Définition
The AI management system answers the questions: who owns the model, what data can be used, how risks are checked, who approves the launch, how incidents are recorded and when the model should be stopped. This is a management layer on top of technology that is especially important for enterprise AI products.
Exemple
The bank implements AI to analyze applications and creates rules: what data is acceptable, who checks the model, how to store logs and how the client can challenge the decision.
Pourquoi c'est important
The term is important because without governance, even useful AI can become a source of legal, reputational and operational problems.
Fonctionnement
The framework includes roles, policies, risk assessment, documentation, auditing, monitoring, employee training and incident response procedures.
Où c'est utilisé
- corporate implementation of AI
- compliance
- risk management
Limites
Processes that are too heavy can slow down the product, and processes that are too light cannot protect against risks. We need an approach based on the level of system criticality.
FAQ
Why is “AI Governance Frameworks” useful to know?
The term is important because without governance, even useful AI can become a source of legal, reputational and operational problems.