> ## Content Index > Fetch the complete content index at: https://roelwillems.com/llms.txt > Use this file to discover other available public pages before exploring further. # Agentic Commerce and the Retail Reality Gap - URL: https://roelwillems.com/agentic-commerce-and-the-retail-reality-gap/ - Published: 2026-03-09T13:13:53.000Z - Updated: 2026-09-16T14:10:35.000Z - Description: We built models to predict grocery baskets. The better they got, the smaller the baskets became. Google, Meta, and now OpenAI have tried to bolt shopping onto their platforms. The disruption never lands. The gap is not compute power. It is a misunderstanding of how people actually shop. - Author: Roel Willems - Tags: Agentic AI & Its Limits, AI Shopping, Essays We built increasingly accurate models to predict a customer's grocery basket. The better the predictions got, the fewer items customers removed from the suggested list. And the fewer items they removed, the smaller their baskets became. They were still visiting the store afterwards, more frequently in fact, picking up things they had forgotten. The model excelled at predicting what people would probably need. It just missed what they would want. Google tried to make shopping work inside search. Then Meta tried it inside social feeds. Now OpenAI and others are trying it inside a chatbot. The pattern is consistent: a powerful platform with massive reach bolts on shopping, launches with impressive demos and a handful of merchant logos, then quietly scales back when reality sets in. OpenAI recently shifted from direct checkouts inside ChatGPT to purchases through retailer apps like Instacart and Target. The handful of merchants that had actually gone live out of Shopify's millions likely tells you why. OpenAI is not walking away from ecommerce. It just learned the hard way that adding a buy-now button to a chat interface is not innovation. The models keep getting better. The headlines keep promising. Reality keeps proving harder than the pitch. The instinct is to treat this as a timing problem. But integrating shopping into general-purpose platforms has swallowed ambitious companies whole for twenty years, and the obstacles have never been purely technical. Take a single product like yoghurt. Fat content, sugar, organic, brand, size, flavour, pack size, packaging type: dozens of attributes that matter to a customer. Multiply that across hundreds of thousands of products, vastly different categories, and millions of merchants. The standardization challenge alone is staggering. Merchants will not surrender control of the customer experience unless the distribution payoff is overwhelming. And no one has figured out the consumer flow: the actual moment-to-moment experience of deciding what to buy through someone else's interface. There is a deeper issue. The current wave of agentic commerce assumes that shopping is fundamentally an optimization problem: compare specs, weigh reviews, find the best price, execute. If that were true, the models we have today would already be transforming retail. They are extraordinary at comparison, synthesis, and reasoning across large datasets. But that is not what most shopping actually is. Apple's $599 [MacBook Neo dominated headlines last week](https://news.google.com/stories/CAAqNggKIjBDQklTSGpvSmMzUnZjbmt0TXpZd1NoRUtEd2lqeGNUU0VCRUVaS0N2ajNaU0dpZ0FQAQ?hl=en-US&gl=US&ceid=US%3Aen&ref=roelwillems.com). PCs with comparable specs have been available at that price for years. No one noticed. No media coverage. That is the reality no agent can navigate by comparing specifications. A grocery basket of forty items is shaped by your life stage, how many mouths you are feeding, how busy your week looks, what you had for dinner yesterday, whether guests are coming on Saturday, and your mood walking into the store. No model optimizing for price and specs is even asking the right questions. None of this means agentic AI will not matter in retail. It will. But likely not in the way the current headlines suggest. Standardized shipping containers were designed to move goods cheaper. Their real impact was the reorganization of global manufacturing. Nobody pitched containers as the thing that would move factories to Asia. The same pattern will hold here. The real impact of agentic AI will come from two places. First, solving hard operational problems that have resisted automation for decades: supply chain coordination, demand sensing, inventory optimization across thousands of interdependent variables. All in real-time. These were simply too complex to tackle only a few years ago. AI is already changing that. Second, from something we cannot yet describe, because the analogy for it does not exist yet. It will not be a buy button in a chat interface. It will be something that reshapes what shopping means entirely. Do not build your strategy around that assumption. The bigger unlock is not at the point of purchase. It is at the point of understanding. Conversational AI can help a customer figure out what they actually need in ways that no product page, review section, or comparison tool ever could. That alone will reshape how people shop, long before any agent places an order on their behalf. An agent can compare ten thousand products in seconds. The list will be perfect. It just will not be right. The real disruption in retail will come from something none of us can see yet. It always does, predictably. > **Working on this yourself?** I help leadership teams turn data and AI strategy, governance and regulation into decisions that hold up in practice. Happy to think it through with you in a 30-minute call. No pitch, no deck. [Book a call →](https://calendar.proton.me/bookings?ref=roelwillems.com#U55oObZbsFTKwQVQy9CUhGPRb5WIgEQ3Ol7vtoCcJH0=) ## Sign up for Data & AI: What Matters & Why Essays for senior leaders on data, AI and governance. Only when there's something worth your time. Subscribe Email sent! Check your inbox to complete your signup. Unsubscribe anytime.