AI Shopping Assistants Redefine the Online Shopping Experience
An AI shopping assistant is a conversational digital agent embedded into retail websites or apps that uses generative and retail AI technology to understand natural language, recommend products, and guide shoppers through discovery, comparison, and purchase decisions in a more human-like way than traditional search or filters. Retailers are turning to these assistants to cut friction from the online shopping experience, turning static catalogues into interactive sessions where customers can ask questions, narrow options, and get tailored advice. Instead of typing rigid keywords or clicking through endless menus, shoppers can describe their needs in everyday language, upload photos, or specify constraints like size, color, and budget. This interaction style mirrors an in-store associate, but scaled across entire catalogues and customer bases. As retailers integrate virtual try-on technology and multimodal AI, these assistants are evolving from basic chatbots into full shopping companions that can drive higher engagement and conversion.
Kmart’s Joy: Virtual Try-On and ‘See It in My Space’
Kmart’s Joy AI shopping assistant shows how retailers are fusing conversational commerce with virtual try-on technology. Available via its website and app, Joy lets shoppers visualise selected products on themselves or inside their homes, including furniture, before buying. The “See It in My Space” feature blends computer vision and augmented reality so customers can preview how items fit their rooms, helping reduce uncertainty around big purchases. Shoppers can ask Joy for products in specific sizes, styles, colours, and price ranges, then refine options through follow-up questions instead of restarting searches. They can also upload photos to receive personalised product suggestions across Kmart’s broader marketplace, including partner brands, and view side-by-side comparisons. Joy runs on Gemini Enterprise for Customer Experience from Google Cloud, which coordinates AI agents across the customer lifecycle, from discovery to post-purchase support. This combination of conversational guidance and immersive visualisation aims to make online shopping feel closer to browsing a physical store with a knowledgeable assistant.
Amazon Turns Its Retail AI Technology into a Platform
Amazon is commercialising years of investment in retail AI technology by offering an Agentic Shopping Assistant through AWS. The service gives retailers a blueprint to build their own AI shopping assistant, tailored to their product catalogue, customer profiles, and brand tone, rather than relying on generic bots. It reuses architecture and lessons from Amazon’s own AI shopping assistant and Alexa for Shopping, with Amazon stating that more than 300 million customers used its assistant last year and that it generated nearly US$12 billion (approx. RM55.2 billion) in incremental sales over the same period. Retailers can deploy these conversational agents in weeks using starter code, architectural guidance, and support from AWS experts and system integrators. Under the hood, services like Amazon Bedrock, AgentCore, and OpenSearch power generative responses, agent orchestration, and search. Amazon also reports that conversational shopping sessions deliver conversion rates 3.5 times higher than traditional keyword-based search, a compelling metric for retailers seeking growth.
Kate Spade’s AI Gift Concierge and the New Competitive Edge
Kate Spade is one of the first brands to adopt Amazon’s Agentic Shopping Assistant, using it to create an AI Gift Concierge focused on gift-buying. Instead of browsing static gift guides, customers can describe the recipient, occasion, and preferences through a natural conversation and receive curated suggestions. The tool responds to a real pain point: Amazon highlights data showing 53% of shoppers report stress when purchasing gifts. By narrowing options quickly and suggesting relevant items, the concierge aims to reduce decision fatigue and increase the chance that browsers become buyers. Behind the scenes, the system taps Amazon Bedrock for generative AI, AgentCore to manage agents, and OpenSearch for retrieval, showing how advanced retail AI technology can be packaged into brand-specific experiences. For retailers, this kind of specialised assistant offers a competitive advantage: it blends brand tone with data-driven recommendations, capturing intent that might otherwise be lost in generic search results.
Why Conversational AI Assistants Matter for Retail’s Future
The momentum behind AI shopping assistants reflects a broader shift away from rigid search bars toward conversational, context-aware retail experiences. Retailers see these systems as a way to shorten the path from discovery to purchase by meeting customers in their own words, whether that means asking for “a red dress for a summer wedding under this budget” or uploading a photo of a living room to find matching décor. According to Kmart’s Chief Customer Officer Bernard Wilson, “Customers aren’t just searching anymore; they’re engaging conversationally and looking for ideas and guidance.” When combined with virtual try-on technology and features like “See It in My Space,” assistants can lower returns and build confidence before checkout. Data from Amazon suggests the upside is significant, with conversational journeys driving conversion rates several times higher than keyword search. As tools become easier to deploy via platforms like AWS and Google Cloud, AI shopping assistants are set to become a standard feature of competitive online commerce.
