Amazon Rufus Is Gaining Traction. Brands Need To Pay Attention.

Amazon Rufus is starting to look less like a novelty and more like one of the most important new surfaces in eCommerce. For the last year, most brand conversations around AI search have focused on ChatGPT, Gemini and Google AI Overviews. That makes sense. Those platforms are reshaping how people discover information, compare options and build consideration sets. But there is another shift happening inside the place where many shoppers are already closest to purchase: Amazon. Rufus, Amazon’s AI-powered shopping assistant, is gaining traction. It is being used by real shoppers, inside real purchase journeys and increasingly around moments where a customer is close to making a decision. For brands that sell on Amazon, that matters. Rufus is not just another chatbot. It is an AI shopping interface sitting inside the world’s most powerful retail marketplace. It can help customers compare products, understand features, ask practical questions and move from uncertainty to purchase. The old Amazon playbook was built around search rank, reviews, price, images, content and ads. Those still matter. But AI shopping assistants add another layer. The question is no longer only, “Do we rank for the keyword?” It is also, “Does Amazon’s AI understand our product well enough to recommend it, explain it and defend it in the moments that matter?” **That is the new visibility challenge.** Amazon is putting AI deeper into the shopping journey Amazon’s Q1 2026 results made the direction clear. The business is growing strongly, but the more interesting signal for brands is how deeply AI is now being woven across Amazon’s customer, seller and advertiser ecosystem. Amazon reported Q1 2026 net sales of $181.5 billion, up 17% year on year. North America sales grew 12% to $104.1 billion, International sales grew 19% to $39.8 billion and AWS grew 28% to $37.6 billion. Operating income rose to $23.9 billion, compared with $18.4 billion in Q1 2025. This is not a company cautiously testing AI at the edges. Amazon also said its free cash flow decrease was driven mainly by a $59.3 billion year-on-year increase in property and equipment purchases, primarily reflecting investments in artificial intelligence. The AI infrastructure story matters because Rufus is not an isolated product. It sits inside a broader Amazon AI system that includes AWS, Bedrock, Amazon Ads, Seller Central, Creative Agent, Alexa+ and new customer-facing shopping experiences. In the same Q1 release, Amazon said it introduced Sponsored Products and Brand Prompts in Rufus, describing prompts as a virtual product expert that automatically surfaces relevant details and deepens shopper confidence at key moments in the shopping journey. Amazon also stated that nearly 20% of shoppers who interact with a prompt in Rufus continue the conversation about that brand. That is a major signal! Rufus is not only answering neutral customer questions. It is becoming a commercial surface where organic product understanding, brand content and paid prompts may converge. For brands, this changes the practical question from “Is Rufus interesting?” to “How do we make sure Rufus has the right information about our products when customers ask?” **The first behavioural data suggests Rufus is already meaningful** A new Gener8 report, How Amazon Shoppers Actually Use Rufus, provides one of the clearest looks so far at how shoppers are using Amazon’s AI assistant. The report is based on consented, metered panel data and focuses on Rufus usage across the US and UK. The headline is simple: Rufus has real adoption, especially in the US. Gener8 estimates that 12.1% of US Amazon shoppers use Rufus monthly, compared with 6.8% in the UK. It also reports that US users are not only adopting Rufus more broadly, they are using it more frequently. Weekly active usage in the US is 5.9% versus 2.5% in the UK and daily active usage is 2.8% versus 1.0% in the UK. For a shopping assistant that is still early in its lifecycle, those numbers are significant. The report also shows that usage is concentrated among power users. In the US, the top 10% of Amazon shoppers account for 40% of Rufus users. In the UK, the top 10% account for 34%. That matters because the most active Amazon shoppers are often the customers who buy more frequently, compare more carefully and influence category-level performance more quickly. This is how new shopping behaviours often start. They do not need to reach every customer immediately. They start with high-intent users, high-frequency users and higher-complexity shopping missions. Then the behaviour normalises. That appears to be what is happening with Rufus. It is being used when shoppers need confidence. The Gener8 report points to one of the most important conclusions for eCommerce teams: Rufus is being used to reduce purchase friction. It is not primarily being used for endless general chat. It is being used as a practical tool inside shopping journeys. Gener8 found that Rufus-enabled sessions are much longer than standard Amazon sessions, with US Rufus-enabled sessions 4x longer on average. The median difference is even more pronounced, with Rufus sessions 8.7x longer in the US. That does not mean Rufus is slowing shoppers down. It likely means shoppers are using Rufus when the purchase is more complex, when they need to compare products, or when they want enough confidence to choose. The report also found that 77% of Rufus journeys are resolved in one to two prompts. That is important. Rufus does not appear to be functioning mainly as a long-form chatbot. It behaves more like a precision layer that helps users get from question to answer quickly. In other words, shoppers are not necessarily going to Rufus to browse endlessly. They are going there to remove doubt. **That should make every Amazon brand pay attention.