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Walmart and OpenAI’s October partnership could be the most significant shift in e-commerce since the “Buy Now” button.
By integrating ChatGPT, Walmart is collapsing the shopping funnel. No search bar. No cart page. Just conversations that lead directly to checkout. This new approach could rapidly redefine how every brand approaches customer discovery, data, and demand.
The new shopping platform lets shoppers chat with the AI-powered bot, browse Walmart’s offerings, and complete purchases from within the app. If ChatGPT and other AI assistants become entry points for retail customers, retail experts warn that the e-commerce funnel may no longer be viable.
According to Josiah Roche, Fractional CMO at JRR Marketing, when ChatGPT becomes the central place people shop, it will flip the performance marketing on its head. When people skip search results and move straight from chat to checkout, pay-per-click, search engine optimization, and even social media funnels lose their power.
“Because discovery will move from brand strategy to the agent’s decision layer, the brands that will win are the ones keeping product data clean, transparent, and detailed,” he told the E-Commerce Times.
How AI Is Reshaping Retail Expectations
Things like price accuracy, shipping times, and verified reviews matter a lot, Roche noted. AI will favor clarity and consistency over ad spend or brand bias.
This new model can grow faster than China’s WeChat or Taobao because it removes the extra steps. People won’t need to open an app or dig through filters. They’ll say what they want and get matched right away, he explained.
“So agentic commerce runs on intent instead of browsing behavior. Every chat becomes both a search and a sale,” Roche said.
It is not some marketplace algorithm guessing what fits best. Instead, it is a system that responds with precision. The speed of adoption will depend on how smooth that process is between what users say and when checkout begins, he offered.
Manick Bhan, founder, CEO, and CTO of SEO firms Search Atlas and LinkGraph, concurred, noting that WeChat and Taobao fused content, social, and commerce into one seamless experience.
“But that’s still human navigation. You’re tapping, scrolling, opening mini programs,” he told the E-Commerce Times.
Competing Models of Agentic Commerce
Bhan explained that agentic commerce removes the interface. Consumers tell the AI agent what they need. It handles the entire funnel, discovery, comparison, and checkout inside a single reasoning loop.
“It doesn’t rely on people adopting an ecosystem. So you go from an app-based journey to a zero-interface journey. That’s a fundamentally different speed of conversion,” he said.
Loc Dang, marketing executive at Mim Concept, defined the Chinese ecosystem as social, transactional, and gamified. Nonetheless, it requires user action and the effort is human-driven, he agreed.
Chinese retail models like WeChat Mini Programs and Taobao have already integrated social, content, and commerce seamlessly. The agentic commerce approach by Walmart and OpenAI is fundamentally different and potentially faster at achieving scale and conversion over Chinese models, he offered.
“Walmart and OpenAI made it better because it doesn’t ask the user to choose; it acts. Since ChatGPT understands context and preferences, you only need to define what you want, and it handles the rest. This beats the Chinese model that still requires manual effort,” Dang told the E-Commerce Times.
Fundamental Differences in E-commerce Approaches
Chinese platforms have mastered e-commerce integration and are among the most sophisticated retail systems globally, observed Shomron Jacob, head of machine learning and platform at Iterate.ai. He assessed agentic commerce as not necessarily better, but as architecturally different.
“Chinese platforms excel at visual discovery and tap-based navigation through personalized feeds. If you know what category you want, their UX is exceptionally efficient,” he told the E-Commerce Times.
Jacob explained that agentic commerce uses natural language as the primary interface. Using language instead of layered menus can speed complex, multi-attribute decisions compared with filtering nested categories.
“The AI agent can also maintain context across sessions and retailers, reducing comparison shopping friction. However, Chinese platforms have scale, proven conversion rates, and years of optimization,” he added.
Agentic commerce is still experimental. The real question is not so much which is faster but whether conversational interfaces solve problems that visual interfaces do not. Jacob noted the problem-solving result has yet to be proven at scale.
He sees this as the central tension in agentic commerce. The reality is that every commerce platform balances user intent with monetization.
For instance, Google ranks ads above organic results, while Amazon promotes sponsored products. Users tolerate this when the trade-off is transparent, and the results remain relevant, according to Jacob.
From Conversational Shopping to Predictive Buying
Roche sees trust still as the big hurdle. Google earned it by staying neutral for years, even though paid spots later changed that.
“For OpenAI and Walmart, people will judge them based on transparency. If shoppers sense bias toward paid listings, they’ll pull back,” he predicted.
The first AI agent that explains why it recommends one product over another will win trust early. People do not need total neutrality. They want honesty about what affects those suggestions, Roche added.
On the tech side, brands will need to rebuild their backend systems. Product feeds have to work for conversations, not just for search indexing. So that means better tagging, real-time pricing updates, and tighter integration with the API for checkout.
“The next step after conversational shopping will be predictive buying. That’s when systems start filling up your basket before you even ask, based on patterns or needs,” he said.
Roche warned that when that happens, control moves to whoever owns the data on intent and preference. That is where the next traffic war begins.
Predictive E-commerce Now Underway
According to Rafay Baloch, CEO and founder of cybersecurity firm RedSecLabs, Walmart’s ChatGPT shopping launch underscores how predictive e-commerce reduces search-intent errors by directly fulfilling customer needs. By removing those friction points, the model can operate faster than China’s retail systems without relying on layered navigation.
“Organizations must compete to win customer trust because this competition will determine which business will achieve success,” he told the E-Commerce Times.
It directly counters Google’s ad-based strategy. AI assistants need to demonstrate their ability to recommend appropriate content rather than display paid advertisements. The central conflict occurs because the AI system functions as both a customer service representative and a sales agent, noted Baloch.
This holiday season marks the moment AI truly enters the shopping aisle, said Greg Petro, CEO of First Insight. Referring to holiday shopping reports, he noted that consumers are using it for more than searching.
“They’re buying through it. At the same time, they’re more cautious about spending, focusing on price, value, and convenience. Retailers that listen to their customers and adapt quickly to these new buying behaviors will be the ones building loyalty that lasts long after the holidays,” he told The E-Commerce Times.
Agentic AI Challenge
The term ‘agentic commerce’ implies that the AI acts on the customer’s behalf. When the AI begins to act as a sales agent for the retailer or the highest-bidding brand, it stops being an agent and becomes an ad network with a friendly face.
“If it becomes biased to the highest bidder, it loses the power that makes agentic commerce work — meeting users’ intent. At first, it seems like a good option for retailers. Eventually, it becomes their ladder to the bottom,” Dang warned.
According to Bhan, the second the AI shifts from being your fiduciary to being the retailer’s sales agent, trust may evaporate — and if trust collapses, the whole model collapses. People will only shop through an agent if they believe it is aligned with their interests, not the highest bidder.
“So the real battle in agentic commerce isn’t Google versus OpenAI, but consumer-aligned agents versus retailer-aligned agents. Whoever wins that alignment battle wins the next decade,” he predicted.
Bhan sees algorithmic transparency — not a pop-up or a buried disclosure — required in these platforms to ensure transparency and ethical recommendations. It must present a clear, simple explanation of why the AI recommended something. Was it the best price, quality, reviews, or was it because a brand paid for placement?
“If we don’t establish that transparency now, we’re just rebuilding the worst parts of digital advertising inside a conversational interface — and that’s the fastest way to destroy trust in agentic commerce,” he warned.