Guardrails
Guardrails are technical and process constraints that keep AI usage safe, compliant, and aligned with business intent.
What it is
Guardrails include policy checks, access controls, output validation, logging, and approval gates around AI-assisted workflows.
Why it matters for delivery teams
They lower risk in production use: less data leakage, fewer unsafe outputs, and clearer accountability for decisions.
Common mistake
Adding guardrails only at the UI layer. Effective control needs defense in depth across prompts, runtime, storage, and observability.
Practical next step
Define minimum controls for one workflow: data classification, approval step, and audit logging. Then enforce them in CI/CD and runtime checks.