In a context where AI is establishing itself as a historical turning point comparable to the advent of the Internet, AI agents are redefining the way in which companies operate, innovate and compete.
In a context where AI is establishing itself as a historical turning point comparable to the advent of the Internet, AI agents are redefining the way in which companies operate, innovate and compete. Leaders can no longer simply observe: they must decide how to integrate these new digital players into their operating model, otherwise they will be relegated to the rank of followers. But before unleashing the full potential of the “agentic” enterprise, a central challenge must be met: that of interoperability.
Capable of acting autonomously, AI agents usher in a new era: that of a continuous and adaptive dialogue with the company and its stakeholders. Their role is not to replace, but to transform: they take charge of tasks with low added value to free employees up for what requires intuition, creativity and judgment. Today, most agents still operate in silos, carrying out isolated missions. Yet the real promise lies elsewhere: in the ability of agents to collaborate with each other, beyond technologies and suppliers, to orchestrate entire value chains. This is where the future of enterprise AI is at stake. Achieving this maturity is now a strategic imperative, a condition for unprecedented efficiency, massive productivity gains and new growth drivers.
Let’s take an example: for customer service, a digital agent can manage a product return request by simultaneously relying on a manufacturer’s agent for damage assessment and a logistics agent for organizing transport. For sales, a sales agent can detect a partnership opportunity, automatically negotiate with the prospect’s agent and prepare a tailored proposal for account teams. It is these multi-agent collaboration scenarios that herald a disruption in the way we offer value to the customer. But to achieve this, we must take a step forward. The evolution follows four levels of sophistication: from the one-off assistant (level 1) to the execution of multi-system tasks (level 3), up to the “operational nirvana” of level 4: multi-agent orchestration. Each company must ask itself about its level of maturity and the levers to activate to take the next step.
This increase in power requires clear conditions: a robust governance framework, including supervision, traceability and security; harmonization of data to guarantee quality and availability; and seamless integration with existing systems. This is not only a technical question, but a corporate governance issue, which calls for clear decisions on the part of managers.
On a sectoral scale, the issue is just as decisive. Open standards like Model Context Protocol (MCP) and Agent-to-Agent (A2A) define a common language. Without them, the risk is that of a fragmented ecosystem where agents become additional silos, repeating the mistakes of the past. With them, the company can build an interoperable, secure and sustainable digital fabric.
The question is therefore simple: do we want AI to further fragment our organizations, or on the contrary to become the force that unites them? Moving to an agent-first business isn’t about tools. It is a cultural and organizational transformation. It is about rethinking the value chain, breaking down silos, and imagining a hybrid model where humans and AI agents co-create performance. This strategy prepares for the emergence of a true “Gen Agent workforce”: an augmented workforce where AI agents become the new interface for digital work, the engine of an economy estimated at $6,000 billion.
We are entering a new era, that of the orchestration of AI agents. Those who know how to build an interoperable and trusted architecture today will get a head start, transforming every constraint into an opportunity. The real question is no longer whether AI will transform our businesses: it is to decide how we, as leaders, will shape this transformation.
