Policy-as-Code brings the rigor of software engineering to AI governance. Learn how to encode compliance requirements, automate policy enforcement, and create repeatable, auditable processes for your ML systems.

What is Policy-as-Code?

Policy-as-Code is the practice of defining and managing compliance, security, and operational policies as machine-readable code. This enables automation, version control, and testing of policies just like application code.

Benefits for AI

• Consistency: Policies are applied uniformly across all models and environments.
• Auditability: Every policy change is tracked and reviewable.
• Automation: Policies can be enforced automatically at deployment or runtime.

Getting Started

1. Define Policies Clearly: Start with business, legal, and regulatory requirements.
2. Choose a Framework: Use tools like Open Policy Agent (OPA) or custom rule engines.
3. Integrate with CI/CD: Enforce policies during model development, testing, and deployment.

By adopting Policy-as-Code, organizations can ensure their AI systems remain compliant, secure, and reliable.