The traditional e-commerce model was conceived with a patient consumer in mind—someone willing to conduct detailed searches, compare information, read reviews, abandon carts, and return days later. Although this consumer profile still exists, its central importance is diminishing. The new frontier of digital commerce will not be determined solely by who attracts the most traffic, invests the most in media, or minimizes friction in the payment process. Instead, it will be defined by who can be selected by artificial intelligence agents capable of interpreting intentions, comparing options, and executing more and more steps of the purchase.
This transformation may seem subtle because it occurs within interfaces that are familiar to the user: they ask a question, receive suggestions, and complete the purchase. However, beneath the surface, commerce ceases to be a sequence of human actions and begins to function as a network of decisions orchestrated by systems. A milestone in this advance was OpenAI's announcement of Instant Checkout in ChatGPT in September 2025. Initially implemented with Etsy sellers in the United States, the feature is set to expand to over one million Shopify stores. Furthermore, it has been reported that more than 700 million people use ChatGPT weekly.
The crucial point is not just the volume of users, but the shift in function: the conversation moves from the discovery phase to the territory of transaction. The distinction between a chatbot and an agent is less aesthetic and more functional. While a chatbot merely responds, an agent has a defined objective, capable of searching, comparing, prioritizing, activating tools, recording preferences, refining options, and forwarding a decision. This fundamentally alters the competitive dynamic in e-commerce. Brands stop interacting only with individuals susceptible to impulses, status, or repetitive advertising; they begin to be evaluated by an intermediary that breaks down the offering into criteria such as price, delivery time, availability, reputation, reviews, return policy, and suitability to the request.
For this reason, artificial intelligence in the retail sector should not be seen merely as customer service support. According to McKinsey, 88% of respondents in their global survey stated that their companies already use AI routinely in some function. Although there is sufficient adoption to generate competitive pressure, the maturity to transform processes is still insufficient. Companies that confuse the isolated use of AI with structural capability may appear modern but remain operationally slow.
In retail, this gap between enthusiasm and implementation is even more critical. A survey conducted by Salesforce, involving 8,350 consumers and 1,700 retail decision-makers across 21 countries, indicates that 75% of retailers consider AI agents essential for maintaining competitiveness next year. The study also points out that 39% of consumers and 54% of Generation Z already use AI in product discovery, and that 63% of Generation Z expresses interest in allowing agents to purchase items on their behalf. This is a significant behavioral signal, given that a considerable portion of consumers already accepts AI as a purchasing filter.
Agents have the capacity to solve complex issues, track orders, manage returns, propose product combinations, adjust offers, detect stock shortages, monitor competitors, and initiate logistics flows. However, the deepest effect is less perceptible because these agents shorten the buying journey. When the consumer delegates comparison and screening tasks—stages where brands and retailers used to exert influence—they disappear. Less browsing means less exposure to banners, viewed storefronts, page views, and opportunities for persuasion. For the retail media sector, a delicate question arises: what happens to a model based on attention when that attention is transferred to delegation?
A valid caveat is that agents still make mistakes, depend on authorizations, face integration obstacles, and can introduce risks of privacy, fraud, discrimination, manipulation, or lack of transparency. However, the mistake lies in assuming that, because they are flawed, they will remain secondary. Any strategic infrastructure starts limited, costly, incomplete, and subject to governance. What distinguishes leaders from laggards is not prudence, but the ability to convert that caution into a structured method, using metrics, responsibilities, limits, auditing, and genuine integration into business systems.
AI agents should not be evaluated solely by cost reduction. The true benefit lies in the restructuring of commercial decision-making. The next competitive advantage will arise from the ability to make data, processes, payments, customer service, catalog, and governance understandable to these agents. A store that cannot be understood by them will become invisible in a growing share of the purchasing decision. Brands that rely only on attracting human attention will discover that the new storefront may not have screens, banners, or physical aisles; it will have defined criteria.
While digital retail was built to compete for attention, agentic commerce will be designed to contest trust, context, and execution. The central question is not whether AI agents will replace the consumer. The consumer will continue to define what is important, but will progressively delegate the effort required to reach that point. When this delegation becomes a habit, the company that continues to focus only on optimizing clicks will belatedly realize that it lost the decisive moment of acquisition: not the payment, nor the advertisement, nor the website visit, but the crucial instant when a machine determined which brands deserved to be seen.
