Inside marketplace AI agents: what they mean for your brand

AI shopping agents aren’t just changing how people shop,  they’re changing who does the shopping in the first place. And nowhere is that shift happening faster than inside the world’s biggest ecommerce marketplaces.

Across Amazon, Walmart, Target, eBay, Lowe’s, and others, a new generation of AI assistants is stepping into the role once held by search bars, filters, comparison grids, and even store associates. These platforms are rebuilding the shopping journey around AI.

For brands, this creates a new kind of competition: not just winning over a human shopper, but winning over the marketplace’s own AI. The platforms are becoming curators, matchmakers, and gatekeepers, deciding which products surface, which get recommended, and which quietly fall off the consideration list.

At Pattern, we’re digging into how each marketplace is deploying these agents, what they’re optimizing for, and what brands need to do to stay in front of both shoppers and the algorithms now shopping on their behalf.

1. Amazon — “Help Me Decide”, “Rufus” & the agent-powered checkout

Amazon has been steadily weaving AI into the shopping journey, introducing tools that change how products surface and how decisions are made. Two of the most visible additions are Help Me Decide and Rufus, both designed to streamline the choice-making process for shoppers in different ways.

Help Me Decide analyzes a shopper’s browsing activity and stated preferences, then presents a single recommended product along with a clear rationale for why it matches the criteria. The feature appears once a customer has viewed multiple similar products in a category, either on the product detail page or through the “Keep shopping for…” pathway in the app.

Meanwhile, Rufus acts as a conversational guide, helping shoppers compare items, surface product features, and understand key review themes. Its role is to answer the kinds of questions customers typically ask before deciding what to buy.

These tools rely on Amazon’s broader AI infrastructure, including large language models integrated across systems like AWS Bedrock, OpenSearch, and SageMaker.

Implications for Brands

For brands selling on Amazon, these AI layers shift the emphasis from keyword-driven discovery to criteria-driven matching. Agents look for structured, consistent, and complete product information — gaps in specs, unclear claims, or inconsistent data now carry a higher cost because the AI may simply skip over incomplete listings.

Clear product details, trustworthy reviews, accurate attributes, and strong content become even more important, not just for human shoppers, but for the AI intermediaries increasingly shaping what those shoppers see. In many ways, the fundamentals stay the same, but the expectations rise: content must be both compelling for people and legible for machines.

2. Walmart – Meet “Sparky” and the agentic shopping future

Walmart has been steadily expanding its AI footprint, and its newest addition, Sparky, brings a conversational shopping assistant directly into the Walmart app. Shoppers can tap “Ask Sparky” to get help choosing products, interpreting reviews, or planning for specific occasions. Whether someone needs “gluten-free snacks for kids,” a “gift for a coworker,” or supplies for an upcoming party, Sparky’s role is to translate intent into curated product suggestions.

What makes Sparky interesting is that it’s part of a broader ecosystem Walmart is building. At its Retail Rewired event, the company outlined a set of internal and external “super-agents”. Sparky is simply the shopper-facing side of a much larger AI network designed to transform how decisions get made across the Walmart experience, from the warehouse to the shopping cart.

Implications for Brands

For brands, Sparky signals a shift toward more contextual, occasion-based shopping on Walmart. Instead of relying solely on keywords, the assistant interprets a shopper’s purpose,  the birthday party they’re planning, the home project they’re tackling, the last-minute gift they need,  and pulls together products that fit the scenario. That means listings must communicate more than just features; they need to clearly express use-cases, attributes, and the kinds of scenarios the product solves.

Sparky also weighs the same criteria human shoppers do, but faster and more consistently: price, ratings, availability, and delivery speed. If an item has incomplete data, slow shipping, or uneven reviews, the assistant may simply move on to a more reliable match. In other words, the fundamentals of marketplace success don’t change,  but the margin for error gets smaller when an AI is doing the sifting.

3. Target – The “Bullseye Gift Finder” & GenAI Shopping Assistant

Target has been steadily layering AI into the shopping experience, starting with tools that help customers narrow in on the right products faster and with more confidence. One of the clearest examples is the Bullseye Gift Finder, a generative-AI tool originally built to help shoppers choose kids’ toys. Customers can input details like age, interests, and favorite brands, and the system generates a curated list of recommendations tailored to the occasion.

