What AI shopping assistants are and why they matter now
AI shopping assistants are conversational retail AI agents that guide customers through browsing, comparing, and buying products by combining natural-language chat with automated search, recommendations, and service workflows. Rather than acting as simple chatbots, they connect to product catalogs, promotions, and order data so they can answer questions, narrow choices, and complete tasks like gift selection or returns inside one interface. Amazon’s decision to license its Agentic Shopping Assistant through AWS shows how this ecommerce AI technology is moving from an in-house advantage to shared infrastructure. Retailers no longer need to build complex AI customer service and recommendation engines from the ground up. Instead, they can plug into proven systems and quickly automate parts of retail operations, from product discovery to post-purchase support. That shift is poised to reset customer expectations for every online store.
Amazon’s Agentic Shopping Assistant moves from store to service
Amazon’s Agentic Shopping Assistant takes the AI systems that power its own shopping agent and packages them for retailers through AWS. Built on Amazon Bedrock for generative AI, AgentCore for operating AI agents, and OpenSearch for search and retrieval, the service gives brands a technical foundation plus starter code and expert guidance so they can launch AI shopping assistants in weeks instead of years. Amazon says its internal AI shopping assistant served more than 300 million customers last year and helped generate nearly USD 12 billion (approx. RM56.4 billion) in incremental sales, experience that now informs the external product. Deployments can be customized to a retailer’s catalog, voice, and shopping environment, turning a generic base into a branded AI customer service and product discovery layer. In effect, Amazon is turning its retail AI agents into a shared ecommerce AI technology platform.
Kate Spade’s AI Gift Concierge shows the new customer experience
Kate Spade New York is among the first brands to adopt Amazon’s Agentic Shopping Assistant, building an AI Gift Concierge focused on gift buying. The agent uses natural-language conversations to ask about occasion, style, and preferences, then recommends suitable products from Kate Spade’s catalog. According to Amazon, 53% of shoppers report stress during gift purchases, so narrowing choices through AI customer service can relieve friction at a high-intent moment. Fabio Luzzi, Tapestry’s chief data and analytics officer, describes the concierge as a conversational AI experience shaped by direct feedback from consumers. Tapestry tested the assistant for about two and a half months before making it public, using Amazon’s architecture and AWS support to shorten time to launch. For shoppers, the result is a more guided journey; for Kate Spade, it is retail automation that can scale without adding human staff to every interaction.
Adidas turns AI agents into ecommerce-as-a-service
While Amazon sells AI shopping assistants as cloud infrastructure, Adidas is folding retail AI agents into an ecommerce-as-a-service model. Running the Audi F1 ecommerce store, Adidas uses Salesforce technology and AI agents to operate an Audi-branded site end to end, from merchandising to 24/7 customer service via email and chat. Adidas senior project manager Dominik Seeberger said the company brought the Audi site live in eight weeks and that AI agents let Adidas scale EAAS without adding headcount. Competitively, this responds to digital disruptors providing similar services for licensed partners. For Audi, shoppers see a native Audi webstore, while Adidas handles ecommerce operations in the background. This approach turns ecommerce AI technology into a white-label service that partners can adopt with minimal effort, reinforcing how AI customer service and retail automation are becoming baked into broader digital commerce offerings.
From competitive edge to standard retail infrastructure
Both Amazon’s Agentic Shopping Assistant and Adidas’s ecommerce-as-a-service signal a shift: AI shopping assistants are moving from being rare differentiators to expected infrastructure. As more shoppers rely on retail AI agents to search, compare, and purchase, brands that lack conversational guidance risk feeling clumsy and outdated. At the same time, cloud and EAAS models mean retailers of all sizes can deploy AI customer service and guided shopping without building their own platforms. Instead of competing on who has AI at all, brands will compete on how well they tune these systems to their assortments, tone of voice, and logistics. Over time, the baseline will be AI-driven discovery, support, and post-purchase workflows in nearly every ecommerce environment, with differentiation coming from better data, sharper merchandising strategies, and more thoughtful design of human-plus-AI shopping journeys.
