AI Model Governance

Definition

Managing AI models helps you stay in control of which model is running, what data it was trained on, who approved it, what risks are known, and when it needs to be updated. This is especially important when the company has many models, versions and teams.

Beispiel

After updating the support model, the team commits the version, compares metrics, checks security, and stores information about the reasons for the transition.

Warum es wichtig ist

The term is important for production AI: a model is not a one-time file, but a system that needs to be maintained.

So funktioniert es

Management includes model registries, documentation, versions, accesses, metrics, monitoring, auditing, responsible roles and change procedures.

Wo es genutzt wird

• MLOps
• corporate AI systems
• model version control

Einschränkungen

Without discipline, it's easy to launch the wrong version, lose reproducibility, or not notice the degradation in quality after data changes.

FAQ