AI Governance, Risk and Compliance (GRC) Assessment

Executive Summary

This document provides a comprehensive assessment framework for evaluating an organization’s compliance with AI Governance, Risk and Compliance (GRC) requirements. Based on ISO 42001, CIS Controls, and NIST Cybersecurity Framework (CSF), this assessment helps organizations identify gaps in their AI governance practices and develop remediation plans.

The assessment is organized into seven domains covering the full spectrum of AI security and literacy:

1. AI Governance and Risk Management
2. AI Data Governance and Privacy
3. AI Model Development and Security
4. AI Operations and Deployment
5. AI Incident Response and Recovery
6. AI Transparency and Explainability
7. AI Literacy and Training

Each domain contains assessment questions with corresponding control references, compliance criteria, and remediation recommendations. This matrix-style assessment allows organizations to clearly identify controls that are compliant versus those out of compliance.

How to Use This Assessment

1. Assessment Preparation: Gather relevant documentation, including AI policies, procedures, risk assessments, and training materials.

2. Compliance Evaluation: For each question, determine the compliance status (Compliant, Partially Compliant, Non-Compliant, or Not Applicable) and document supporting evidence.

3. Gap Analysis: For items that are not fully compliant, document the specific gaps and assign a priority level (High, Medium, Low).

4. Remediation Planning: Use the provided remediation recommendations to develop an implementation plan with timelines and responsible parties.

5. Progress Tracking: Regularly update the assessment to track remediation progress and overall compliance improvement.

AI Governance vs. Cybersecurity GRC

It’s important to note that AI Governance differs from traditional Cybersecurity GRC in several key ways:

• AI Governance focuses primarily on input/output data and associated outcomes
• Traditional Cybersecurity GRC operates within a total enterprise risk methodology
• AI security requires specialized roles like the Chief AI Security Officer (CAISO) and AI Governance Certifier (AIGC)
• AI Security Operations Centers (AiSOCs) have unique requirements compared to traditional SOCs

This assessment framework accounts for these differences by incorporating AI-specific controls and considerations throughout all domains.

Domain 1: AI Governance and Risk Management

Overview

This domain assesses the organization’s AI governance structure, policies, risk management processes, and oversight mechanisms. Effective AI governance is the foundation for responsible AI deployment and use within an organization.

Assessment Questions

Question 1: Does the organization have a documented AI governance policy that aligns with ISO 42001?

Control Reference: ISO 42001 Section 5.2 (AI Policy)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement an AI governance policy that establishes principles, roles, and responsibilities for AI systems management, aligned with ISO 42001 requirements | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 2: Has the organization established a formal AI risk assessment methodology?

Control Reference: NIST AI RMF (MAP function), ISO 42001 Section 6.1

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement a structured AI risk assessment methodology based on NIST AI RMF MAP function, including context analysis, risk identification, and impact assessment | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 3: Are AI governance roles and responsibilities clearly defined, including CAISO and AIGC roles?

Control Reference: ISO 42001 Section 5.3, NIST CSF 2.0 (GOVERN function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Define and document AI governance roles and responsibilities, establish CAISO and AIGC positions with appropriate authority and resources | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 4: Does the organization maintain an inventory of all AI systems and their risk classifications?

Control Reference: CIS Control 1, NIST AI RMF (MAP function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Create and maintain a comprehensive inventory of all AI systems with appropriate risk classifications based on potential impact | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 5: Is there a process for regular review and approval of AI systems before deployment?

Control Reference: ISO 42001 Section 8.1, NIST AI RMF (MEASURE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish a formal AI system review and approval process that includes security, ethics, and compliance assessments before deployment | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 6: Does the organization have metrics to measure the effectiveness of AI governance controls?

Control Reference: ISO 42001 Section 9.1, NIST CSF 2.0 (GOVERN function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement metrics to measure AI governance effectiveness, with regular reporting to leadership | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Domain Summary

Overall Compliance Status: - Total Questions: 6 - Compliant: 0 - Partially Compliant: 0 - Non-Compliant: 0 - Not Applicable: 0 - Not Assessed: 6

Priority Distribution: - High Priority Findings: 0 - Medium Priority Findings: 0 - Low Priority Findings: 0

Remediation Timeline: - Immediate Actions (0-30 days): 0 - Short-term Actions (1-3 months): 0 - Long-term Actions (3+ months): 0

Additional Considerations for AI Governance

1. AI Security Operations Center (AiSOC): Consider establishing an AiSOC with defined position descriptions, training requirements, incident response plans, and disaster recovery procedures.

