AI creates a new cloud security surface

AI applications can introduce a combination of data flows, model endpoints, external services and automated actions. A secure AI architecture therefore needs more than model-level controls.

Protect the data path

Teams should understand what information enters a model, where it is stored, who can access it and how long it is retained.

Identity becomes even more important

AI services and agents should receive only the permissions required for their tasks, with strong authentication and auditable access.

Monitor the whole workflow

Monitoring needs to cover both the application and the model workflow. Unusual requests, unexpected data movement and abnormal agent behaviour can all become security signals.

Start with proven fundamentals

Identity, network controls, encryption, logging, vulnerability management and governance remain the foundation. AI adds new layers to protect; it does not remove the need for the basics.