From Technological Experimentation to Organisational Transformation
The emergence of artificial intelligence agents marks a profound shift in the way organisations conceive and execute their activities. Unlike traditional digital tools, AI agents are not limited to automating isolated tasks. They are capable of interacting with systems, processing complex information, making conditional decisions and acting autonomously or semi-autonomously within a defined framework.
This evolution shifts the question of AI from the purely technological field to that of the operating model. The challenge is no longer simply to deploy AI solutions, but to rethink the way the organisation functions, decides and creates value. It is in this context that the notion of the Target Operating Model becomes central.
AI Agents as New Actors within the Organisation
AI agents can be envisaged as new actors within the organisation. They work 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 changes the organisational balance. It raises questions about the distribution of roles between humans and systems, the nature of responsibilities and the modes of coordination. Without a clear framework, the risk is of multiplying 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 organisation will function, fully integrating AI and automation. It defines how processes, roles, tools, governance and competencies are articulated to achieve strategic objectives. In the context of AI agents, the Target Operating Model becomes a tool for clarification. It enables organisations to answer structuring questions: which processes are partially or fully managed by AI agents, which decisions remain the responsibility of human teams, how interactions are organised and how performance is managed. This framework prevents a fragmented adoption of AI and situates agents within an 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 does not simply consist of accelerating what already exists, but of rethinking work sequences, control points and responsibilities. In a Target Operating Model integrating AI, value is no longer created solely through human execution, but also through the ability to orchestrate intelligent agents effectively. Companies capable of rethinking their value chains around this logic gain in efficiency, responsiveness and quality of execution.
Governance and Management of AI Agents
The deployment of AI agents requires specific governance. This means defining clear rules regarding their scope of action, the limits of their autonomy and supervision mechanisms. Governance must also address issues of security, compliance and accountability. The Target Operating Model enables this governance to be embedded in a readable structure, by specifying the roles of IT, business and management teams. It becomes possible to manage AI agents as full components of the organisation, with performance indicators, control mechanisms and continuous improvement processes.
Impact on Roles and Competencies
The introduction of AI agents transforms the nature of work. Teams see certain tasks disappear, while new responsibilities emerge around the management, supervision and interpretation of results produced by AI. This evolution requires an adaptation of skills and career paths. A well-designed Target Operating Model anticipates these transformations. It identifies key roles, critical competencies and upskilling needs. The objective is not to replace humans with machines, but to redeploy human capabilities towards higher added-value 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 strengthen the scalability of operations. This performance is not based solely on technology, but on the organisation's ability to leverage it effectively. Ultimately, companies that succeed in aligning AI agents with their Target Operating Model gain a competitive advantage that is difficult to replicate. AI ceases to be an isolated project and becomes a strategic asset, deeply embedded in the organisation's ways of working and culture.
Towards Augmented and Manageable Organisations
AI agents pave the way for more augmented organisations, capable of operating with a high level of automation while maintaining strong human governance. The Target Operating Model forms the foundation of this evolution, providing a clear, structured and manageable vision of the company's future operations. In an uncertain and competitive economic environment, the ability to articulate technology, organisation and strategy becomes decisive. AI agents, when integrated into a well-mastered Target Operating Model, are no longer simply an optimisation tool, but a driver of profound and lasting transformation.