26 • November / December 2026• abasto.com A reflection by Jack Dorsey, an American entrepreneur and programmer, co-foun- der of Twitter and founder of Square, now known as Block, on the shift from hierar- chy to intelligence helped me put a name to a different possibility: building a living model of the operation that maintains the context of what should happen, compares it with what is actually happening, and re- commends the next best course of action. It’s not simply a matter of giving every manager a ChatGPT license. It’s about as- king ourselves how AI can change the way we coordinate work. Let’s imagine Camila, a merchandiser who is starting her day. Before she leaves, the system has prioritized her store visits based on the brand’s objectives, stockout risk, current promotions, and new arri- vals at each store. When Camila finds an incorrect display, she doesn’t just report it for someone to re- view two weeks later. The system understands the context and recommends how to resolve it right then and there. The system logs the action taken so that the next recommendation can be even better. The process ceases to be merely a repor- ting system and becomes a learning cycle: Observe. Understand. Prioritize. Act. Verify. Learn. The Human Contribution Is Irreplaceable This does not make the person in the field any less important. It does the opposite: it can make them the best-informed node in the entire organization. People contribute what technology has not yet fully mastered: reading the environment, trust with the merchant, negotiation, creativity, intuition, and the ability to handle exceptions. AI pro- vides historical data, alerts, and recom- mendations at the exact moment they’re needed. Supervision doesn’t disappear either. It changes roles. Instead of spending much of the day chasing reports, relaying ins- tructions, and compiling updates, you can focus on developing talent, resolving exceptions, supporting complex negotia- tions, and improving execution quality. That difference may seem small, but it can transform an operation’s economics. Until now, growth meant hiring more people. More people required more coor- dination; more coordination added layers, and more layers increased the distance between what happens and the decision made. With AI comes another possibility: scaling the organization’s intelligence wi- thout increasing its hierarchy in the same proportion. Speed and Effectiveness Lead to Success That’s why the compe- titive advantage won’t go to the company that purchases more licenses, builds more dashboards, or accu- mulates more data. It will go to the one that reduces the time between execution and learning. An organization that takes two weeks to res- pond to a product that’s out of stock will have enormous difficulty competing with ano- ther that detects the same problem, defines a course of action, and learns from it in two hours. The relevant ques- tion is no longer how much information a company possesses. It’s how quickly it can turn that information into a better decision. And there remains an even more uncom- fortable question: if we could design our organizations from scratch today, relying on a system that main- tains the context of the operation and guides decisions in real time, would we build them exactly as they are now? Probably not. • Continuation of page 24 • TECHNOLOGY FOCUS