Shadow AI is expanding attack surfaces in most organizations, with the majority of employees using unapproved AI tools. A practical framework for governing AI in cloud environments covers four main areas: discovery (using CASBs, service mesh telemetry, and API gateway logs to inventory AI usage), data classification at creation (using AWS Macie, Amazon Comprehend, and tagging schemas to label data immediately), IAM-based enforcement (deny-by-default S3 bucket policies tied to classification tags), and policy-as-code with Open Policy Agent (OPA) for complex contextual rules. Additional operational controls include model registries backed by Kubernetes CRDs, risk-based approval workflows, and integrating governance metrics into existing observability stacks like Prometheus. The goal is making the secure path the path of least resistance for developers.
