By: Sebastián Borgeaud, Business and Transformation Manager, SYM
Over the past few years, many organizations have grown accustomed to talking about Artificial Intelligence as if it were a promise perpetually under construction. Pilots, proofs of concept, isolated initiatives—but very few structural decisions. That period now appears to be coming to an end.
What lies ahead in 2026 is not simply a more advanced version of the technology, but a shift in the place AI occupies within organizations. The discussion moves away from technical capabilities and begins to enter a more uncomfortable territory: how decisions are made, who makes them, and under what logic.
This is where the real turning point lies. AI ceases to be a matter of technological adoption and becomes an issue of organizational design. It is not about adding tools, but about rethinking structures, decision-making flows, and ways of working that for years have been taken for granted.
The first wave of AI was driven by efficiency: automating, optimizing, accelerating. It was useful, but also limited. Doing the same things faster does not change the core of the business. The stage ahead is different: AI begins to intervene in how priorities are set, how work is coordinated, and how human capabilities are combined with mechanized systems. When that happens, technology stops being mere support and starts to directly influence strategy.
For Chilean companies, this shift is not insignificant. In a context of stagnant productivity, growing competitive pressure, and increasingly tight margins, AI can no longer be treated as an experimental project or as an isolated business initiative. The question is no longer whether to adopt AI, but for what purpose, where, and under which strategic criteria to do so.
This change forces organizations to confront decisions they have long postponed. Which processes must remain human? Which decisions should no longer be intuitive, but objective? Where does it make sense to apply advanced analytics? How is an organization structured and governed when people and intelligent models coexist, making decisions together? Trust, data governance, and analytics cease to be technical issues and become strategic conditions for operating at scale and with sustainability.
The year 2026 will not be determined by the size of models or the amount of available computing power, but by the quality of the decisions organizations are able to make with their help.
For this reason, the true challenge AI poses toward 2026 is not technological. It is strategic. The companies that lead will not be those that adopt more AI, but those that dare to integrate it intentionally into their culture, their structure, and their way of deciding. Because, ultimately, the question is no longer what AI can do, but what kind of organization we want to build with it.
