AI Policy for GRC Managers
GRC Managers are the operational backbone of AI governance, responsible for translating frameworks into tested controls and maintaining the evidence that proves compliance. As organizations adopt multiple AI governance standards simultaneously, the GRC function needs tooling that maps controls across frameworks and automates the testing lifecycle.
Primary Responsibilities
- Mapping AI systems to governance frameworks including NIST AI RMF, ISO 42001, and ISO 27001
- Conducting and documenting AI risk assessments with standardized scoring methodologies
- Managing the control testing schedule and ensuring AI-related controls are validated regularly
- Maintaining the compliance evidence library with current attestations and third-party audit reports
- Coordinating internal and external audit engagements for AI governance program assessments
- Tracking remediation plans for AI governance gaps and reporting progress to leadership
Questions Auditors Will Ask
- Which governance frameworks have been adopted for AI systems, and how is mapping maintained?
- How frequently are AI-related controls tested, and what methodology is used?
- Can you produce the complete evidence package for your most recent AI governance audit?
- What is the average time to remediate AI governance gaps once identified?
- How do you ensure framework mapping stays current as standards are updated?
How PolicyGuard Helps
- Multi-framework mapping engine that links AI controls to NIST AI RMF, ISO 42001, and SOC 2 simultaneously
- Automated control testing scheduler with evidence collection and pass/fail tracking
- Remediation tracker with owner assignment, due dates, and leadership escalation rules
PolicyGuard automates multi-framework mapping, control testing schedules, and evidence collection for GRC teams. Reduce manual effort and close governance gaps faster.
