Amazon Rufus: What AI Search Means for Sellers in 2026

What is Amazon Rufus?

Rufus is Amazon's AI shopping assistant, a conversational interface built into the Amazon app and website where customers ask questions in natural language instead of typing keyword searches.

Instead of searching "moisturiser dry skin SPF," a shopper asks Rufus "what's the best moisturiser for dry skin that also has sun protection?" Rufus reads product listings, reviews, Q&A sections, and Amazon's product knowledge graph to generate a conversational answer with product recommendations.

Amazon launched Rufus in beta in February 2024, rolled it out to all US shoppers by mid-2024, and has since expanded to the UK, Germany, France, Italy, Spain, Canada, and India. As of late 2025, Rufus was handling over 274 million daily queries, roughly 14% of all Amazon searches. That percentage is growing fast, with some projections putting it at 35%+ of total search volume by now.

This isn't a side feature. Amazon has publicly stated that AI-powered shopping is a strategic priority. They've projected Rufus will drive $10 billion in additional annualised sales. Customers who engage with Rufus are 60% more likely to complete a purchase. Those are numbers that change how the entire platform works.

What Rufus can do now (that it couldn't before)

Rufus has evolved rapidly from a simple Q&A chatbot into what Amazon calls an "agentic AI assistant." Here's what it can do in 2026:

Answer detailed product questions. "What material is this made of?" "Is this dishwasher safe?" "How does this compare to [competitor product]?" Rufus pulls answers from your listing content, reviews, and Q&A section.

Compare products conversationally. Shoppers ask "which of these two is better for outdoor use?" and Rufus evaluates both products using listing details, review sentiment, and product specifications.

Show price history. Rufus now displays 30-day and 90-day price history to shoppers. The "was £29.99, now £19.99" trick is visible to anyone who asks. Price transparency is no longer optional.

Set price alerts. Shoppers can tell Rufus "alert me when this drops below £20" and Rufus will notify them when the price hits their target.

Auto-buy. This is the big one. Prime members can set a target price and Rufus will automatically purchase the product when it hits that price. No human action required. Amazon calls this "agentic commerce."

Reorder past purchases. "Reorder my dog food" and Rufus handles it. Repeat purchases are being automated.

Cross-ecosystem memory. Rufus is beginning to incorporate signals from Kindle reading habits, Prime Video viewing, and Audible listening to inform product recommendations. A customer reading crime thrillers on Kindle might get different gift recommendations than someone watching cooking shows on Prime Video.

Sponsored Products in Rufus. Amazon is now placing ads inside Rufus conversations. When a shopper asks "what's the best protein powder?" your Sponsored Products ad can appear within the AI response. This is currently in beta with free placements. But Amazon will monetise it.

Why this changes everything for sellers

Traditional Amazon selling has been built around one model: optimise your listing for Amazon's A10 search algorithm. Pick the right keywords, put them in the title, win the ranking, get the traffic.

Rufus doesn't replace A10. It operates alongside it. But as Rufus handles a growing share of product discovery (14% and climbing), there's a new game happening in parallel.

Three fundamental shifts:

The first shift is from keywords to questions. A10 matches keywords. Rufus matches intent. When a shopper asks "what's the best backpack for a 10-year-old starting secondary school?" Rufus doesn't just look for keywords. It evaluates which products genuinely answer that question based on listing content, reviews, and product attributes. Keyword stuffing doesn't just stop working with Rufus. It actively hurts you because it makes your content harder for the AI to parse.

The second shift is from rankings to recommendations. In traditional search, position 1 wins most of the clicks. In Rufus, the AI recommends specific products and explains why. Your product might never appear in position 1 of a keyword search but get recommended by Rufus because your listing clearly answers the shopper's specific question. This means the content quality of your listing matters more than ever.

The third shift is from impressions to trust. Rufus doesn't just list products. It explains why it's recommending them, citing reviews, product details, and use cases. Products with detailed, honest listings and strong reviews get cited more. Products with vague listings and thin reviews get skipped. The AI is essentially quality-filtering on behalf of the shopper.

How to optimise your listings for Rufus

You don't need to throw out your existing Amazon SEO strategy. You need to add a layer on top of it. Everything that works for A10 still works. But Rufus rewards content that goes further.

Write naturally, not just for keywords. "This moisturiser is formulated for dry, sensitive skin and includes SPF 30 protection for daily use" answers the shopper's question directly. "Moisturiser dry skin SPF 30 face cream lotion daily" is keyword soup that Rufus can't use to form a coherent recommendation. Write copy that a knowledgeable shop assistant would say out loud.

