AI Governance Improvement Center

Define approved AI usage boundaries, review responsibilities, and escalation criteria for high-risk use cases.

Enforce MFA and role-based access for all AI administration and integration pathways.

Implement data handling controls for prompts and generated output aligned with data sensitivity.

Set mandatory human validation steps for high-impact AI decisions and external-facing responses.

Introduce layered controls to detect, block, and log prompt injection attempts in critical workflows.

Aggregate AI interaction logs and policy events into a unified monitoring and alerting pipeline.

Introduce pre-deployment model risk assessment and approval criteria for model updates.

Maintain a living risk register for model providers and AI tool vendors with review cadence.

Automate evidence collection and control mapping for AI governance and security frameworks.

Define detection, containment, and escalation playbooks for AI-specific incident scenarios.

Add AI-specific risk scoring and treatment workflows into enterprise risk governance.

Establish recurring KPI tracking for security, governance, and operational AI performance.