What AI Shopping Agents Are and Why Retailers Care
AI shopping agents are software-based assistants that use generative and agentic AI to guide customers through discovery, comparison and purchase decisions, while also automating behind-the-scenes retail tasks such as pricing, inventory and promotions. Unlike static search bars or rule-based chatbots, these agents can interpret natural language, draw on real-time data and act on insights without human intervention. In 2026, they sit at the center of retail innovation, connecting e-commerce sites, retail media, store sensors and analytics platforms into one responsive experience. The NRF APAC Innovators Showcase highlights that this is no longer experimental technology: from marketplace management to in-store digital twins, AI shopping agents are becoming the new operating layer for how retailers sell, plan assortments and respond to shifting demand.
Inside the NRF APAC Innovators: Agents Across the Retail Stack
The NRF APAC Innovators Showcase puts AI agents at the heart of retail AI technology, spanning e-commerce, analytics and in-store tools. On the digital side, companies like Mirakl help retailers expand marketplaces and retail media at a time when global retail media spend is forecast to surpass $300 billion by 2030. Intelligence Node tracks competitive prices and content in real time so agents can suggest rapid changes to promotions and assortments. In business analytics, Propheus blends signals such as weather and competitor moves, then uses agents to recommend staffing, inventory and pricing actions. Trendier AI compresses trend validation cycles for beauty brands from weeks to a single day by reading social buzz. Meanwhile, in-store innovators such as Planoverse and Whale bring the same level of insight to shelves and store operations that retailers already expect from their e-commerce dashboards.
Amazon’s Agentic Shopping Assistant and Alexa for Shopping Go Retail-Wide
Amazon is turning the AI that powers its own Alexa for Shopping agent into a reusable foundation for other retailers through the Agentic Shopping Assistant on AWS. The solution is built on Amazon Bedrock, AgentCore and OpenSearch, and was validated on billions of shopping interactions on Amazon.com. Amazon says retailers can deploy conversational agents “in weeks,” compared with the years it would take to build from scratch. The key idea is that brands keep their own catalog data, tone of voice and customer insights, while relying on a battle-tested core for AI customer service and guided discovery. Early adopters can design agents that feel less like keyword search and more like speaking with an attentive store associate who understands context, cross-category needs and constraints such as budget, occasions or style preferences.
Kate Spade’s AI Gift Concierge Shows Luxury’s Early Lead
Kate Spade New York is among the first to turn Amazon’s Agentic Shopping Assistant into a real-world AI shopping agent, building a conversational AI Gift Concierge in roughly 2.5 months. Powered by Anthropic’s Haiku 4.5 model and informed by questions customers asked Alexa for Shopping, the agent recommends gifts based on occasion, style and other personal details. Tapestry’s data and digital leaders describe it as a way to reduce the stress of gift-buying and to create an experience that “feels less like search and more like talking to someone who knows the brand and knows how to give a great gift.” This luxury example signals how fashion and premium brands are moving first: they see AI not only as a customer-service channel, but as a digital expression of their brand’s taste and curation.
AI Beyond the Customer: Agents in Retail Operations
While AI shopping agents shine in customer-facing roles, the same technologies are reshaping back-office retail operations. Tapestry’s internal platform Mira, built with Amazon Bedrock, helps employees plan assortments, manage inventory and track consumer trends by surfacing related insights in seconds to minutes. At the NRF APAC Innovators Showcase, Propheus plays a similar role by having AI agents recommend actions across inventory, staffing and promotions based on external signals. Planoverse uses AI-powered 3D digital twins to test store layouts for chains like Woolworths before any physical change happens, and Whale connects fragmented store systems so staff can ask natural-language questions instead of jumping between dashboards. Together, these examples show that AI shopping agents and related tools are becoming the connective tissue of retail innovation 2026, tightening the loop between insight, decision and action in both digital and physical environments.
