A quiet but radical shift in Amazon’s role

Amazon has quietly taken a decisive step toward becoming the AI “switchboard” of e-commerce, not just a marketplace that sells its own inventory and third‑party listings. By expanding its Shop Direct program to accept product feeds from outside merchants and commerce platforms, Amazon is now wiring its AI shopping layer directly into other retailers’ catalogues across the open web.

On paper, this sounds like a technical upgrade. In practice, it rewires how product data moves, how shoppers discover items, and who actually owns the customer relationship in an AI‑driven economy.

What Amazon actually changed

Shop Direct started as a way for Amazon shoppers in the United States to discover and buy products that are not sold on Amazon’s own marketplace. Now, Amazon is broadening access by allowing merchants to connect third‑party product feeds, plugging their full catalogs into Amazon’s AI‑powered discovery surfaces.

• Merchants can now connect feeds from providers like Feedonomics, Salsify, and CEDCommerce, sending Amazon real‑time inventory, price, and catalog data.
  
• Shoppers see these products directly inside Amazon search and through its AI shopping assistant, Rufus.
  
• When they tap on an item, they can either click “Shop” to buy on the merchant’s own site or, in some cases, click “Buy for Me” so Amazon completes the purchase on their behalf.
  

Amazon’s own description is blunt: these third‑party feeds are becoming the backbone of the Shop Direct experience, and more feed providers plus a dedicated merchant portal are already on the roadmap.

From marketplace to AI distribution layer

For years, Amazon’s commerce business rested on two pillars: its own retail operations and its marketplace of millions of third‑party sellers. Third‑party merchants already account for more than half of the products sold on Amazon, and Amazon has deployed a growing range of AI tools to help them generate product listings, images, and even manage operations.

The latest move is different. Instead of insisting that the product “lives” inside Amazon’s marketplace, Amazon is positioning itself as an AI‑powered discovery and transaction layer that routes demand to external stores. That shift has at least three strategic implications:

1. Amazon starts to monetize discovery, not just the transaction it hosts. By inserting its AI assistant and search into the earliest stages of product discovery, Amazon can capture value even when the final transaction happens on a merchant’s own site.
   
2. Retailers gain access to Amazon’s traffic without ceding full control of the brand experience. For merchants who have resisted listing on Amazon, Shop Direct offers a middle path: use Amazon’s reach, keep your own storefront.

3. The AI assistant becomes the real “home page” of shopping. As Amazon layers generative AI into discovery and decision‑making, the shopper may never mentally distinguish between an item sold on Amazon and one fulfilled by an outside retailer.
   

A decade ago, marketplaces fought to aggregate inventory. Now the battle is shifting to who owns the AI layer that understands intent, interprets product data, and guides the shopper to a decision.

How the new feeds work under the hood

The technical piece matters, because it quietly defines power in this new ecosystem. Product feeds have long been the plumbing behind marketplace listings, price comparisons, and ad campaigns. Amazon is now standardising that plumbing for Shop Direct.

• Providers like Feedonomics, Salsify, and CEDCommerce already sit between thousands of merchants and platforms, normalising catalogue data and syncing it across channels.
  
• By integrating those feeds, Amazon gains structured, machine‑readable data at scale: titles, attributes, images, real‑time stock levels, and pricing.
  
• That data then feeds Amazon’s AI models, which power search ranking, recommendations, and Rufus’s conversational answers.
  

In Amazon’s own framing, merchants supply the feeds; Amazon supplies the AI‑driven discovery and, increasingly, the agent that can act on the shopper’s behalf.

It is not hard to imagine Amazon’s internal math. If even a small fraction of the millions of SKUs flowing through these partner feeds convert via Shop Direct, Amazon gains fresh data on browsing, price sensitivity, and product performance with limited inventory risk.

The shopper’s new journey: AI first, channel later

For customers, the promise is simple: ask once, get the right product, regardless of who sells it. Amazon has been laying the groundwork for this journey over the past two years:

• It started rolling out generative AI tools to deliver more personalised recommendations on the homepage, drawing on browsing and purchase history rather than just “similar items”.
  
• It launched AI‑powered tools for sellers, including listing generators that can create up to roughly 70 percent of a product detail page from a short description, URL, or image, plus new creative tools for ads.
  
• It introduced Rufus, an AI assistant that can guide shoppers across categories, answer questions in natural language, and recommend products accordingly.
  

