Agentic AI Shopping Assistants Become Retail’s New Frontline
Agentic AI shopping assistants are AI-powered retail agents that hold natural conversations with customers, understand intent across contexts, and autonomously guide them through product discovery, comparison, and purchase decisions across digital channels. This new wave of agentic retail technology is reshaping what an AI commerce experience looks like, turning static websites and apps into interactive, guided journeys. Instead of forcing shoppers to click through menus and filters, retail AI agents interpret goals, refine results, and surface tailored options in real time. Retailers are combining first-party customer data, detailed product catalogs, and behavioral signals to train these assistants around their own inventory and brand voice. At the same time, AI tools are moving behind the scenes, helping commerce teams configure recommendations, personalize layouts, and automate merchandising workflows. Together, these trends are turning AI shopping assistants into a strategic differentiator rather than a side experiment.
Amazon Turns Alexa for Shopping into a Retail AI Platform
Amazon’s cloud division is pushing agentic retail technology out to other retailers with the AWS Agentic Shopping Assistant, built on the same foundation as its Alexa for Shopping assistant. Amazon says Alexa for Shopping, formerly known as Rufus, drove nearly USD 12 billion (approx. RM55.2 billion) in incremental sales last year, a proof point it is using to sell its model of AI commerce experience to the wider market. Retailers can deploy their own branded AI shopping assistants in about 60 days, with each instance trained on that retailer’s catalog, content, and business rules. AWS stresses that merchants keep control of customer data while using Amazon’s infrastructure and know-how. An early adopter is Kate Spade parent Tapestry, which launched an AI gift concierge that asks about occasion, recipient, and style before recommending products—an example of retail AI agents acting as conversational stylists rather than static search bars.
DICK’S AI Coach and Kmart Joy Bring Agentic AI to Shoppers
On the consumer-facing side, retailers are embedding AI shopping assistants directly into their apps and websites to deepen engagement. DICK’S Sporting Goods has launched Coach by DICK’S inside its mobile app, combining its product knowledge with conversational AI to give real-time guidance based on sport, skill level, and stated preferences. The assistant also surfaces “Pro Tips,” product education, and guidance on equipment and services, moving conversational AI beyond basic support into tailored coaching. Kmart has introduced Joy, a conversational AI shopping assistant that supports virtual try-ons and a “See It in My Space” feature so customers can visualize products in their homes before buying. Joy lets shoppers refine searches with natural language, compare items side by side, and even upload photos to receive personalized suggestions. Powered by Gemini Enterprise for Customer Experience, Joy is designed to manage agents across the full shopping lifecycle, from discovery to post-purchase help.
Nosto and Shopify Sidekick Bring Agentic AI Behind the Scenes
Agentic AI in retail is not only customer-facing; it is also reshaping how commerce teams work. Nosto, an agentic Commerce Experience Platform, has launched native agentic AI workflows for Shopify’s AI assistant, Sidekick. Within Shopify’s interface, merchandisers can describe the changes they want—such as adjusting the design or placement of Nosto-powered product recommendations—and see the outcome immediately, instead of switching tools or waiting on developer support. During a live demonstration with Shopify and Ford’s ecommerce partner Autonative, conversational prompts inside Sidekick were used to modify recommendation layouts on Ford’s accessories store in real time. Nosto’s CEO, Jim Lofgren, describes operational bandwidth and developer access as key bottlenecks, arguing that bringing retail AI agents directly into Shopify “collapses the distance between action and performance.” This kind of agentic retail technology is turning AI into a co-worker that helps teams iterate on personalized experiences faster.
The Commerce Race: From Experiments to Agentic Retail Systems
Taken together, these moves signal a new phase in the AI commerce experience: conversational tools are evolving into full agentic retail systems that automate parts of shopping and operations. Retailers are shifting from isolated pilots toward infrastructure that embeds retail AI agents across the customer journey and internal workflows. Amazon is betting that a large share of online sales will run through AI agents in the coming years, and cloud platforms, retailers, and commerce tech vendors are positioning to control different layers of that stack. According to Accenture, by 2030 more than 30% of online commerce could be mediated by AI agents, representing about USD 3.1 trillion (approx. RM14.3 trillion) in transactions. In this race, AI shopping assistants are becoming a competitive necessity: the brands that turn their product data and customer insight into responsive, agentic experiences are likely to define shoppers’ expectations for everyone else.
