AI Glossary
AI Controls
AI Controls are policies, procedures, safeguards, and technical measures that help reduce risks and ensure AI systems operate responsibly.
AI Controls
Overview
Organizations cannot eliminate every AI risk.
Instead, they implement safeguards that reduce the likelihood or impact of potential problems.
These safeguards are known as AI Controls.
AI Controls are policies, procedures, technical safeguards, and operational processes that help organizations deploy AI responsibly.
Examples include:
- Human oversight
- Access controls
- Model validation
- Security testing
- Documentation
- Approval workflows
- Continuous monitoring
A helpful way to think about AI controls is the safety equipment found in a modern vehicle.
Seatbelts.
Airbags.
Brakes.
Backup cameras.
None of these prevent every accident.
Instead, they reduce risk and improve safety.
Organizations use AI controls in much the same way.
AI controls are a critical component of AI Governance and AI Risk Management because they help reduce technical, operational, and compliance risks.
Why It Matters
Even well-designed AI systems can produce unexpected outcomes.
AI controls provide structured safeguards that improve security, reliability, transparency, and trust.
Real-World Example
Before deploying an AI chatbot, an organization performs security testing, requires executive approval, enables continuous monitoring, and documents model behavior.
Together, these activities form part of the organization’s AI control framework.
Related Concepts
Related Articles
- What Is AI Risk Management?
- AI Governance vs AI Risk Management
- Why AI Governance Matters As AI Adoption Grows