Shop Direct slots into this stack as the bridge between AI intent and external inventory. A customer might ask Rufus something as broad as “I need a mid‑range treadmill for a small apartment, under 700 dollars.” The assistant can now surface both Amazon listings and relevant offers from outside retailers whose feeds are synced into the system, with options to either stay in Amazon’s ecosystem or jump out to complete the purchase.

In effect, the funnel flips. Instead of shoppers typing a product query into multiple sites, the AI agent handles the legwork and chooses the most relevant mix of sources. For retailers, that means the real competition is not “who has the better product page” but “who has cleaner, richer, and more AI‑readable data flowing into Amazon’s feeds.”

Who wins: marketplace sellers, brands, or external retailers?

The benefits and risks of this shift will not fall evenly.

For marketplace sellers already on Amazon

Existing third‑party sellers are not being pushed out, but they now share space with a new kind of competitor: external merchants whose products can appear in the same AI‑curated experiences without listing directly on Amazon..

On the plus side, Amazon is heavily investing in AI to support these sellers:

• Around 1.3 million third‑party sellers have already used Amazon’s generative listing tools, which can automatically draft most of a product listing and reduce time‑to‑market.
  
• New tools such as Project Amelia act as an AI “selling expert” for merchants, spotting issues, suggesting actions to grow revenue, and even taking some actions autonomously.
  

For these sellers, the priority is clear: lean into Amazon’s AI ecosystem, make listings as machine‑friendly as possible, and treat Rufus and other AI surfaces as the new shelf space.

For brands and retailers outside Amazon

For independent brands and larger retailers that have historically kept Amazon at arm’s length, Shop Direct offers both an opening and a dilemma.

• Opening: They can tap into Amazon’s hundreds of millions of customers without giving up their own checkout and full brand experience.
  
• Dilemma: To benefit, they must hand Amazon granular data on pricing, assortment, and availability, and accept that the first point of interaction is mediated by Amazon’s AI, not their own channels.
  

One commerce executive at a mid‑sized retailer, speaking hypothetically, might put it this way: “You get access to a firehose of qualified traffic, but you are training someone else’s AI on your business.” That trade‑off will define a lot of boardroom conversations in the months ahead.

For customers

Customers stand to gain more choice and, potentially, better prices, since AI can surface alternatives that sit outside Amazon’s own marketplace. The risk is subtle: the more shoppers grow accustomed to asking a single AI assistant for purchase decisions, the less likely they are to comparison‑shop across multiple sites on their own.

Put differently, the friction that once protected diversity of retail discovery is being smoothed away.

Follow the data: what Amazon really wants

Looking past the product names and program branding, Amazon’s strategic pattern around AI is consistent.

• Acquire more structured product data across brands, sellers, and now external retailers through standardized feeds.
  
• Acquire more behavioral data across the whole journey, from query to click to purchase, even when the transaction happens off‑site.
  
• Use generative AI models to sit on top of that data, personalizing discovery and automating routine work for both shoppers and sellers.
  

At Amazon’s seller events and AI announcements, the company has repeatedly highlighted tools that remove “tedious tasks” from merchants, from listing creation to stock management to creative production. It has also rolled out AI‑powered advertising products that extend Sponsored Product ads beyond Amazon to external websites, allowing brands to reach shoppers where they already are.

Shop Direct’s feed expansion is a natural extension of that story. The more channels Amazon’s AI can see and influence, the more valuable its optimization engine becomes.

A simple framework: the new AI retail stack

To understand where this is heading, it helps to break the emerging AI retail stack into four layers:

1. Data layer: product and customer signals
   Product attributes, availability, prices, and content flow in from sellers, brands, and now external merchants via standardized feeds and integrations. At the same time, behavioral data on searches, views, and purchases flows back through Amazon’s interfaces and AI assistants.
   
2. Model layer: generative and predictive AI
   Amazon’s generative models power content creation for listings and ads, while predictive models support ranking, recommendations, and merchandising. Tools like Project Amelia layer on top as always‑on advisors for sellers.
   
3. Interface layer: search, chat, and visual discovery
   Rufus, AI‑enhanced search, and features like visual scanning all sit at this level, interpreting intent and returning curated selections across Amazon and now external stores.
   
