Multiagent orchestration: the new operational model

In the past two years, the race for Artificial Intelligence has been marked by a recurring question: what is the best model?

Every month, more capable, cheaper, and accessible agents emerge. What once required specialized teams and million-dollar investments can now be subscribed to. The trend is clear: AI agents are quickly becoming infrastructure—available to virtually all companies.

But if everyone will have access to the same agents, where will the competitive advantage lie?

Market signals suggest that it will not lie in the agents themselves, but in the ability to coordinate them. The State of AI 2025 report from McKinsey shows that only 23% of companies have managed to scale agent systems in their operations, while the majority remain stuck in the experimentation phase.

We may be facing a change similar to that triggered by industrial automation. Back then, the advantage shifted from the machines themselves to how they were integrated into production processes. Now, the differentiator seems to be migrating again: from the individual capabilities of the agents to the capacity to orchestrate hundreds (or thousands) of them around business objectives.

The question that leaders should ask is no longer “which agent will we adopt?”, but rather: what will our operational model be when a significant part of intellectual work is executed by hybrid teams made up of humans and digital agents?

Recent technology history shows that sustainable competitive advantages rarely remain tied to the tool itself. ERP became a commodity. Cloud computing became a commodity. Analytical platforms, once limited to a few organizations, are now part of the everyday life of companies of all sizes. Everything indicates that multi-agents will follow the same trajectory.

What changes when specialized intellectual capacity ceases to be scarce?

Perhaps the answer lies in a deeper change: the competitive advantage shifts from execution to the design of the organization. For decades, companies were structured to coordinate people, distribute activities, consolidate information, and make decisions. In an environment where a significant portion of these tasks is performed by autonomous agents, the differentiator shifts from merely hiring talented professionals or acquiring advanced technologies. It becomes about building organizations capable of learning continuously, preserving knowledge, and reorganizing their capabilities at the speed demanded by the market.

This movement could produce impacts similar to those observed during industrial automation. Mechanization did not eliminate production leaders, but drastically reduced the need for roles dedicated solely to supervising repetitive tasks. The orchestration of multi-agents seems to point toward an equivalent phenomenon in intellectual work.

Much of middle management is still focused on consolidating data, monitoring deliveries, distributing tasks, and producing reports. These are important activities, but also highly susceptible to automation. This does not mean there will be fewer leaders, but rather that the role of leadership tends to change in nature. Managers will transition from being execution supervisors to taking on higher value-added roles, such as designing workflows, establishing decision criteria, supervising exceptions, training agents, and ensuring that the intelligence produced by the organization remains aligned with its strategic goals.

Perhaps the most relevant transformation lies precisely in the relationship between companies and knowledge. For decades, organizations were evaluated based on their ability to attract talent. However, much of corporate knowledge remains dispersed in conversations, presentations, individual experiences, and decisions that are rarely recorded in a structured way. When professionals leave the company, a portion of this context simply disappears.

The orchestration of multi-agents opens the possibility of creating something unprecedented: organizations that learn continuously and forget less and less. Negotiations, exceptions, project learnings, strategic decisions, and team interactions may cease to depend exclusively on people’s memory and instead compose a living organizational memory, accessible and reusable by humans and agents.

Building this organizational memory, however, is not a theoretical discussion. Experiences accumulated by Objective in data engineering, architectural modernization, and automation initiatives show that organizations capable of structuring previously dispersed information are already beginning to transform knowledge into a reusable asset at scale. 

In a project conducted alongside Bauducco, for example, the restructuring of the data architecture eliminated operational bottlenecks, increased scalability, and accelerated the development of Artificial Intelligence solutions. Although the initiative was not originally designed for multi-agents, it underscores an important point: companies that invest today in data, integrations, and platforms are, in practice, building the necessary foundations to operate tomorrow with hybrid teams composed of people and digital agents. 

It is at this point that the true distinction arises between companies that will experience spot productivity gains and those that will consistently capture value. The former will see agents as tools capable of executing specific tasks. The latter will understand that the opportunity lies in redesigning the very way they operate.

In the future, perhaps organizations will be composed not just of areas, departments, or teams but by hybrid cells made up of dozens of professionals and thousands of specialized agents, working in coordination to solve problems, explore opportunities, and accelerate decisions.

The multi-agent revolution may not just be a technological revolution. It could represent the greatest transformation in management models since the popularization of the internet.

Companies that view agents merely as instruments of efficiency will likely gain productivity. Companies that understand orchestration as a new operational model may redefine how they learn, adapt, and create competitive advantage.

If this topic is also being discussed in your company, we would be happy to exchange experiences. Get in touch with us for a coffee, virtual or in person, to explore how to build the necessary foundations for this new operational model.

Frequently Asked Questions on the Topic