Governance and compliance of AI agents :

Deploying an AI agent has become accessible. Deploying it in a compliant and secure environment is much more complex. In regulated sectors, the challenge is not technological. It is organizational, regulatory, and systemic.

Companies must now integrate:

• GDPR → data protection

• DORA → operational resilience

• AI Act → governance of AI systems

Systems must be controllable, auditable, and explainable.

An AI agent takes decisions, sequences actions, and interacts with systems. It introduces autonomy into the IS, and therefore new risks to control.

An agent must never be a black box. It must operate with:

• a defined scope of action

• explicit rules

• human supervision

• rights and access management

Governance becomes an architectural element.

In a regulated environment, every action must be traceable. This involves preserving: input data, instructions given to the agent, decisions made, and actions executed. Without traceability, no audit is possible.

Systems must allow for explaining decisions, identifying errors, and understanding behaviors. Explainability is indispensable for compliance, trust, and business validation.

Agents interact with critical systems. It is necessary to guarantee: authentication, fine-grained permissions management, logging of actions, and anomaly detection. Security must be integrated by design.

Agents must work with core systems, legacy systems, business tools, and APIs. The goal is to integrate with them in a controlled manner.

Moving to production requires clear governance, continuous monitoring, incident management, and full auditability. Without a framework, there is no scaling.

Deploying AI agents is not enough. They must be governed, traced, secured, and audited. Governance and compliance are the conditions for industrialization.