The AI Evolution From Tools to Autonomous Collaborators

We are closing the chapter of "query AI" to open the book of intelligent execution.

Over the past few years, our interaction with artificial intelligence has been fundamentally reactive, limited by the "chat box" that accustomed us to requesting isolated tasks. However, in the business ecosystem of 2026, that initial phase of wonder has given way to a need for deep utility. We are crossing the frontier toward Agentic AI, a paradigm where technology stops being a passive interlocutor to become an actor that plans, decides, and executes from start to finish.
This evolution is the step from having a brilliant librarian to having a project manager capable of operating with autonomy. Projections leave no room for doubt: after 2025, where agent deployment grew by 119% in the first half alone, Gartner estimates that by 2028, one-third of enterprise applications will be agentic, transforming what was an experimental trend into the new standard for global competitiveness.

To understand the depth of this change, we must stop viewing AI as a simple language model and start understanding it as a system with a "digital body." An agent does not just process text; it uses its reasoning capacity to interact with the world by profiling its role, decomposing complex problems, and actively using external tools. This capacity for execution and real-time self-correction is already yielding tangible results that redefine operational efficiency.

In sectors of high technical complexity, such as software engineering, agentic systems already solve more than 12% of critical errors autonomously, a figure that triples the capacity of isolated models from just two years ago. What previously required constant human supervision for every line of code is now managed by systems that not only identify the problem but also implement the solution and verify its success.

However, the true revolution does not reside in the solitary agent, but in multi-agent systems (MAS). If an autonomous agent is a talented professional, a multi-agent system is the equivalent of a corporate department working in perfect synchrony. Instead of forcing a single AI to be an expert in everything, today we design specialized "crews" where each member fulfills a critical function: one researches the market, another analyzes financial viability, and a third refines strategic communication.

Research from Microsoft has shown that this collaboration increases accuracy in complex tasks by up to 45%, drastically mitigating the "hallucinations" of the models. In 2026, we no longer talk about implementing AI, but about orchestrating intelligences. In fact, 60% of organizations already plan to integrate AI as an active and responsible member of their teams, shifting the narrative from "tool" to "collaborator." From a strategic management perspective, the economic impact of this transition is massive.

Recent estimates from IDC suggest that AI could contribute up to US$19.9 trillion to the global economy by the end of this decade, with a surprising investment multiplier: for every dollar invested in AI solutions, an indirect return of nearly US$5 is expected. But as CEOs, our focus should not only be on financial ROI, but on the reconfiguration of human capital. The 2025 PwC Barometer reveals that sectors most exposed to AI have seen revenue growth per employee three times higher than the rest. This forces us to rethink leadership: our role is evolving into that of a digital orchestra director.

The goal is to free up that 90% of time that was lost in bureaucratic and research processes to reinvest it in strategic vision and ethics. Finally, we must understand that agentic AI represents the definitive step from static intelligence to dynamic intelligence. In this new era, a company's competitive advantage will not be measured by the power of its servers, but by the efficiency of its agent network and the clarity of its governance. It is no longer about what AI can tell us, but what it can achieve for our organization. The leap to the era of action is already here, and success will belong to those leaders who stop using isolated tools and start directing autonomous ecosystems of value.