Retail AI Agents Move From Experiment to Growth Engine
Retail AI agents are rapidly evolving from pilot projects into core drivers of AI-powered sales growth and customer engagement. Major retailers are deploying conversational AI shopping tools that blend product discovery, recommendations, and guided selling into a single experience anchored in first-party data. These systems draw on purchase histories, inventory signals, and behavioral insights to personalize journeys in real time, boosting relevance while simplifying complex decisions for shoppers. At the same time, retailers are consolidating previously separate technologies—search, recommendations, and digital selling assistants—under unified AI models that can reason across the full catalog and customer profile. This consolidation is enabling more consistent experiences across apps, websites, and stores, while also making it easier to link marketing investments to measurable business outcomes. The new generation of retail AI agents is therefore less about novelty chatbots and more about end-to-end commerce engines that can influence what customers discover, how they buy, and how supply chains respond.
Walmart’s Sparky Shows the Sales Impact of Conversational AI Shopping
Walmart’s Sparky illustrates how retail AI agents can directly lift average order value and unit sales. CEO John Furner describes the company as “becoming AI native,” highlighting Sparky’s role in both shopping assistance and smarter supply chain decisions. Weekly active users of Sparky more than doubled in the last quarter, and Walmart says its AI investments have improved the agent’s intelligence and response quality by 40% this year. Customers who shop with Sparky have an average order value about 35% higher than non-users, and units purchased through the agent have more than quadrupled since the previous fiscal quarter. Sparky is integrated across the ecommerce site, mobile app, and stores, supporting capabilities like personalized replenishment, meal planning, and recommendations based on inventory positioning, pricing, and delivery speed. Walmart is also extending AI into its advertising toolkit, helping brands dynamically adjust creative to improve campaign performance and fuel ecommerce growth.
Coach by DICK’S: Personalized Athlete Guidance at Scale
DICK’S Sporting Goods is applying the same retail AI agents trend to sports with Coach by DICK’S, an agentic AI-powered experience embedded in its mobile app. Designed to provide personalized athlete guidance, Coach blends conversational AI shopping with training support, product education, and tailored recommendations based on an athlete’s sport, goals, interests, and preferences. Built on Adobe Brand Concierge technology and DICK’S proprietary sport knowledge, the platform extends in-store expertise into a digital channel, creating a more seamless journey between research, coaching, and purchase. The system adapts to behavior and input in real time, surfacing relevant gear suggestions alongside training “Pro Tips” and equipment guidance, with capabilities expected to expand over time. DICK’S leaders frame the initiative as a way to scale what makes the brand distinctive—its people, point of view, and connection to sport—while giving athletes more confidence in decisions about products and services.
Agentic Commerce Links Marketing, Stores, and Unified AI Stacks
The launch of Coach by DICK’S reflects a broader shift toward agentic commerce systems that connect marketing, digital engagement, and store outcomes through unified AI models. DICK’S is combining product catalogs, first-party customer data, and behavioral signals with conversational AI to guide shoppers through discovery and purchase decisions, moving far beyond traditional support bots. Adobe’s Brand Concierge foundation ensures the experience is trained on approved brand content rather than open web data, reinforcing trust while enabling highly personalized journeys across digital properties. In parallel, retailers like Walmart are using AI to tune advertising content in real time and tie media spend on platforms such as Meta and Google to measurable ecommerce performance. As these capabilities mature, the ecommerce tech stack is consolidating: search, recommendations, guided selling, and marketing optimization increasingly sit on top of the same AI layer, enabling consistent personalization from the first ad impression through the final transaction.
