Set up AI governance
Govern your generative AI usage to capture the benefits without the legal and operational risks.
Try for freeAI governance refers to the set of rules, processes and responsibilities that shape how an organization develops or uses artificial intelligence systems. It is not limited to large companies training their own models: any organization using a conversational assistant, a content generation tool or a recommendation system is concerned.
Without governance, AI usage multiplies informally across teams, escaping any control over shared data, the reliability of outputs produced, or regulatory compliance, notably regarding the European AI Act.
Map usage before governing it
The first step is not regulatory but factual: inventory every AI usage already in place across the organization, including those spontaneously adopted by teams outside any official project. A framework that ignores this informal usage leaves the biggest risk unaddressed.
Classify each usage by risk level
The European AI Act distinguishes four risk levels: unacceptable, high, limited and minimal. An automated recruitment system does not call for the same obligations as a customer support chatbot. Documenting this classification for every usage avoids over-governing simple cases and under-governing sensitive ones.
- Precise purpose of the usage and data processed
- Risk level under the AI Act
- Effective human oversight of automated decisions
- Transparency toward end users
Measure maturity to prioritize action
An AI maturity diagnostic structures this work around governance, data engineering and usage security, to objectively identify the domains furthest behind rather than tackling every topic at once with no clear priority.
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Frequently asked questions
Does AI governance concern small businesses?
Yes. As soon as a company uses a generative AI tool, even through a third-party service, it is subject to the AI Act's transparency and risk management requirements, regardless of its size.
Do you need a dedicated role to run AI governance?
Not necessarily at first. Ownership can sit with IT or legal, with a documented framework, before considering a dedicated role if usage grows.
What is the difference between AI governance and AI Act compliance?
AI Act compliance is a legal subset of AI governance, which more broadly covers data quality, output reliability and aligning usage with company strategy.
How should the first AI governance efforts be prioritized?
By starting with mapping high-risk usage under the AI Act, then prioritizing anything touching decisions with a direct impact on people (recruitment, credit, access to a service).
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