Secure AI Deployment Checklist

Shipping AI into production is more than just exposing an endpoint. You need controls for access, monitoring, logging, data protection, and incident response—just like any other critical system.

• Access control and authentication around models and data.
• Rate limiting and abuse detection for prompt and API usage.
• Structured logging and monitoring for anomalous behavior.
• Data retention, encryption, and redaction policies.
• Documented incident response plan for AI‑related issues.

The AI Security pillar page shows how deployment fits alongside threat modeling, testing, and governance.