From Omnichannel to AI-First Unified Commerce
Omnichannel retail AI is entering a new phase. For leading chains, it no longer means only syncing websites, mobile apps and stores; it now includes AI platforms like large-language models and intelligent agents. This expanded view reflects a shift from siloed retail operations to unified commerce platforms where every channel, including AI assistants, draws from the same core data. Retailers are treating AI as another surface where customers discover, evaluate and purchase products. That demands consistent product information, inventory visibility and experience design across digital and physical touchpoints. The emerging AI ecommerce strategy focuses on making product catalogs “AI-ready,” so conversational tools can understand attributes, answer questions and guide purchases whether customers start on a search engine, in an app or inside a store. The result is a retail AI integration agenda driven less by flashy features and more by disciplined data governance and experience continuity.
Academy Sports and Outdoors Redefines Omnichannel Around AI
Academy Sports and Outdoors offers a clear example of this evolution. Its CIO describes omnichannel as spanning the retailer’s site, mobile app, physical stores, AI platforms such as ChatGPT and Gemini, and external marketplaces. The foundation is a single, maturing product feed that connects the catalog to all these endpoints. Instead of separately managing thousands of SKUs for each channel, Academy enriches product attributes in waves, by department, to build a scalable, unified data layer. That feed powers everything from its ecommerce site to on-demand delivery partners. AI is used for content enrichment, scraping additional attributes and then proposing new descriptors that human merchants approve. The approach turns the catalog into a living asset that continuously improves searchability and relevance. In practice, this unified commerce platform lets customers encounter consistent product information whether they shop at a store, in an app or through an AI-powered experience.
Agentic Search and AI-Ready Product Discovery
A major frontier in omnichannel retail AI is search. Academy Sports is moving from static keyword search to agentic search, where AI tools interpret natural-language queries—much like a sales associate would—across channels. To make this work, the retailer is investing in AI-driven metadata and generative engine optimization so products can be discovered easily by both traditional search engines and AI models. Partnerships around open standards such as the Universal Commerce Protocol aim to let agentic AI and ecommerce platforms interact consistently. Pilot initiatives focused on conversational attributes, direct offers in AI modes and business agents signal where AI ecommerce strategy is headed: AI that not only answers questions but also surfaces the right products, promotions and content in context. For shoppers, this reduces friction in product discovery; for retailers, it enhances conversion by matching intent with relevant inventory in real time.
AI-Driven Personalization and Operational Efficiency
Behind the scenes, retail AI integration is reshaping both customer experience and operations. On the front end, richer attributes and conversational AI support highly tailored recommendations that align with local preferences, past purchases and real-time stock. Retailers use these tools to reduce cart abandonment, increase units per transaction and lift average order value by making every interaction more relevant. On the back end, AI applications help merchandising teams predict demand, refine assortments and adapt quickly to shifting trends. Supply chain systems and order management platforms synchronize inventory across stores and ecommerce so fulfillment options like buy online, pick up in store or ship-from-store remain accurate. Frequent feed updates ensure that what AI recommends can actually be delivered. Together, these capabilities turn unified commerce platforms into adaptive systems that balance personalization with operational efficiency, ensuring that promises made by AI assistants are supported by real-world logistics.
Blurring the Boundary Between Channels
As omnichannel retail AI matures, the distinction between online and in-store shopping is fading. Customers may start a journey by chatting with an AI assistant, continue it through a marketplace app, and complete it in a physical store—all powered by the same unified data and systems. Retailers like Academy Sports are designing for this fluidity, treating AI channels as first-class touchpoints rather than experimental add-ons. The strategic focus is on removing friction: making products easy to find, offers transparent and fulfillment options clear, regardless of where the interaction begins. In this model, AI ecommerce strategy and store strategy are not separate; both contribute to a coherent brand experience. As agentic AI tools grow more capable, retailers that invest in robust product data, integrated platforms and human oversight will be best positioned to deliver seamless journeys that feel natural, consistent and channel-agnostic to shoppers.