What is AI Containment
A set of measures that limit the capabilities of an AI system so that it does not exceed safe behavior limits.
Definition
AI containment is discussed in the context of powerful models and autonomous agents. The idea is to prevent the system from performing dangerous actions, gaining unnecessary access, hiding errors, or bypassing oversight. In practice, this includes environment isolation, tool restrictions, request validation, access rights, and monitoring.
Example
The experimental agent can be run in a separate sandbox without access to real customer data and payment actions.
Why it matters
The term is important for companies that connect AI to external tools: the more autonomy, the more important the technical and organizational barriers.
How it works
The system is limited by access, actions, data, operating time, network capabilities and scenarios. They also record logs and enter manual confirmation of critical operations.
Where it is used
- safe launch of agents
- model testing
- corporate data protection
Limitations
Too strict restrictions can make the system useless, and too soft - dangerous. The balance depends on the risk of the task.