Amazon’s new AI ‘Interests’ feature acts as a personal shopper for users

Amazon is expanding the artificial intelligence capabilities underpinning its e-commerce platform with a new feature called “Interests.” This generative AI tool continuously monitors Amazon’s inventory to proactively recommend products matching users’ self-described passions and preferences. By transforming casual language into specific queries that traditional search engines can process, Amazon is attempting to recreate the experience of having a personal shopper who understands individual tastes and actively looks for relevant new products.

The big picture: Amazon has launched “Interests,” a generative AI feature that uses large language models to transform user preferences into ongoing, personalized product recommendations as new items become available on the platform.

• The feature is currently available in beta to a limited number of U.S. customers through Amazon’s mobile app and website.
• Interests works alongside Rufus, Amazon’s AI shopping assistant launched in September, creating a more comprehensive AI-powered shopping ecosystem.

How it works: The Interests feature functions as an automated personal shopper that monitors user-defined preferences and continuously updates recommendations based on new product listings.

• Users can create and adjust “Interest Prompts” describing their preferences in natural language, such as “The latest pickleball gear and accessories, don’t show me backpacks.”
• The system then translates these casual descriptions into technical queries that can be processed by Amazon’s recommendation engines.
• As inventory changes with new products arriving or others going out of stock, the recommendations update automatically.

Why this matters: Amazon’s investment in AI-driven personalization signals a shift toward more predictive and frictionless e-commerce experiences that could fundamentally change how people discover products.

• By using generative AI to curate suggestions rather than just respond to queries, Amazon is reducing the effort required from shoppers to find relevant products.
• The system represents a more sophisticated approach to personalization that goes beyond traditional recommendation algorithms based solely on past purchases or browsing history.

The broader trend: Amazon’s AI shopping tools reflect the evolution of artificial intelligence from novelty applications to practical tools that directly influence consumer behavior and purchasing decisions.

• While Rufus answers specific product questions and provides comparisons, Interests takes a more proactive approach by anticipating user needs before they’re explicitly expressed.
• This application of AI for product discovery suggests Amazon is positioning itself at the forefront of AI-driven retail, potentially creating competitive advantages through enhanced personalization.