For years, talking about Artificial Intelligence (AI) in logistics meant talking about pilot projects and tests that generated more headlines than real impact. That scenario has changed. By 2026, AI is already part of the daily operations of many supply chains and is used to solve very specific problems, not to fuel futuristic promises.

It’s no longer just about saying that AI is being used, but about applying it effectively in day‑to‑day operations. To do that, it must be deployed where it provides immediate value.

In practice, AI is already being used for tasks such as:

• Anticipating demand peaks and adjusting shifts, inventory, and transportation in advance
• Managing incidents without overloading operational teams
• Reducing distances traveled, time, and fuel consumption in transportation
• Automating administrative processes that previously required manual intervention

This tangible use is what separates a rigid supply chain from one capable of adapting when something deviates from the plan.

Amazon is one of the clearest examples of real AI use in operational optimization. Its systems combine historical and real‑time data to forecast demand levels and decide in advance where inventory should be located, how to organize order preparation, and which delivery routes to follow.

The goal is clear: absorb spikes in orders without oversizing the logistics network and maintain operational reliability even during high‑volume periods.

In transportation, UPS uses its ORION system to plan delivery routes. The algorithm determines the optimal sequence of stops for each driver every day, taking into account traffic, number of deliveries, and real road conditions.

Since its large‑scale deployment in the United States in 2016, ORION has helped eliminate around 100 million miles per year, significantly reduce fuel consumption, and improve delivery reliability in a network that operates tens of thousands of daily routes.

The difference doesn’t lie in having more technology, but in making the right decisions at the right moment. Logistics chains that integrate AI into their daily operations don’t wait for problems to become obvious: they detect them early and act with enough time to respond.

In markets characterized by variability and constant peaks, working with foresight results in more efficient and profitable logistics, and enables a better customer experience.