Retail competition used to happen on shelves and screens. AI agents are moving it to data feeds and API endpoints. The retailer with the most machine-readable, real-time product data is the one the agent recommends. Everything else is a visibility problem. That shift is already underway. AI agents are personalizing recommendations, auto-replenishing inventory, and completing purchases without a human click. The question for every retailer is not whether agents are coming. It is whether their systems are ready to be found when they arrive.
A NRF article drawing on input from retail executives and subject matter experts named 2025 the year of the AI agent in retail. The article says that digitally influenced sales already exceed 60% and that percentage will only grow as AI agents personalize recommendations, streamline decision-making, and handle auto replenishment tasks.
The article quotes Jason Goldberg, chief commerce strategy officer at Publicis, saying AI shopping assistants are poised to embed artificial intelligence into the heart of shopping experiences, forever changing the retail landscape. Agents are becoming reality as industry giants pour resources into the space, envisioning a future where the friction of shopping, endless comparisons, scrolling and decision-making is replaced by seamless, personalized assistance.
The article also notes that the linchpin for all things AI is enormous amounts of accurate, clean data. Too many retailers continue to wrestle with fragmented data across different channels, making it difficult to train and optimize AI models. The retailers that solve the data problem first will be the ones that capture the AI agent opportunity first.
Retailers Must Decide How Much to Open Up to Agents
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A Harvard Business Review article argues that autonomous AI agents are transforming how consumers discover and buy products, often completing the entire customer journey from research to checkout without a human click. The article calls this agent-to-agent commerce, noting that Amazon’s Buy for Me, Perplexity, ChatGPT and Gemini are already crawling vendor sites, reviewing options and recommending products.
The article says retailers’ decisions on agents range along a spectrum of four approaches. Fully closed vendors block AI agents from crawling their sites. Selective vendors share some data while retaining exclusive inventory for their own sites. Hybrid vendors build both a presence in agent ecosystems and a strategic moat through services available only on their own platforms. Fully open vendors expose their entire catalog, pricing and inventory to any agent that queries it.
The article argues that retailers with sufficient market clout might consider building dedicated agent-facing infrastructure, a site optimized for machine-readable data rather than human browsing. Feeds to agents should be optimized for visibility and inclusion in agent recommendations. Some inventory should remain exclusive to the vendor’s own site, including limited products, premium bundles, and loyalty multipliers. Early movers who collaborate strategically with agent ecosystems can shape the rules of engagement, while laggards risk losing both visibility and control over the customer relationship.
The Retailers Building AI-Native Operations Are Already Pulling Ahead
A World Economic Forum article from Apparel Group, a retailer with more than 85 brands, 2,500 stores and 14 markets, describes how the company rebuilt its operating model around AI rather than layering tools onto existing workflows. The article argues that the old retail formula of the right brand, the right location and efficient scale is no longer enough. The next decade will belong to companies built on intelligence.
The article says AI is reshaping every layer of the retail operating model, from how products are designed and priced to how customers are served and how stores are run. Predictive models continuously read customer signals, regional trends and operational data, then recommend or auto-execute the right product mix in the right store at the right time, reducing stockouts, excess inventory and working capital requirements.
At Apparel Group, the article says, AI-driven forecasting, allocation and replenishment are live across major brands. Pricing intelligence is optimizing sell-through and margins. AI-driven shift scheduling is improving workforce planning across stores. Autonomous AI agents are helping employees across merchandising, finance, procurement and retail operations by removing friction from daily decisions so teams can focus on higher-value work. “Becoming an AI-native enterprise,” the article concludes, “is, ultimately, less about deploying software and more about changing how decisions are made.”
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