4. Transaction layer: on‑site checkout or “Buy for Me”
   Finally, the purchase can either happen on Amazon, on the merchant’s own site, or through delegation to an Amazon agent that completes the checkout on the shopper’s behalf.
   

Once that stack is in place, the exact location of the shopping cart matters less than who operates the AI layer that orchestrates discovery and fulfillment. That is the position Amazon is clearly aiming to secure.

Strategic questions for the rest of the market

For retailers, brands, and even rival marketplaces, Amazon’s expansion of AI‑driven product feeds raises a set of hard questions.

• How much AI intermediation can you accept?
  Every time a retailer connects its feed to Amazon, it gains potential demand, but it also trains Amazon’s systems to better understand its catalog, pricing behavior, and customer appeal. That knowledge can later inform Amazon’s own assortment strategies or be used to re‑rank competitors.
  
• Can you build your own AI discovery surface fast enough?
  Many retailers are experimenting with their own chat assistants and AI search features. The challenge is scale. Amazon’s models are trained on billions of interactions; smaller players may not have enough data to compete on relevance and personalization without partnering.
  
• What happens to customer loyalty when AI is the front door?
  If shoppers increasingly ask an AI agent what to buy instead of starting with a favorite retailer, brand equity risks being filtered through someone else’s recommendation engine. Over time, that can compress margins and reduce differentiation.
  

A small but telling example

Consider a mid‑sized home furnishings retailer that has never sold on Amazon. Its team already maintains product feeds for advertising and marketplace partners, handled by a platform like Feedonomics or Salsify.

With Amazon’s new Shop Direct capabilities, that same retailer can flip a switch in its feed solution so that its catalog becomes visible inside Amazon’s AI shopping experiences. A customer searching through Rufus for “Scandinavian‑style oak coffee table under 300 dollars” now sees the retailer’s product alongside items sold directly on Amazon.

The retailer gains:

• Incremental high‑intent traffic from shoppers who may never have visited its site directly.
  
• The ability to keep its own checkout, branding, and post‑purchase communication.
  

Amazon gains:

• Detailed data on the retailer’s assortment and pricing.
  
• Signals on how often that retailer’s products win clicks and conversions against its marketplace sellers.
  
• A stronger case for itself as the AI entry point to home furnishings, not just a single destination site.
  

No single integration is transformative on its own. At scale, however, thousands of such relationships can reshape the gravity of global ecommerce.

What to watch next

Several early indicators will show how ambitious Amazon’s vision really is.

• Merchant portal rollout and feed partnerships. Amazon has already signaled plans for a dedicated portal and support for more feed providers. The speed and breadth of this rollout will hint at whether Shop Direct is meant to be a niche program or a mainstream on‑ramp for global retailers.
  
• Expansion beyond the US and new verticals. If Amazon extends Shop Direct’s AI‑powered discovery model into more countries and categories, it would further cement its role as a cross‑border demand router rather than a country‑by‑country marketplace.
  
• Tighter coupling with Amazon Ads. Amazon has already pushed Sponsored Product ads to external sites, allowing brands to reach shoppers off Amazon while still leveraging Amazon’s ad stack. It is logical to expect deeper integration between Shop Direct feeds, ad targeting, and AI‑generated creatives over time.
  
• Regulatory and competition scrutiny. As Amazon’s AI shifts from recommending products in its own store to steering demand across the broader web, regulators may ask fresh questions about data access, ranking transparency, and potential conflicts between favoring internal versus external inventory.
  

Amazon is turning AI into the new infrastructure of retail

Amazon’s decision to open its AI shopping experiences to outside merchants through standardized product feeds is more than a feature launch. It is a strategic bet that in the next phase of e-commerce, the real power will lie not in owning every transaction, but in owning the AI layer that mediates discovery, intent, and trust.

For merchants, the choice will not be simple. Plugging into Amazon’s AI shop doors offers access to vast demand and increasingly sophisticated tools, from generative listing creators to seller‑side AI agents. It also means ceding more visibility into their business and accepting that, for many customers, the conversation with Amazon’s AI will come long before any direct interaction with their own brand.

The next few years will show whether retailers choose to meet Amazon’s AI on their own terms, build serious alternatives, or quietly let one company become the operating system of everyday shopping. What is already clear is that product feeds were once back‑office plumbing. In Amazon’s new configuration, they are becoming front‑line infrastructure for who controls the future of ecommerce.

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