AI agent researches, compares, and buys on a consumer's behalf, who actually owns that customer relationship: the retailer, the agent's developer, or the brand whose product got picked?

This is not just a retail problem. Real estate firms already face agentic tools that pre-screen listings before a human ever sees them, which is why Britton built out dedicated guidance for that sector through his real estate AI keynote work. Financial services firms are watching the same dynamic play out in robo-advisory and automated comparison tools, a topic Britton addresses directly in his finance industry keynote programs. The pattern repeats: whoever controls the agent increasingly controls the transaction.

Industry voices expect the business model to evolve rather than vanish, but the shape of that evolution is still being negotiated in real time. Industry experts expect retail media to evolve rather than disappear, with advertising potentially moving towards systems where brands compete to have products recommended by AI agents. That is a fundamentally different advertising product than a banner ad or sponsored search placement. It requires brands to optimize for being chosen by a machine, not just noticed by a human.

Retail media executives are already adjusting their playbooks around this uncertainty. Dan Marc, CEO of retail media platform Footprints AI, expects Amazon and Walmart to sign their biggest advertisers to multiyear deals, and expects more discounting on digital retail media as shoppers turn to chatbots and agents. Locking in big spenders with long contracts is a defensive move, a hedge against a future where the old auction-based ad model no longer guarantees exposure to a human buyer.

Britton argues the companies that win this next phase will be the ones that treat agent relationships the way they once treated search engine optimization: not as a side project for the marketing team, but as a board-level priority with its own budget, metrics, and executive owner.

AI Consumer Behavior 2026: What the Data Actually Shows

Beyond the Amazon and Walmart headlines, broader consumer research confirms the behavioral shift is already underway and accelerating. Quantum Metric's newest benchmark data captures just how fast agent-driven browsing has scaled. New 2026 Peak Benchmark finds AI agent sessions grew 25x in under a year, and more than 1 in 4 AI-related sessions now come from AI assistants that browse alongside shoppers.

Interest in traditional sales moments is not disappearing, but it is being reshaped by generational differences. 28% of consumers are paying more attention to Cyber 5 this year, rising to nearly 40% of Gen Z and Millennials. That split matters: younger shoppers are both more engaged with sale events and more likely to let AI do the comparison work before they ever visit a site, a dynamic Britton unpacks in depth through his Gen Z consumer behavior keynotes.

Separate Quantum Metric research shows AI-referred traffic behaves nothing like traditional traffic once it arrives. Shoppers who come from AI platforms tend to be further along in their decision, more informed, and far less patient with friction. Customers who use AI-powered discovery are two times more likely to abandon their cart if they experience friction, and four out of five consumers say they won't return to a brand they discovered through AI if they have an issue with the experience. That loyalty paradox, loyal to the agent's recommendation but unforgiving of the brand's execution, is exactly the kind of nuance Britton's team models for enterprise clients through the Suzy consumer intelligence platform.

The advertising dollars at stake are not theoretical either. Advertising regularly contributes about 10% of Amazon's total net sales. A disruption to even a fraction of that revenue line is the kind of number that moves quarterly earnings calls, not just trend reports.

Retail Media Disruption: A Framework for Fortune 500 Leaders

Matt Britton advises enterprise leaders to stop treating agentic commerce as a future problem and start building infrastructure now, before the next earnings cycle forces the issue. Based on how Amazon, Walmart, and category leaders in adjacent industries are responding, four priorities stand out:

• Audit your agent exposure. Identify which third-party AI tools already interact with your product listings, pricing, and checkout flow, authorized or not.
• Decide your governance posture early. Choose deliberately between an Amazon-style restrictive approach and a Walmart-style open infrastructure approach, rather than letting the decision happen by default.
• Rebuild your media mix for machine discovery. Structured product data, clear specifications, and review quality increasingly matter more than banner placement when the buyer is an algorithm.
• Protect the human handoff. Since AI-referred shoppers abandon fast when friction appears, checkout experience and account linking need the same investment as the agent relationship itself.
• Put a named executive in charge. Agentic commerce strategy cannot live inside a marketing subcommittee; it needs direct reporting to the C-suite, the same way ecommerce did in its early years.

These are the exact frameworks Britton builds into his enterprise engagements, available through his speaker platform, where Fortune 500 teams get a customized briefing on how agentic disruption maps onto their specific category.

Key Takeaways for Business Leaders

• Recognize that AI shopping agents directly threaten the attention-based model behind the $74.4 billion U.S. retail media market.
• Monitor both the Amazon restrictive model and the Walmart open-access model as two viable, opposite playbooks worth testing in your own category.
• Prioritize the governance question of who controls the customer relationship before a competitor or platform answers it for you.
• Invest in structured, machine-readable product data now, since agents reward clarity over creative ad placement.
• Assign executive ownership of agentic commerce strategy at the same level your organization once assigned digital transformation leadership.

Frequently Asked Questions

What are AI shopping agents and how do they affect retail media?

AI shopping agents are software tools that research, compare, and sometimes purchase products on a consumer's behalf, often without the shopper ever viewing a webpage. Because retail media revenue depends on human eyeballs seeing sponsored listings, agents that skip the browsing step reduce ad exposure, directly threatening the $74.4 billion U.S. retail media business that Amazon and Walmart dominate.

Why did Amazon block Meta's AI shopping agent while Walmart welcomed similar tools?

Amazon blocked Meta's Muse agent after alleging unauthorized access and improper handling of customer credentials, choosing a restrictive, control-first approach. Walmart instead built infrastructure allowing approved third-party agents to operate through linked customer accounts with spending limits, betting that partnership preserves more long-term value than blocking access outright.

How much of e-commerce spending could AI agents control by 2030?

Morgan Stanley analysts estimate AI shopping agents could account for 10% to 20% of total U.S. e-commerce spending by 2030. Combined with data showing AI agent browsing sessions grew 25 times in under a year, this suggests agentic commerce is moving from early experimentation to a mainstream purchasing channel far faster than most retail and advertising forecasts anticipated.

What should CMOs do now to prepare for agentic commerce disruption?

CMOs should audit which AI agents already interact with their brand's product data, decide on a clear governance posture toward third-party agents, and invest in structured product information that machines can easily evaluate. Equally important is protecting the checkout experience, since AI-referred shoppers abandon purchases quickly when they encounter friction.

The Window to Act Is Now

The Amazon and Walmart divergence is not an isolated retail story, it is a preview playing out in real time for every industry built on human attention and advertising dollars. Matt Britton has built his career identifying exactly these inflection points before they show up on a quarterly earnings call, and this one is moving faster than most. The companies that wait for perfect data before deciding their agentic commerce governance posture will find the decision made for them by competitors, platforms, or the algorithms themselves.

Britton's keynote work, detailed through his Generation AI book and enterprise briefings at mattbritton.com/speaker-hq, gives Fortune 500 leaders the specific frameworks to answer the governance question before it becomes a crisis. For organizations ready to understand what agentic disruption means for their category specifically, booking Matt Britton for a keynote or executive briefing is the fastest way to turn this uncertainty into a competitive advantage.