AI Agents and the Target Operating Model

This evolution moves the AI discussion from a purely technological domain to that of the operating model. The challenge is no longer simply to deploy AI solutions, but to rethink how the organization operates, makes decisions and creates value. In this context, the concept of the Target Operating Model becomes central.

AI agents as new actors within the organization

AI agents can be viewed as new actors within the organization. They operate alongside human teams to execute processes, support decision-making or orchestrate information flows. Their value lies in their ability to operate continuously, process large volumes of data and apply complex rules consistently. However, the introduction of AI agents profoundly alters organizational balances. It raises questions about the distribution of roles between humans and systems, the nature of responsibilities and coordination mechanisms. Without a clear framework, the risk is to multiply isolated initiatives that are difficult to manage and sustain over time.

The Target Operating Model as a structuring framework

The Target Operating Model provides a target vision of how the organization operates while fully integrating AI and automation. It defines how processes, roles, tools, governance and skills are articulated to achieve strategic objectives. In the context of AI agents, the Target Operating Model becomes a tool for clarification. It helps answer structuring questions: which processes are partially or fully handled by AI agents, which decisions remain the responsibility of human teams, how interactions are organized and how performance is managed. This framework prevents fragmented AI adoption and embeds agents within a coherent overall logic.

Redefining processes and value chains

The integration of AI agents leads to a reconfiguration of business processes. Some processes are automated end-to-end, while others become hybrid, combining human intervention and automated action. This transformation is not only about accelerating existing workflows, but about rethinking work sequences, control points and responsibilities. In an AI-enabled Target Operating Model, value is no longer created solely through human execution, but also through the ability to effectively orchestrate intelligent agents. Companies that rethink their value chains around this logic gain efficiency, responsiveness and execution quality.

Governance and management of AI agents

The deployment of AI agents requires specific governance. This involves defining clear rules regarding their scope of action, the limits of their autonomy and supervision mechanisms. Governance must also address security, compliance and accountability issues. The Target Operating Model makes it possible to embed this governance within a clear structure by specifying the roles of IT teams, business units and leadership. AI agents can then be managed as full components of the organization, with performance indicators, control mechanisms and continuous improvement processes.

Impacts on roles and skills

The introduction of AI agents transforms the nature of work. Some tasks disappear, while new responsibilities emerge around supervision, orchestration and interpretation of AI-generated outputs. This evolution requires adaptation of skills and career paths. A well-designed Target Operating Model anticipates these changes. It identifies key roles, critical skills and upskilling needs. The objective is not to replace humans with machines, but to redeploy human capabilities toward higher value-added activities.

From operational performance to competitive advantage

When integrated into a coherent operating model, AI agents become a lever for sustainable performance. They reduce lead times, improve decision quality and enhance operational scalability. This performance does not rely solely on technology, but on the organization’s ability to use it effectively. Over time, companies that succeed in aligning AI agents with their Target Operating Model build a competitive advantage that is difficult to replicate. AI ceases to be an isolated project and becomes a strategic asset, deeply embedded in organizational processes and culture.

Toward augmented and manageable organizations

AI agents pave the way for more augmented organizations, capable of operating with a high level of automation while maintaining strong human governance. The Target Operating Model forms the foundation of this evolution by providing a clear, structured and manageable vision of the company’s future operations. In an uncertain and competitive economic environment, the ability to align technology, organization and strategy becomes decisive. When integrated into a well-defined Target Operating Model, AI agents are no longer merely optimization tools, but powerful drivers of deep and sustainable transformation.