AI Glossary
AI Control Framework
An AI Control Framework is a structured collection of policies, procedures, and safeguards used to reduce AI risks and support responsible AI governance.
AI Control Framework
Overview
Organizations rarely rely on a single AI control.
Instead, they implement multiple safeguards that work together to reduce risk.
This collection of safeguards is known as an AI Control Framework.
An AI Control Framework is a structured collection of policies, procedures, technical controls, and governance activities designed to manage AI risks and support responsible AI adoption.
An AI control framework may include:
- Human oversight
- Security controls
- Risk assessments
- Documentation
- Model validation
- Monitoring
- AI audits
- Governance approvals
A helpful way to think about an AI control framework is the security systems protecting a modern office building.
Locks.
Security cameras.
Alarm systems.
Access badges.
Each control serves a different purpose, but together they create a stronger overall security posture.
Organizations apply the same principle to AI governance.
Why It Matters
An AI control framework helps organizations manage AI consistently, reduce operational risk, improve accountability, and demonstrate responsible AI practices.
Real-World Example
A financial institution establishes a control framework requiring fairness testing, executive approval, security reviews, and continuous monitoring before every AI system enters production.
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