2. AI vs. Cybersecurity GRC: Note that AI Governance focuses primarily on input/output data and associated outcomes, while traditional Cybersecurity GRC operates within a total enterprise risk methodology.

3. Reference Frameworks: Ensure alignment with OWASP AI Exchange, MIT Risk Matrix, and NIST standards when developing your AI governance framework.

Domain 2: AI Data Governance and Privacy

Overview

This domain assesses the organization’s practices for managing data used in AI systems, including data quality, privacy protections, bias mitigation, and data lineage tracking. Effective data governance is essential for developing trustworthy and compliant AI systems.

Assessment Questions

Question 1: Does the organization have a documented data governance framework specific to AI training and operational data?

Control Reference: ISO 42001 Section 7.5, NIST AI RMF (MAP function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement an AI-specific data governance framework that addresses data quality, privacy, and security throughout the AI lifecycle | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 2: Are there processes to assess and mitigate bias in AI training data?

Control Reference: NIST AI RMF (MEASURE function), ISO 42001 Section 8.2

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement formal processes for bias assessment in training data, including diverse data sampling, statistical analysis, and regular bias audits | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 3: Does the organization maintain data lineage and provenance tracking for AI systems?

Control Reference: CIS Control 3, NIST AI RMF (MAP function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish data lineage and provenance tracking systems that document the origin, transformations, and usage of all AI-related data | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 4: Are there data protection controls specific to AI training datasets and model outputs?

Control Reference: CIS Control 3, ISO 42001 Section 8.3

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement enhanced data protection controls for AI datasets, including encryption, access controls, and data minimization techniques | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 5: Does the organization have a data retention and disposal policy for AI training data?

Control Reference: CIS Control 3, NIST CSF 2.0 (PROTECT function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement a data retention and disposal policy specific to AI training data that complies with relevant regulations and minimizes risk | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 6: Is there a process for regular data quality assessment for AI systems?

Control Reference: ISO 42001 Section 9.1, NIST AI RMF (MEASURE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish formal data quality assessment processes for AI systems, including completeness, accuracy, and relevance checks | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Domain Summary

Overall Compliance Status: - Total Questions: 6 - Compliant: 0 - Partially Compliant: 0 - Non-Compliant: 0 - Not Applicable: 0 - Not Assessed: 6

Priority Distribution: - High Priority Findings: 0 - Medium Priority Findings: 0 - Low Priority Findings: 0

Remediation Timeline: - Immediate Actions (0-30 days): 0 - Short-term Actions (1-3 months): 0 - Long-term Actions (3+ months): 0

Additional Considerations for AI Data Governance

1. Input/Output Focus: Remember that AI Governance focuses primarily on input/output data and associated outcomes, making data governance a critical component of your overall AI GRC strategy.

2. Privacy by Design: Implement privacy by design principles in your AI data governance framework to ensure compliance with relevant privacy regulations.

3. Data Ethics Committee: Consider establishing a data ethics committee to review and approve the use of sensitive or potentially biased datasets in AI training.

Domain 3: AI Model Development and Security

Overview

This domain assesses the organization’s practices for secure AI model development, documentation, testing, and supply chain management. Implementing security throughout the AI model lifecycle is essential for developing robust and trustworthy AI systems.

Assessment Questions

Question 1: Does the organization follow a secure AI model development lifecycle?

Control Reference: ISO 42001 Section 8.1, NIST AI RMF (MANAGE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement a secure AI model development lifecycle that includes security requirements, threat modeling, and security testing at each phase | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 2: Is there comprehensive documentation for all AI models, including version control?

Control Reference: ISO 42001 Section 7.5, CIS Control 2

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish standardized documentation practices for AI models, including architecture, parameters, training methods, and version control | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 3: Are AI models tested for security vulnerabilities before deployment?

