Amazon's AI shopping assistant is seeing significant adoption, and shoppers who use it spend more. Here's what the latest numbers reveal about the future of product discovery on Amazon.
Amazon just gave brands another reason to take AI-powered shopping seriously.
During its Q3 2026 earnings announcement, Amazon revealed that more than 400 million customers had used Alexa for Shopping over the previous 12 months. Customer interactions with the AI shopping assistant also increased 570% year over year.
And perhaps the most interesting number? According to Amazon, customers who use Alexa for Shopping spend 50% more than those who don't.
That's a pretty compelling set of statistics for a technology that many brands are still trying to figure out.
But before marketers start rewriting their entire Amazon strategy around AI shopping, there's an important distinction worth making: Alexa for Shopping isn't necessarily creating all that additional spending. But it's becoming part of how some of Amazon's most valuable customers shop.
And that's a development brands can't afford to ignore.
Amazon's AI Shopping Assistant Is Gaining Serious Traction
Alexa for Shopping, previously known as Rufus, was designed to help shoppers ask product-related questions, compare options and find items based on their specific needs.
Amazon rebranded Rufus to Alexa for Shopping earlier this year, bringing its AI shopping experience under a name consumers already recognized. Since then, the company has continued expanding its capabilities. During its latest earnings announcement, Amazon reported:
- More than 400 million customers used Alexa for Shopping over the last 12 months.
- Customer interactions increased 570% year over year.
- Customers who use Alexa for Shopping spend 50% more than those who don't.
- More than 100 new capabilities have been introduced, including conversational gift list management, Subscribe & Save updates and account-related tasks.
These numbers suggest conversational shopping is becoming a meaningful part of Amazon's experience, but they don't prove AI is driving higher spending. More engaged shoppers may simply be more likely to use Alexa for Shopping. Either way, adoption suggests AI-assisted shopping is moving beyond experimentation.
Product Discovery Is Becoming a Conversation
Think about how shoppers traditionally find products on Amazon: they enter a keyword, scroll through search results, compare listings, read reviews and narrow their options.
That process isn't disappearing, but Alexa for Shopping introduces another way to navigate it.
Instead of searching for "coffee maker," a shopper might ask for a compact coffee maker that fits under kitchen cabinets, costs less than $150 and doesn't require expensive replacement pods. Rather than manually filtering through dozens of listings, the shopper can describe what matters and let the assistant help narrow the options. That's a meaningful change in how product discovery works.
Traditional keyword search depends heavily on matching a shopper's query to relevant products, but conversational shopping creates opportunities for more specific recommendations based on attributes, use cases, preferences and follow-up questions.
And those recommendations depend on how well Amazon's systems understand the products available. For brands, that makes product information more important than ever.
Amazon Is Already Bringing Advertising Into AI Shopping Conversations
For advertisers, the bigger story isn't just that more consumers are shopping with AI. It's that Amazon is already building advertising into those conversations.
Existing Sponsored Products and Sponsored Brands campaigns are automatically eligible to appear within Alexa for Shopping conversations, giving brands another opportunity to reach shoppers as they research and compare products.
Amazon is also experimenting with ways to keep shoppers engaged beyond the initial ad. Sponsored Products and Sponsored Brands prompts encourage consumers to ask follow-up questions, and Amazon reports that nearly 20% of shoppers who engage with these prompts continue the conversation about the brand. Adding prompts to Sponsored Brands ads has also driven a 6% lift in conversions.
And the opportunity extends beyond the shopping experience itself. Alexa+ Conversational Ads bring brand messaging into Alexa+ conversations on supported devices through audio and static placements, with eligible sponsored ads advertisers automatically enrolled.
The next evolution is coming in January 2027. Amazon's Branded Conversations offering will allow brands to contribute their own product expertise to Alexa's responses. Think recommendations for specific skin types, explanations of product benefits or suggestions for which products work best together.
For marketers, this changes the conversation around visibility. It's no longer just about appearing in search results or winning a sponsored placement. It's increasingly about making sure shoppers get useful, accurate information about your products when they're actively considering what to buy.
