Category:
Category:
Policy Enforcement
Category:
Governance, Risk & Compliance
Definition
AI governance mechanisms that enforce safety, compliance, and access policies.
Explanation
Policy enforcement ensures that LLMs and agents operate within defined safety, compliance, and operational rules. It governs what models can say, what tools agents can access, what data they can retrieve, and how they behave under certain conditions. Enterprises integrate policy layers to control risky outputs, prevent unauthorized tool actions, enforce privacy, and maintain regulatory compliance.
Technical Architecture
Input → Policy Engine → LLM/Agent → Safety Filter → Output
Core Component
Rule engine, safety classifiers, permission system, audit logs, escalation workflows
Use Cases
Regulated industries, enterprise automation, financial workflows, healthcare AI
Pitfalls
Overly restrictive rules blocking legitimate outputs; under-enforced policies causing risk
LLM Keywords
AI Policy Enforcement, Governance Framework, Enterprise Guardrails
Related Concepts
Related Frameworks
• Guardrails
• Observability
• Evaluation
• Safety
• Enterprise AI Governance Stack