Target is also testing a conversational “Shopping Assistant” embedded directly within product pages for select owned-brand items. This feature lets shoppers ask practical questions, from care instructions to ingredient specifics, and get real-time answers without leaving the product page or scrolling through reviews.

Looking ahead, Target has outlined several new AI-powered capabilities for the 2025 holiday season, including a more robust conversational Gift Finder, improved list-to-cart recognition, and in-store navigation enhancements through Store Mode. Together, these updates show Target leaning into a hybrid model where AI supports the shopper everywhere, online, in-app, and inside the physical store.

Implications for Brands

For brands, Target’s AI focus raises the importance of clarity, attributes, and transparency. Gift Finder and the product-page assistant both rely heavily on clean data, the clearer your ingredients, materials, safety features, sensory benefits, sizing notes, or functional claims, the easier it is for Target’s AI to match your product to the right customer scenario. 

And because Target’s ecosystem spans digital storefronts and physical shelves, data consistency and fulfillment reliability carry extra weight. If the AI is factoring in availability for same-day pickup or local inventory, those operational strengths (or weaknesses) may influence which products Target’s systems surface first.

4. eBay – Conversational Agent & “Shop the Look” for Discovery

eBay, with its mix of new, used, and one-of-a-kind items, is a bit of a different animal compared to the more traditional retailers. But even in this diverse marketplace, eBay is integrating AI in ways that are reshaping how shoppers discover and interact with products. One of the standout features is the conversational AI shopping assistant. Currently available to select U.S. customers, this tool offers personalized suggestions and advice directly on the page or through predictive messaging, helping buyers navigate the vast inventory eBay has to offer.

In addition to the chatbot, eBay’s “Shop the Look” feature, part of their eBay.ai initiative, takes a more visual and immersive approach to discovery. Focused particularly on fashion, this carousel-driven tool curates complete outfits based on a shopper’s history and interests, linking items together in a visually engaging way. Users can interact with product hotspots that suggest similar products or complementary pieces, giving the shopping experience a more seamless, “stylist-led” feel.

Implications for Brands

For brands selling on eBay, AI becomes less about filtering and more about discovery. With eBay’s enormous inventory of pre-owned, new, and even rare items, standing out requires more than just competitive pricing, it’s about presenting your product in a way that tells a story. The AI assistant can help surface your item, but if it’s not tagged correctly or doesn’t have enough contextual information, it could get lost in the shuffle. Content and condition matter more than ever, eBay shoppers are often searching for a story, whether it’s the history of a vintage item or the quality guarantee on a new product.

The “Shop the Look” feature, in particular, underscores how visual appeal is now critical. If your product can fit into a curated outfit or lifestyle moment, it has a much higher chance of being surfaced. For fashion brands, this means investing in high-quality images, creating outfit ideas, and thinking about how your products can tie together with others to create a complete experience. Offering bundled items, or even suggesting complementary products, could help AI agents connect the dots for shoppers.

Given eBay’s more varied marketplace, it’s also important for brands to signal trust. The resale aspect of eBay means that listings for secondhand or refurbished products will need to be clearly marked and authenticated. Certified items or products with clear quality assurance signals will likely be prioritized, especially if the buyer is looking for “trusted” or “like-new” goods.

5. Lowe’s – “Mylow” + “Mylow Companion” —  Agent Assistance for Projects

AI shopping assistants aren’t limited to traditional e-commerce giants,  they’re extending into spaces like home improvement, where the need for guidance and expertise is just as important as product selection. Lowe’s is a great example of this trend, having launched Mylow, a conversational AI assistant that helps guide customers through both product recommendations and project planning. 

Accessible on Lowe’s website and app, Mylow isn’t just about “what to buy”,  it helps customers understand how to use what they buy. It’s an AI-driven tool that gives shoppers the knowledge they need to plan and execute their home improvement projects with confidence.