** If a customer asks: - “Is this suitable for sensitive skin?” - “Which of these is best for long runs?” - “Will this fit a narrow foot?” - “Compare this with the leading alternative.” - “Is this safe for children?” - “Which one is better value?” Rufus needs to understand the product, the use case, the differentiators and the evidence. If your product detail page does not make those things clear, you are leaving the answer to chance. Rufus is moving closer to the point of purchase. One of the strongest findings in the Gener8 report is that Rufus usage increases later in the shopping session. The report describes Rufus as solving “last mile friction”, with 56% of US Rufus usage occurring in the second half of the shopping journey. This is not just a top-of-funnel discovery behaviour. It is happening near the commercial decision. That matters because the closer AI assistance gets to purchase, the more commercially important the answer becomes. Traditional eCommerce optimisation has often split the funnel into discovery, consideration and conversion. Amazon compresses those stages. A shopper can move from search to comparison to add-to-basket in minutes. Rufus compresses it further by giving customers a conversational way to ask what would previously have required opening multiple product detail pages, reading reviews, scanning bullets and comparing images. That creates a new kind of “AI-mediated conversion moment”. The shopper may still see the product page. They may still read the reviews. They may still respond to price and delivery speed. But Rufus can now sit between uncertainty and purchase. For brands, that means Rufus visibility is not just about being mentioned. It is about being correctly represented when the customer is about to decide. **The US and UK Rufus usage gap is worth watching closely.** Gener8’s report shows that US shoppers are more likely to use Rufus, use it more often and use it for comparison. US Rufus users are especially focused on comparative selection, with 22% of US Rufus sessions focused on comparing products. The UK market appears more focused on practical support questions. Gener8 reports that UK Rufus usage over-indexes on technical, physical fit, usage context and suitability questions. This difference may partly reflect product maturity. The report notes that Rufus is more useful in the US because it can leverage deeper account data and persistent memory, including past purchases, browsing history, delivery preferences and household composition. In the UK, Rufus is described as more frequently defaulting to generic product or simple link-based assistance. **One of the more surprising findings from the Gener8 report is demographic.** Rufus adoption appears to be strongest among older shoppers. The report says Baby Boomers and Gen X show the strongest Rufus engagement, with adoption peaking among older demographics. Retired shoppers also show strong adoption across both US and UK markets. That cuts against the lazy assumption that AI shopping assistants are mainly for young early adopters. In reality, Rufus may be especially useful for shoppers who want a simpler way to navigate crowded product pages, dense reviews and complex product choices. This matters for category strategy. If your brand sells in a category where customers need reassurance, guidance, comparison or explanation, Rufus may become more important than expected. That includes health, beauty, pet care, electronics, home improvement, baby, sports nutrition, footwear, supplements, appliances and any category where product choice carries a perceived risk. The more complicated the decision, the more useful an AI shopping assistant becomes. **Closing remarks ** Amazon’s Q1 results show a company investing heavily in AI, growing its advertising business and embedding AI into shopping, selling and customer experiences. The Gener8 data shows that shoppers are already using Rufus in meaningful ways, especially in the US and especially around decision-making moments. This is the signal brands should not ignore. Rufus is not replacing Amazon search yet. But it is becoming a new layer on top of it. And in eCommerce, new layers of customer attention become new layers of competition. The brands that act now will build an advantage while the rules are still being written. The brands that wait will be asking why Amazon’s AI understands their competitors better than it understands them.