What AI Shopping Assistants Are—and Why Retailers Want Them
An AI shopping assistant is a digital helper that uses artificial intelligence to understand shopper questions, recommend products, and guide purchases through conversational interactions, increasingly integrating visual tools like virtual try-on shopping to make online buying more intuitive and personalised. Retailers are racing to deploy this kind of retail AI technology because shoppers are moving from keyword searches to natural conversations, asking for ideas, comparisons, and styling tips. These agents sit inside apps and websites, connecting product data, search, recommendations, and chat into one experience. They promise higher conversion rates by reducing friction around product discovery, fit, and decision-making. At the same time, they give retailers constant, automated frontline service that can respond in seconds at any hour. As companies like Kmart and Kate Spade roll out their own assistants, they are setting expectations for a new era of conversational commerce.
Kmart’s Joy: From Search Bar to Conversational Shopping Partner
Kmart’s new AI shopping assistant, Joy, turns its website and app into a personalised, conversational shopping space. Built with Google Cloud’s Gemini Enterprise for Customer Experience, Joy goes beyond basic search: shoppers can ask for a product in a specific size, style, colour, and budget and get tailored options within seconds. Virtual try-on shopping lets people see how selected products may look on them, while the “See It in My Space” feature displays furniture and décor inside their own homes before they buy. Customers can upload photos to receive more precise recommendations and compare items side by side across Kmart, Target, and marketplace brands. According to Kmart Group’s Chief Customer Officer Bernard Wilson, “Customers aren’t just searching anymore; they’re engaging conversationally and looking for ideas and guidance,” and Joy is designed to narrow that journey from inspiration to purchase.
Amazon’s Agentic Shopping Assistant: Retail AI Technology as a Service
Amazon is taking the AI engine behind its own AI shopping assistant and offering it to retailers through AWS as the Agentic Shopping Assistant. The service combines Amazon Bedrock for generative AI, AgentCore for running agents, and OpenSearch for search and retrieval, plus architecture guidance and starter code. Amazon says this setup lets retailers deploy conversational agents “in weeks,” instead of the years required to build from scratch. The system was “validated using billions of real shopping interactions on Amazon.com,” and Amazon reports that its AI shopping assistant was used by more than 300 million customers last year, generating nearly US$12 billion (approx. RM55.2 billion) in incremental sales. Retailers can customise the assistant to their catalogues, customer bases, and brand voices, keeping control of proprietary data while tapping into a proven retail AI technology foundation.
Kate Spade’s AI Gift Concierge and the Rise of Conversational Commerce
Kate Spade is among the first brands to adopt Amazon’s Agentic Shopping Assistant, launching an AI Gift Concierge aimed at stress-free gift buying. Powered by Anthropic’s Haiku 4.5 model and informed by questions people ask Alexa for Shopping, the concierge chats with users in natural language, asking about the occasion, style preferences, and hints about the recipient before suggesting products. Amazon notes that 53% of shoppers report stress when buying gifts, so this focused assistant helps narrow choices quickly. Tapestry’s chief data and analytics officer, Fabio Luzzi, describes it as “a conversational AI experience that helps customers find the right gift” built by listening to what consumers said they needed. This is a clear example of conversational commerce: instead of browsing dozens of pages, shoppers rely on an agentic AI to curate options and refine them through back-and-forth dialogue.
What Shoppers Should Expect Next from Agentic AI in Retail
For shoppers, these new AI shopping assistants signal a move from static catalogues to interactive journeys guided by agentic AI. Expect more sites where you describe your needs in plain language, upload a photo of your space or outfit, and receive curated, side-by-side suggestions. Virtual try-on shopping and “see it in my space” tools should become standard, making fit and style decisions less uncertain. Retailers will use conversational commerce to keep you engaged longer, answer follow-up questions, and surface add-ons that feel relevant rather than random. At the same time, behind-the-scenes agents, like those powered by Gemini Enterprise or AWS, will support the entire lifecycle—from discovery to post-purchase questions or returns. As these systems spread, shoppers gain speed and convenience, but they should also watch how their data is used, since better personalisation depends on deeper behavioural insight.
