AI Shopping Agents Move From Experiment to Core Retail Strategy
AI shopping agents are rapidly shifting from pilots to core engines of retail sales growth. Instead of static search bars and filters, shoppers now interact with conversational AI shopping assistants that understand intent, context, and inventory in real time. This model, often described as agentic commerce, allows an AI agent to guide discovery, comparison, and basket-building on behalf of the customer. Analyst forecasts suggest that a significant share of ecommerce transactions could soon be mediated by such agents, fundamentally changing how consumers browse and buy. For retailers, the appeal is clear: AI shopping agents promise higher average order value, more units per order, and richer data on customer preferences. At the same time, the technology is expanding beyond front-end experiences into fulfillment, supply chain decisions, and advertising optimization, creating a connected, data-driven loop from product recommendation to delivery and media performance.
Inside Walmart’s Sparky: Higher AOV, More Units, Smarter Operations
Walmart’s Sparky AI agent illustrates how agentic commerce can translate into measurable performance gains. Executives report that weekly active users of Sparky more than doubled in the most recent quarter, while enhancements have improved its intelligence and response quality by 40% this year. Crucially, customers who shop with Sparky show an average order value about 35% higher than non-users, and units purchased through the agent have more than quadrupled versus the prior fiscal quarter. Sparky now supports personalized replenishment, meal planning, and recommendations that factor in inventory positioning, prices, and delivery speeds, and it is accessible across the ecommerce site, mobile app, and physical stores, including Spanish-language support. Beyond front-end sales, Walmart is deploying AI to optimize inventory placement and fulfillment decisions, and to power advertising tools that dynamically adjust creative and expand reach via its connected TV platform, contributing to double-digit advertising revenue growth.
AWS Agentic Shopping Assistant: Bringing Alexa-Grade AI to Every Retailer
Amazon Web Services is opening its AI shopping technology to outside retailers through the AWS Agentic Shopping Assistant, signaling a new phase in the race for agentic commerce. Built on the same technology that powers Alexa for Shopping on Amazon.com, which has generated nearly USD 12 billion (approx. RM55.2 billion) in incremental sales, the service lets retailers embed their own branded AI shopping assistants into their sites and apps. These assistants can converse with shoppers, answer detailed product questions, and make recommendations tuned to each merchant’s catalog, promotions, and merchandising rules. AWS says retailers can launch an experience in about 60 days, reducing the need to build complex AI stacks from scratch. Early adopters include fashion brand Kate Spade, whose parent company used the platform to create an AI gift concierge that gathers context about the occasion and recipient before suggesting products, demonstrating how conversational guidance can deepen engagement and drive higher-value baskets.
Beyond Conversation: Fulfillment, Supply Chain, and Ad Optimization
The rise of AI shopping agents is reshaping more than just the digital storefront. Retailers are increasingly connecting these agents to back-end systems, allowing insights from customer conversations to inform fulfillment routing, inventory allocation, and demand planning. When an AI agent steers shoppers toward certain bundles or replenishment patterns, those signals can help determine where inventory should be positioned and which facilities should fulfill particular orders to meet speed and cost targets. At the same time, AI is driving more efficient retail media operations. By analyzing performance in real time, AI tools can dynamically adjust ad content, placement, and cross-channel mix, especially on connected TV platforms, to maximize campaign outcomes and ecommerce lift. This integrated approach turns agentic commerce into a full-funnel engine: the same intelligence that boosts average order value at checkout also helps ensure the right stock is in the right place and the right ad reaches the right audience.
Enterprise-Grade Agentic Commerce Without Building From Scratch
For many retailers, the historical barrier to AI shopping agents has been the cost and complexity of building and maintaining bespoke systems. That calculus is changing as large platforms productize their internal tools. Offerings such as the AWS Agentic Shopping Assistant give retailers a way to deploy enterprise-grade AI shopping assistants that still reflect their own branding, merchandising strategy, and customer data policies. Meanwhile, success stories like Walmart’s Sparky demonstrate that when done well, agentic commerce can significantly increase average order value, unit sales, and engagement. Retailers can now plug into proven AI models, integrate their product catalogs and business rules, and iterate through testing rather than multi-year custom development. As agentic commerce becomes more accessible, competitive pressure is likely to grow: shoppers will increasingly expect intelligent, conversational help across categories, pushing laggards to adopt AI shopping agents not as experiments, but as standard infrastructure for modern retail.