But Lowe’s didn’t stop there. They also rolled out Mylow Companion, a companion tool designed specifically for in-store associates. Built using OpenAI’s technology, Mylow Companion turns every Lowe’s employee into a product expert by providing real-time answers to customer questions about inventory, product compatibility, and installation instructions. This innovation means customers have access to expert-level advice whether they’re browsing online or walking the aisles of their local store.

Implications for Brands

For brands in the home improvement and project-oriented categories, Lowe’s AI developments represent a significant shift in how products are positioned and sold. The AI is no longer just evaluating specs or price tags, it’s factoring in intent. 

Customers are looking for more than a product; they want guidance. For example, a shopper might ask, “What do I need to hang shelves in a 12 × 10 room with drywall?” In this scenario, an AI assistant would need to surface not just the right shelf brackets, but also the appropriate tools, fasteners, and perhaps instructional content to help the shopper execute their project. This means brands must begin thinking project-first, and ensure that their product data speaks directly to the needs of specific home improvement projects.

Rich, detailed product data becomes essential. Beyond basic specifications, products should include compatibility information, installation instructions, and recommendations for related products. If an agent is tasked with providing project guidance, missing context — like unclear compatibility details or insufficient how-to information — could cause your product to be overlooked.

For brands with both digital and physical store presence, the importance of data consistency increases. Product information must be seamlessly aligned between the online catalog and in-store inventory, ensuring that the customer experience is uniform across both channels. Additionally, the integration of customer reviews and installation feedback will help to build trust and enhance the likelihood that your products are recommended by Lowe’s AI.

Next steps for your brand

Here’s our actionable shortlist for brand owners who want to be ahead of the curve as AI shopping agents transform the marketplace:

1. Clean, Structured, Honest Product Data

The basics only get more important. Product titles, attributes, images, pricing, inventory, and all core details must be accurate, comprehensive, and formatted in a way that machines (not just people) can evaluate at scale. An AI agent will punish brands for outdated information or missing specs by filtering them out or ranking them lower.

2. Content That Works for Humans & Machines

Your visuals, bullet points, enhanced content should still draw in humans,   don’t lose sight of storytelling, differentiation, and trust signals like reviews and badges.

But it’s time to also ensure your content is structured for machine-readability: standardized attributes, unambiguous features, thorough FAQs, images that clearly convey what the product is and does.

Example: For a nutritional supplement (okay, theoretical since we’re not recommending regulated products), an agent might filter out if “no artificial sweeteners” isn’t clearly flagged in attributes.

3. Reputation, Reviews & Visibility

Because AI agents will weigh reviews and ratings heavily, review quality and volume matter more than ever. Stay on top of customer feedback, quickly resolve issues, and make it easy for happy buyers to leave positive ratings. Negative patterns will stand out to an agent, potentially derailing your listing instantly.

4. Price & Promo Must Be Strategic

Agents are ruthless price analysts, tracking deals, dynamic pricing, cross-site comparisons. Brands should expect even sharper competition on pricing and promo, and need to be smart about when to match, when to hold, and how to communicate value beyond just being the lowest price.

Remember: the agent may pick a higher-price item if it scores much stronger in reviews, delivery, brand reputation, and return policy.

5. Differentiate Where Agents Don’t Shine (Yet)

Yes, agents are powerful — but they aren’t perfect. The brands that win will be those that continue to build trust, tell a compelling story, deliver on promises, and create memorable human experiences.

The decision might start with an agent, but humans still control the criteria, the add-to-cart, and (crucially) the re-order.

So focus on offering: exceptional customer service, creative branding, memorable packaging, loyalty programs, community building. Agents don’t (yet) compete in the emotional narrative realm, but they will evaluate the signals you build.

Navigating the next chapter

The future of e-commerce is fast, precise, and increasingly powered by AI shopping agents. If your brand is serious about staying ahead, now is the moment to look around the corner.

What will it mean for you when the majority of buyers stop searching, scrolling and comparing for themselves, and instead send an AI agent to do the work?

‍With Pattern as your partner, your brand can meet the shopper, and their digital helper, right where they’re searching, clicking and buying next.