AI Security & Governance
AI Governance
Structure the responsible use of artificial intelligence across your organization
Why govern AI?
The rapid adoption of artificial intelligence exposes organizations to new risks: opaque decisions, bias, data leaks, regulatory non-compliance. Without a governance framework, these uses escape management's control.
AI governance provides the policies, roles and processes to oversee the lifecycle of each AI system, from design to decommissioning, aligning innovation with risk control.
Solid foundations:
Structured governance directly prepares your ISO/IEC 42001 and EU AI Act compliance, while integrating with your existing ISO 27001 ISMS.
The pillars of effective AI governance
AI Policy
Definition of a charter and principles for the responsible use of AI, approved by management.
Governance Committee
Establishment of a cross-functional body (business, legal, security, data) steering AI decisions.
System Inventory
Centralized mapping of all AI systems, internal and third-party, with their criticality level.
Roles & Responsibilities
Clear assignment of responsibilities for each AI system (owner, validator, controller).
Continuous Oversight
Monitoring of performance, drift and incidents throughout the model lifecycle.
Third-Party Management
Governance of external AI vendors and solutions through tailored contractual requirements.
Our support approach
Assessment
Evaluation of your AI maturity and identification of existing uses, including undeclared ones.
Governance Framework
Drafting of the AI policy, definition of the committee and decision processes.
Inventory & Classification
Identification of AI systems and qualification of their risk level.
Deployment
Implementation of processes, stakeholder training and tooling.
Continuous Improvement
Periodic review, steering indicators and adjustment of the framework.
Use cases
Regain control of your AI
Our experts support you in implementing AI governance tailored to your context and regulatory obligations.
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