ChatGPT has become just a shopping channel. Walmart is ready, but most retailers are not
OpenAI just announced that consumers can now purchase products directly within ChatGPT. Meanwhile, he loves big retailers Walmart We already see that one in five referral clicks comes from ChatGPT. In a matter of months, AI agents have gone from a fun novelty to a business necessity, representing one of the fastest shifts in consumer shopping behavior since the advent of the Internet.
But ChatGPT shopping isn’t just a new sales channel, it’s a stress test that reveals a hard truth: AI runs on data, and most retailers’ data isn’t ready.
Shoppers now expect an AI agent to answer questions like, “Who can deliver my patio heater by Saturday?” Or “Where is the best price for a Dyson vacuum today?” These answers don’t come out of nowhere, they come directly from the retailer’s own systems. If inventory is siloed, prices mismatch across channels, or fulfillment timelines are out of date, the agent will give the wrong answer. When a promise is broken, it doesn’t just cost a sale. It erodes trust in both the retailer and the AI itself.
Walmart is one of the exceptions that prove the rule. I work for a company that helps Walmart automate and standardize their data systems. Through years of supporting their integrations and data operations, I’ve seen first-hand how a retailer has invested in making data a true competitive advantage. They prioritized connecting their ERP, inventory, and fulfillment systems — infrastructure that now allows AI agents to confidently display Walmart product information. That’s why they’re seeing an increase in ChatGPT referral traffic. For most retailers, the same query may uncover outdated prices, bogus inventory, or missed delivery slots.
It’s not about building a flashy chatbot or trying to “own” the front end of shopping with AI. Leave that to AI platforms. The real work is the plumbing: clean, real-time, comprehensive data. If your systems cannot provide reliable answers, AI will simply skip you. In a world where consumer habits are rapidly forming, disappearing from the funnel now could mean disappearing forever.
How should retailers respond? First, by treating data as a strategic asset, not an IT afterthought. This means hiring leaders who understand integration as a growth lever, not just a cost center. This means reorganizing so that operations, digital and promotional teams are working on the same data, not fighting over conflicting versions of the truth. This means investing in systems that update in real time, rather than batch processes that are designed to match the pace of yesterday’s trading.
Second, retailers need to build technical resilience. This doesn’t just mean buying new tools; It means designing architectures where prices, inventory, and logistics are closely linked enough to withstand the demands of AI-driven discovery. Retailers who continue to treat these functions as separate areas will find themselves invisible in the world of AI research.
These latest shifts continue the transformational journey that retailers have gone through in moving from brick-and-mortar stores to online sales, to mobile sales, and then to social media. Now they face a new challenge as the concept of multichannel sales continues to expand.
The era of AI trading has arrived, and it is moving faster than most executives expected. The retailers that survive will not be the ones with the biggest marketing budgets, but those whose systems can talk to AI. Success will come to companies that align technology and organizational priorities around one goal: making their data trustworthy, current, and connected. Those who don’t risk being left out of the conversation entirely.
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