Control Reference: CIS Control 16, NIST CSF 2.0 (PROTECT function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement comprehensive security testing for AI models, including adversarial testing, input validation, and output filtering | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 4: Does the organization assess and manage supply chain risks for AI components?

Control Reference: CIS Control 15, NIST CSF 2.0 (IDENTIFY function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement a supply chain risk management program for AI components, including vendor assessment and component verification | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 5: Are there processes for secure model updates and versioning?

Control Reference: CIS Control 7, ISO 42001 Section 8.1

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish formal processes for secure model updates, including testing, approval, and rollback capabilities | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 6: Does the organization perform regular security assessments of third-party AI models?

Control Reference: CIS Control 15, NIST AI RMF (MEASURE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement a program for regular security assessments of third-party AI models, including documentation review, testing, and compliance verification | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Domain Summary

Overall Compliance Status: - Total Questions: 6 - Compliant: 0 - Partially Compliant: 0 - Non-Compliant: 0 - Not Applicable: 0 - Not Assessed: 6

Priority Distribution: - High Priority Findings: 0 - Medium Priority Findings: 0 - Low Priority Findings: 0

Remediation Timeline: - Immediate Actions (0-30 days): 0 - Short-term Actions (1-3 months): 0 - Long-term Actions (3+ months): 0

Additional Considerations for AI Model Development

1. OWASP AI Security References: Leverage the OWASP AI Exchange for guidance on secure AI development practices and common vulnerabilities.

2. Model Security Testing: Consider implementing specialized security testing for AI models, including adversarial testing, robustness testing, and privacy analysis.

3. Secure Model Registry: Establish a secure model registry to maintain version control, access management, and deployment tracking for all AI models.

Domain 4: AI Operations and Deployment

Overview

This domain assesses the organization’s practices for secure deployment, monitoring, access control, and configuration management of AI systems in production environments. Operational security is critical for maintaining the integrity and reliability of AI systems throughout their lifecycle.

Assessment Questions

Question 1: Does the organization implement secure deployment practices for AI systems?

Control Reference: CIS Control 4, NIST CSF 2.0 (PROTECT function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement secure deployment procedures for AI systems, including configuration management, environment separation, and deployment verification | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 2: Is there continuous monitoring of AI systems in production for security anomalies?

Control Reference: CIS Control 13, NIST AI RMF (MEASURE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement continuous monitoring solutions for AI systems that detect security anomalies, unexpected behaviors, and performance issues | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 3: Are there robust access controls and authentication mechanisms for AI systems?

Control Reference: CIS Control 6, ISO 42001 Section 8.3

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish strong access controls for AI systems, including multi-factor authentication, role-based access, and privilege management | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 4: Does the organization maintain comprehensive logs of AI system operations and access?

Control Reference: CIS Control 8, NIST CSF 2.0 (DETECT function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement comprehensive logging for AI systems, including system operations, access attempts, and administrative actions | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 5: Are there processes to detect and address model drift or performance degradation?

Control Reference: ISO 42001 Section 9.1, NIST AI RMF (MEASURE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish processes to detect and address model drift, including performance monitoring, statistical analysis, and remediation procedures | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 6: Does the organization have secure configuration standards for AI infrastructure?

Control Reference: CIS Control 4, NIST CSF 2.0 (PROTECT function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement secure configuration standards for AI infrastructure, including servers, networks, and cloud environments | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Domain Summary

Overall Compliance Status: - Total Questions: 6 - Compliant: 0 - Partially Compliant: 0 - Non-Compliant: 0 - Not Applicable: 0 - Not Assessed: 6

Priority Distribution: - High Priority Findings: 0 - Medium Priority Findings: 0 - Low Priority Findings: 0

Remediation Timeline: - Immediate Actions (0-30 days): 0 - Short-term Actions (1-3 months): 0 - Long-term Actions (3+ months): 0

Additional Considerations for AI Operations

1. AI Security Operations Center (AiSOC): Consider implementing an AiSOC with specialized monitoring capabilities for AI systems, including model behavior monitoring and anomaly detection.

