What are AI Guardrails?
AI guardrails are control mechanisms that constrain AI model behavior to ensure safety, quality, and regulatory compliance. They act as "guardrails" — not blocking AI, but keeping it within safe boundaries.
Types of guardrails
Input guardrails — filtering and validating queries before sending to the model (blocking prompt injection, removing PII). Output guardrails — verifying model responses before delivery to users (format validation, hallucination checking, content filters). Process guardrails — permission limits, token budgets, human escalation on low confidence.
Enterprise requirements
In corporate environments, guardrails must include: policy compliance validation, confidential information protection, auditability (every guardrail decision must be logged), per-department/role configurability, and integration with existing security systems (SIEM, DLP).