From Chatbots to Agentic Commerce
An AI shopping assistant is a conversational system that does more than answer questions; it behaves as a retail AI agent that understands context, proposes options, compares products, and takes multi-step actions to guide customers from discovery to purchase in a more autonomous way. This marks a shift from static search bars and scripted chatbots toward agentic commerce, where AI e-commerce tools act like digital sales associates instead of passive help widgets. Rather than waiting for a shopper to type exact keywords, these assistants respond to natural language, refine criteria such as budget or style, and surface relevant items across a retailer’s catalogue. The goal is to reduce decision fatigue while keeping customers on a single site, and to give retailers a direct, AI-powered channel for shaping how shoppers find, evaluate, and commit to products.
Amazon’s Agentic Shopping Assistant Leaves Its Own Store
Amazon Web Services is opening its Agentic Shopping Assistant to outside retailers, extending the same Alexa for Shopping technology that powered nearly USD 12 billion (approx. RM55.2 billion) in incremental sales on Amazon.com. Retailers can build branded AI shopping assistants for their own sites in about 60 days, with control over customer data, product catalogues, and business rules. Instead of sending shoppers to Amazon, the AI sits inside each retailer’s mobile or web experience, answering questions, handling product comparisons, and steering customers toward items that match that specific inventory. According to Accenture, more than 30% of online commerce could run through AI agents by 2030, representing about USD 3.1 trillion (approx. RM14.26 trillion) in transactions. Early adopters like Kate Spade are already using the tool as a gift concierge, showing how agentic commerce can feel like a personal stylist rather than a search engine.
Kmart’s Joy Blends Conversation, Virtual Try-On, and AR
Kmart’s AI shopping assistant Joy shows how retail AI agents can combine conversation with richer visuals. Joy is embedded in the website and app, acting as a virtual shopping partner that lets customers describe size, style, colour, and budget in natural language, then suggests suitable products. Its virtual try-on technology lets shoppers see how selected items may look, while the “See It in My Space” feature places furniture and other products in a customer’s home using augmented visuals. Shoppers can upload their own photos, receive tailored recommendations, and compare items side by side across Kmart, Target, and marketplace brands. These capabilities draw on Gemini Enterprise for Customer Experience, an agentic solution that manages AI agents across the customer lifecycle from discovery to post-purchase issues. Joy illustrates how agentic commerce aims to make online shopping more visual, exploratory, and confidence-boosting than a standard product grid.
Inside the Platforms: Nosto, Shopify Sidekick, and Huginn
While consumer-facing assistants guide shoppers, Nosto is focusing on the commerce teams behind the scenes. Its integration with Shopify’s AI assistant Sidekick lets merchandisers use conversational prompts inside Shopify to adjust Nosto-powered product discovery and personalisation. Instead of switching tools or relying on developers, a team member can describe the design changes they want for recommendation blocks and see updates in the store theme, which reduces execution overhead. Nosto is also developing Huginn, its AI agent that connects through MCP, bringing deeper commerce intelligence into Sidekick. Planned agentic AI workflows include a Doc Agent that gives technical guidance, a Merchandising Agent that suggests and later automates merchandising actions, and reporting agents that surface performance insights. This shows how AI e-commerce tools are evolving into multi-agent systems that coordinate both customer experiences and back-office decisions, tightening the loop between strategy and on-site execution.
What AI Shopping Agents Mean for Your Experience
For shoppers, the rise of AI shopping assistants means fewer dead-end searches and more guided journeys. Instead of sifting through pages of products, you can describe your needs in everyday language and receive tailored options, visualisations, and comparisons in one place. Agentic commerce also lets retailers fine-tune their AI agents around brand voice, inventory, and rules, which can keep recommendations aligned with stock levels and margin goals. At the same time, these tools raise familiar questions about data trust and dependence on large platforms such as AWS, Google Cloud, and Shopify’s ecosystem. Retailers need to balance the appeal of advanced retail AI agents with the desire to keep customer relationships and data under their own control. As more sites embed autonomous assistants, the competitive edge may come from not only who has AI, but who uses it to make shopping feel clearer, more transparent, and less overwhelming.