2. Automated Guardrails: Implement automated guardrails and circuit breakers that can detect and respond to abnormal AI system behavior in real-time.

3. Operational Metrics: Establish key operational metrics specific to AI systems, such as prediction accuracy, data drift, and resource utilization.

Domain 5: AI Incident Response and Recovery

Overview

This domain assesses the organization’s capabilities for responding to and recovering from AI-related incidents, including system failures, security breaches, and ethical issues. Effective incident response is essential for minimizing the impact of AI incidents and ensuring business continuity.

Assessment Questions

Question 1: Does the organization have AI-specific incident response procedures?

Control Reference: CIS Control 17, NIST CSF 2.0 (RESPOND function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement AI-specific incident response procedures that address unique AI failure modes, security incidents, and ethical breaches | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 2: Are there capabilities to roll back AI systems to previous versions in case of incidents?

Control Reference: CIS Control 11, NIST CSF 2.0 (RECOVER function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement and test AI system rollback capabilities, including version control, configuration backups, and deployment automation | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 3: Does the organization maintain backups of AI models, training data, and configurations?

Control Reference: CIS Control 11, ISO 42001 Section 7.5

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish comprehensive backup procedures for AI assets, including models, training data, and configurations, with regular testing of restoration processes | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 4: Is there a business continuity plan that addresses AI system failures?

Control Reference: NIST CSF 2.0 (RECOVER function), ISO 42001 Section 6.1

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and test a business continuity plan that addresses AI system failures, including alternative processes and recovery time objectives | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 5: Does the organization conduct post-incident analysis for AI-related incidents?

Control Reference: CIS Control 17, NIST AI RMF (MANAGE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement post-incident analysis processes for AI-related incidents, including root cause analysis, impact assessment, and improvement recommendations | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 6: Are AI incident response team members trained on AI-specific incident scenarios?

Control Reference: CIS Control 17, NIST CSF 2.0 (RESPOND function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Provide specialized training for incident response team members on AI-specific incident scenarios, including technical, ethical, and reputational aspects | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Domain Summary

Overall Compliance Status: - Total Questions: 6 - Compliant: 0 - Partially Compliant: 0 - Non-Compliant: 0 - Not Applicable: 0 - Not Assessed: 6

Priority Distribution: - High Priority Findings: 0 - Medium Priority Findings: 0 - Low Priority Findings: 0

Remediation Timeline: - Immediate Actions (0-30 days): 0 - Short-term Actions (1-3 months): 0 - Long-term Actions (3+ months): 0

Additional Considerations for AI Incident Response

1. AI Security Operations Center (AiSOC): Consider integrating AI incident response capabilities into an AiSOC with specialized training and tools for AI-specific incidents.

2. Tabletop Exercises: Conduct regular tabletop exercises that simulate AI-specific incidents, such as model poisoning, adversarial attacks, or ethical breaches.

3. Cross-functional Response: Ensure incident response teams include representatives from AI development, legal, communications, and executive leadership to address the multifaceted nature of AI incidents.

Domain 6: AI Transparency and Explainability

Overview

This domain assesses the organization’s practices for ensuring transparency and explainability in AI systems, including documentation of decision processes, interpretability of model outputs, and communication of AI limitations to stakeholders. Transparency is essential for building trust and ensuring accountability in AI systems.

Assessment Questions

Question 1: Does the organization implement explainable AI methodologies for high-risk AI applications?

Control Reference: NIST AI RMF (MAP function), ISO 42001 Section 8.4

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement appropriate explainable AI methodologies based on use case requirements, including local and global explanation techniques | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 2: Is there documentation of AI decision processes for critical systems?

Control Reference: ISO 42001 Section 7.5, NIST AI RMF (MEASURE function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and maintain detailed documentation of AI decision processes, including model logic, key features, and decision boundaries | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 3: Are there mechanisms to ensure transparency in AI-human interactions?

Control Reference: NIST AI RMF (MANAGE function), ISO 42001 Section 8.4

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement transparency mechanisms for AI-human interactions, including disclosure of AI use, confidence levels, and limitations | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 4: Does the organization have methods to interpret and validate model outputs?

