Don’t Just Get Recommended by AI. Earn its Trust

For decades, retailers have optimized commerce experiences for human shoppers. However, the next era of e-commerce will require retailers to make their products transactable by machines.

Artificial intelligence-assisted shopping is accelerating, with 41 percent of shoppers using AI assistants to research products, 33 percent look for reviews, and 31 percent search for deals. This consumer behavior is already translating into measurable retail traffic. Between October 2024 and May 2026, referral traffic from AI platforms to retail sites increased 1,324 percent, suggesting that is AI evolving from a discovery tool to a purchasing agent. As that shift unfolds, brands and retailers will increasingly compete to have their products included in AI-generated recommendations.

Succeeding in AI-powered commerce will require more than product visibility. Retailers must have the data and operations in place to ensure AI agents can find, recommend, and reliably fulfill products. And getting there is more complicated than it sounds.

Retailers Must Earn the Trust of AI

Human shoppers browse and compare, and they may overlook a bad product image or errors in a product description. But AI agents are less forgiving and more likely to treat those inconsistencies as signals that a product cannot be trusted.

AI agents make decisions based on structured data like product details, inventory, delivery time, and seller reliability. If any of that information is incomplete or incorrect, the agent may skip surfacing the product altogether. Yext's recent analysis of 6.8 million AI citations across ChatGPT, Gemini, and Perplexity found that 86 percent of generative AI answers draw from brand-managed, structured sources rather than open web content.

Rather than simply capturing a shopper's attention, retailers must now earn the trust of AI. That means giving AI agents accurate, up-to-date information required to confidently recommend a product.

However, being recommended is only the first step. If retailers cannot reliably deliver on those recommendations, they risk being passed over the next time an AI agent decides what to surface.

The Backend is Becoming Retail’s Biggest Liability — and Opportunity

Retailers have spent a fortune on the online storefront, perfecting their user experience, site speed, and omnichannel marketing to attract human shoppers. But behind the scenes, many still rely on fragmented operations, from disconnected supplier data and stale inventory feeds to manual fulfillment processes.

Front-end investments have a clear, measurable impact on conversion, while back-end infrastructure remains invisible until something breaks.

As AI agents rely more on operational data to evaluate products and complete purchases, this often-overlooked part of the retail experience will quickly become retailers’ biggest liability.

Fulfillment performance will increasingly influence which products AI agents surface. Repeated stockouts or late deliveries could train those systems to favor more reliable alternatives. Once that pattern is established, winning back visibility is far more difficult.

What it Actually Takes to Be AI-Ready

Avoiding that outcome starts with getting the fundamentals right. Retailers need consistent supplier and fulfillment data across suppliers, warehouses, and third-party logistics providers. Next, retailers need to ensure their product data is accurate, complete, and machine-readable. Simply logging data in a spreadsheet or PDF catalog won't suffice. Lastly, retailers need greater visibility into their operations to make more informed fulfillment decisions that balance cost, speed and reliability.

Retailers that prioritize these back-end capabilities will be better positioned to earn recommendations and establish reliability with AI systems. OpenAI has clearly outlined guidelines for retailers to ensure ChatGPT surfaces the right products, including updated information on pricing, inventory, shipping, and returns. Together, this data makes it easier for AI agents to find relevant products and complete purchases on a shopper’s behalf.

Retailers must move beyond hoping AI recommends their products to prioritizing their ability to fulfill those recommendations reliably.

AI Shopping is Moving Faster Than Retail Infrastructure

AI shopping is changing at a pace retail infrastructure was never built to match. In recent months, AI shopping experiences have moved deeper into product discovery and merchant-connected checkout, shortening the distance between recommendation and purchase. Retailers face a longer clock. Cleaning supplier data, synchronizing inventory, and strengthening fulfillment controls can take months. That timing gap makes this moment especially consequential. Retailers that start now can build the necessary foundation while AI shopping behaviors are still taking shape.

Omar Qari is CEO of Logicbroker and a member of the Industry Partner Council at the National Retail Federation.