Amazon is also pushing beyond product discovery into transactions. Its Alexa+ Agentic Ads already allow consumers to complete certain purchases, including food orders and event tickets, directly within a conversation without navigating to another site.
The takeaway? Conversational commerce isn't a future advertising opportunity. It's already here. And with Branded Conversations launching in January, brands will have more ways to influence how their products are explained, compared and considered at the moment shoppers are making decisions.
Three Priorities for Brands Selling on Amazon
1. Audit your product content through the lens of real shopper questions
For years, brands have optimized Amazon listings around search relevance, conversion and retail readiness. Don't get us wrong: those fundamentals still matter.
But AI-powered shopping introduces another consideration: Is your product information detailed and clear enough to answer increasingly specific shopper questions?
Consider someone looking for a protein powder that's dairy-free, low in sugar and suitable for baking. A listing that emphasizes "great taste" and "premium ingredients" might not provide enough information to answer those questions. But a listing that clearly communicates dietary attributes, nutritional information and use cases gives AI shopping assistants more relevant information to work with.
That doesn't mean stuffing listings with every possible keyword. It means making sure your product content answers the questions shoppers are actually asking.
Brands should be looking at:
- Product titles and attributes: Are important features and differentiators accurately represented?
- Bullet points and descriptions: Does your listing answer specific questions about who the product is for, what it does and why someone should choose it?
- Images and enhanced content: Are product benefits and use cases clearly communicated?
- Reviews and customer questions: What are shoppers asking that your existing content doesn't address
- Retail readiness: Are products consistently available, competitively priced and supported by accurate information?
Amazon hasn't disclosed exactly how Alexa for Shopping weighs these inputs when making recommendations. But complete, accurate product information is a smart place to start.
2. Start testing how your products appear in AI shopping experiences
Brands don't need to wait for a perfect AI visibility measurement tool to begin learning.
Start by creating a consistent set of realistic shopping prompts based on your products, categories and customer needs. Think beyond broad searches like "best protein powder" to more specific questions about ingredients, use cases, product comparisons and purchase considerations.
Look at which products are recommended, how they're described and whether important attributes are represented correctly. Are competitors showing up when you're not? Is the AI accurately communicating what makes your product different?
Repeat those tests over time to identify patterns and potential gaps, and even consider doing this across other AI sources.
Results can vary based on the prompt, shopper context and other factors, so individual tests shouldn't be treated as definitive rankings. But a structured approach can help brands better understand how their products are represented as AI-assisted discovery grows.
3. Keep advertising, content and retail operations connected
AI shopping doesn't eliminate the need for strong retail fundamentals. If anything, it makes the connection between advertising, product content and retail operations even more important.
Amazon is already incorporating Sponsored Products and Sponsored Brands into Alexa for Shopping conversations, and its upcoming Branded Conversations offering will give brands another way to contribute product expertise to AI-powered responses.
That means the information brands provide about their products, the messages they promote through advertising and the experience shoppers have when they're ready to buy all need to work together.
A compelling recommendation won't mean much if the product is out of stock, priced uncompetitively or missing the information a shopper needs to make a decision. And a strong product listing can only do so much if shoppers never discover it in the first place.
The opportunity isn't to abandon existing Amazon strategies in favor of AI. It's to make sure your advertising, content and retail operations are working together to support how consumers are increasingly discovering, evaluating and purchasing products.
Alexa for Shopping Is Becoming Harder to Ignore
Four hundred million customers is a significant audience, but the bigger story isn't simply how many people have tried Amazon's shopping assistant.
It's that Amazon is continuing to invest in making AI part of the everyday shopping experience, from discovering products to managing purchases and subscriptions.
For brands, the immediate priority isn't abandoning traditional Amazon SEO or advertising strategies.
It's making sure those strategies are ready for a shopping experience where consumers increasingly describe what they want rather than search for it one keyword at a time.
The brands that win won't necessarily be the ones with the most keywords. They'll be the ones that make it easiest for shoppers, and the systems helping them, to understand why their products are worth choosing.