Answer common questions in your bullet points and description. Think about the questions shoppers ask before buying your product: "Is it suitable for sensitive skin?" "How long does it last?" "Does it work with [other product]?" Answer these explicitly in your listing. Rufus pulls from this content when formulating recommendations.

Fill out your Q&A section proactively. Don't wait for customers to ask questions, seed the Q&A with the most common queries and thorough answers. Rufus pulls from Q&A when answering shopper questions. Empty Q&A means fewer opportunities for Rufus to recommend your product.

Encourage detailed reviews. Rufus synthesises review content when comparing products. Reviews that mention specific benefits ("the battery lasts 3 days of heavy use"), specific use cases ("perfect for hiking in wet weather"), and specific comparisons ("much better than the Brand X version") give Rufus more material to work with. Generic 5-star reviews with no detail are less useful.

Use A+ Content thoroughly. Rufus reads A+ Content. Rich product descriptions with specific feature callouts, use case explanations, and comparison charts give the AI more information to recommend your product for the right queries. Brands with comprehensive A+ Content have an advantage over those without it.

Optimise for comparison queries specifically. "How does this compare to [competitor]?" is one of the most common Rufus queries. Make sure your listing clearly articulates what makes your product different, and better, for specific use cases. Don't just list features; explain the benefit of each feature in context.

The Sponsored Products angle

Amazon is now placing ads inside Rufus conversations, called Sponsored Products Prompts. When a shopper asks a buying question, your product can appear as a recommendation within the AI response.

This is currently in beta and free. Amazon hasn't started charging for Rufus ad placements yet, but they will, their ad revenue is already approaching $50 billion annually and AI-integrated formats are a growing share.

What sellers should do right now: make sure you have automatic or broad match Sponsored Products campaigns running, these are the campaigns eligible for Rufus placements. Check the Prompts report in Seller Central (Advertising → Reports → Sponsored Products → Prompts) to see if you're already getting Rufus impressions. Optimise backend keywords with question-based phrases shoppers might ask Rufus. Build baseline metrics now while the placements are free, so you can measure impact when Amazon introduces pricing.

The sellers who build their Rufus ad data during the free beta will have a significant advantage when Amazon turns on the auction.

The parallel with GEO for websites

What's happening with Rufus on Amazon is the same thing happening with ChatGPT, Gemini, and Perplexity on the open web. AI is reading content, synthesising it, and recommending based on quality, relevance, and structure, not just keyword matching.

On Amazon, Rufus reads your listings and reviews to recommend products. On Google, AI Overviews read websites to answer search queries. On ChatGPT, the AI cites web content to answer user questions.

The sellers and brands who understand this shift, and optimise their content for AI across both their Amazon listings and their website, will dominate the next era of ecommerce. It's the same skillset applied to two channels.

This is one of the reasons we built Jarvio the way we did. The Jarvio Agent uses AI (Claude, ChatGPT, Gemini) to help sellers understand and act on their Amazon data, including the Brand Analytics search term data that shows you how shoppers are finding your products. As Rufus changes shopping behaviour, the search terms in your Brand Analytics will shift from keyword strings to conversational queries. Tracking that shift is how you stay ahead.

Ask the Jarvio Agent: "Show me my Brand Analytics search terms for last month and highlight any question-based queries." Set up a weekly workflow that tracks how your search term mix is changing over time. That's how you see Rufus's impact on your specific products, not just read about it in articles.

What to do right now

You don't need to panic or overhaul everything. Rufus is growing but it's not replacing traditional search yet, A10 still drives the majority of product discovery. The smart approach:

Spend 80% of your effort on fundamentals. Great product, strong images, solid keywords, competitive pricing, healthy reviews. These work for both A10 and Rufus.

Spend 20% adapting for AI. Rewrite your top 10 listings with natural language that answers shopper questions. Fill out Q&A sections. Review your A+ Content. Check the Rufus Prompts report.

Start monitoring. Track your Brand Analytics search terms weekly and watch for the shift from keyword queries to question-based queries. That's Rufus changing your traffic mix. The earlier you see it, the faster you can adapt.

Don't wait for it to be mainstream. The sellers who optimised for mobile in 2015 had an advantage for years over those who waited. Rufus is the same kind of shift. Gradual, then sudden.

Related reading: Top 10 Ways to Use AI in Your Amazon Business · Jarvio for Brands · Jarvio for Sellers