AI Governance & Policy Enforcement

Organizations are rapidly adopting AI, but boardrooms and compliance teams face a critical challenge: how to govern its use. Without automated guardrails, AI policies exist only on paper. True AI Governance requires real-time policy enforcement, clear asset tracking, and comprehensive audit trails.

The Pillars of AI Governance

Governing enterprise AI involves aligning corporate risk frameworks with actual employee behavior:

• Inventory Control: Documenting every AI tool currently accessed across the enterprise.
• Access Policies: Defining which roles can use which AI models (e.g. restricting access to code generation tools for non-engineering staff).
• Compliance Recording: Creating a permanent, tamper-resistant record of AI security enforcement to show to regulatory auditors.

How TryAIDR Enforces AI Governance

TryAIDR translates high-level corporate governance policies into automated, endpoint-level rules:

• Dynamic Rules Engine: Update policies instantly from the central dashboard. Push rules to thousands of endpoints in seconds.
• Cryptographic Audit Ledger: Every policy decision (block, allow, redact) is cryptographically signed and stored in a blockchain-style log file, providing auditors with a verifiable history of compliance.
• Vendor Risk Control: Control which specific model endpoints are authorized, blocking public APIs while facilitating access to self-hosted private models.

Sample Governance Policy Configuration

Below is a policy that restricts general employees from uploading files containing source code to public LLMs:

{
  "policy_name": "Source Code Governance",
  "scope": {
    "exempt_groups": ["Engineering-Admin"],
    "target_applications": ["ChatGPT", "Claude", "Gemini"]
  },
  "rules": [
    {
      "classifier": "code_detector",
      "action": "block"
    }
  ]
}

To kickstart your organization's governance plan, download our AI Security Policy Template for Enterprises.