From Static Search to Agentic Commerce
Agentic commerce is the use of autonomous AI shopping assistants that can understand goals, hold conversations, and take multi-step actions to guide people from product discovery through purchase decisions in real time. This marks a change from static product grids and basic recommendation widgets toward interactive retail AI agents that behave more like digital shopping companions. Instead of forcing customers to filter through endless menus, these systems ask questions, interpret intent, and suggest tailored options. For consumers, the promise is a more personalized shopping experience with less friction and faster decisions. For retailers, the appeal is higher engagement and improved conversion in an increasingly crowded e-commerce landscape. As more brands connect agents to product catalogs, customer profiles, and inventory systems, the line between browsing and being guided toward a purchase is starting to blur.
Amazon’s Agentic Shopping Assistant Goes Multi-Retailer
Amazon Web Services is pushing agentic commerce beyond its own marketplace by offering the AWS Agentic Shopping Assistant to outside retailers. Built on the same technology that powers Alexa for Shopping on Amazon.com, this AI shopping assistant can run inside a retailer’s site, answer product questions, and recommend items aligned with that store’s inventory and brand. According to Amazon, Alexa for Shopping drove nearly $12 billion in incremental sales last year, a figure that underlines why retailers are eager to test similar AI-driven experiences. AWS says retailers can deploy a custom assistant in about 60 days and retain control over customer data, catalogs, and business rules. Early adopters like Kate Spade’s parent company are already experimenting with AI gift concierges, highlighting how conversational agents are becoming a new competitive layer on top of traditional e-commerce platforms.
Shopify and Nosto Bring Agentic Workflows Inside the Back Office
While Amazon targets consumer-facing shopping journeys, Shopify and Nosto are focusing on how retail AI agents can change daily work for commerce teams. Nosto’s new native workflows for Shopify Sidekick let merchandisers adjust product discovery and personalization directly through conversational instructions inside Shopify, instead of hopping between tools or waiting on developers. At the OMR Festival, Ford’s e-commerce partner used Sidekick prompts to modify Nosto-powered product recommendations on its accessories store, showing how design and merchandising changes can move at the speed of a chat. Nosto is also extending Huginn, its AI agent, into a wider range of agentic commerce workflows, from technical guidance via a Doc Agent to proactive merchandising insights and automated execution. The goal is to cut operational bottlenecks and make it easier to launch and optimize personalized shopping experiences at scale.
DICK’S Sporting Goods Turns AI into a Digital Coach
DICK’S Sporting Goods is bringing agentic commerce into its mobile app with Coach by DICK’S, an AI shopping assistant designed as a digital coach for athletes and families. The system combines the retailer’s product knowledge with conversational AI so shoppers can describe their sport, skill level, and preferences, then receive guided recommendations on gear, training “Pro Tips,” and related services. Vlad Rak, the company’s CTO, says the goal is real-time guidance rather than static product listings. This AI Coach builds on DICK’S broader investments in inventory management, RFID automation, omni-channel systems, and e-commerce operations, tying customer-facing conversations to back-end data. By integrating conversational AI with customer profiles and product catalogs, DICK’S aims to deliver a more personalized shopping experience that links advice, availability, and purchase in a single flow, reinforcing its wider digital strategy.
What AI Shopping Agents Mean for Shoppers and Competition
Across these examples, agentic commerce signals a new phase in digital retail where AI shopping assistants play an active role in decision-making. Instead of passively suggesting “related items,” retail AI agents can ask why you are shopping, refine options, and automate parts of selection and purchasing. Accenture estimates that by 2030 more than 30% of online commerce could run through AI agents, representing about $3.1 trillion in transactions, a projection that explains the current rush among platforms and brands. For consumers, this could mean faster, more relevant guidance—but also more subtle steering toward specific products. For retailers, AI agents are becoming a competitive necessity, not a novelty, as they look to lift conversion and loyalty in saturated markets. The race now is to balance personalization, trust, and control while AI intermediates more of the shopping journey.