Control Reference: NIST AI RMF (MEASURE function), ISO 42001 Section 9.1

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish methods for interpreting and validating model outputs, including statistical analysis, human review, and comparison with expected outcomes | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 5: Is there clear communication to stakeholders about AI system limitations?

Control Reference: ISO 42001 Section 7.4, NIST AI RMF (GOVERN function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop clear communication materials about AI system limitations, including accuracy boundaries, known biases, and appropriate use cases | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 6: Are there processes to address algorithmic transparency requirements from regulations?

Control Reference: ISO 42001 Section 6.1, NIST CSF 2.0 (GOVERN function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish processes to identify and address algorithmic transparency requirements from applicable regulations, including documentation and reporting mechanisms | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Domain Summary

Overall Compliance Status: - Total Questions: 6 - Compliant: 0 - Partially Compliant: 0 - Non-Compliant: 0 - Not Applicable: 0 - Not Assessed: 6

Priority Distribution: - High Priority Findings: 0 - Medium Priority Findings: 0 - Low Priority Findings: 0

Remediation Timeline: - Immediate Actions (0-30 days): 0 - Short-term Actions (1-3 months): 0 - Long-term Actions (3+ months): 0

Additional Considerations for AI Transparency

1. Explainability Tools: Consider implementing specialized explainability tools and techniques appropriate for different AI models and use cases.

2. Transparency Documentation: Develop standardized transparency documentation templates that can be used across different AI systems.

3. Stakeholder Engagement: Establish processes for engaging with stakeholders to understand their transparency needs and expectations for AI systems.

Domain 7: AI Literacy and Training

Overview

This domain assesses the organization’s practices for developing AI literacy and providing appropriate training to staff at all levels. Effective AI literacy and training programs are essential for building a culture of responsible AI use and ensuring that personnel have the knowledge and skills needed to manage AI risks effectively.

Assessment Questions

Question 1: Does the organization have an AI awareness program for all employees?

Control Reference: CIS Control 14, NIST CSF 2.0 (GOVERN function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and implement an AI awareness program for all employees, covering AI capabilities, limitations, and responsible use | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 2: Is there specialized technical AI security training for relevant personnel?

Control Reference: CIS Control 14, ISO 42001 Section 7.2

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish specialized technical AI security training for IT, security, and development personnel, including threat modeling, secure development, and vulnerability management | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 3: Does the organization provide AI ethics training for staff involved in AI development and deployment?

Control Reference: ISO 42001 Section 7.3, NIST AI RMF (GOVERN function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement AI ethics training that covers fairness, accountability, transparency, and privacy considerations in AI systems | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 4: Is there training on AI risk management for leadership and risk management personnel?

Control Reference: ISO 42001 Section 7.2, NIST AI RMF (MAP function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Develop and deliver AI risk management training for leadership and risk personnel, covering AI-specific risks, assessment methodologies, and mitigation strategies | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 5: Does the organization have a continuous learning program for AI security and governance?

Control Reference: CIS Control 14, ISO 42001 Section 7.2

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Establish a continuous learning program for AI security and governance, including regular updates on emerging threats, regulatory changes, and best practices | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Question 6: Are there mechanisms to assess AI literacy and competency across the organization?

Control Reference: ISO 42001 Section 7.2, NIST CSF 2.0 (GOVERN function)

Compliance Matrix: | Compliance Status | Evidence | Gap Analysis | Priority | |——————-|———-|————–|———-| | ☐ Compliant
☐ Partially Compliant
☐ Non-Compliant
☐ Not Applicable | | | ☐ High
☐ Medium
☐ Low |

Remediation: | Remediation Recommendation | Implementation Timeline | Responsible Party | Resources Required | Status | |—————————-|————————-|——————-|——————-|——–| | Implement mechanisms to assess AI literacy and competency, including knowledge assessments, skills evaluations, and certification programs | ☐ Immediate (0-30 days)
☐ Short-term (1-3 months)
☐ Long-term (3+ months) | | | ☐ Not Started
☐ In Progress
☐ Completed
☐ Verified |

Domain Summary

Overall Compliance Status: - Total Questions: 6 - Compliant: 0 - Partially Compliant: 0 - Non-Compliant: 0 - Not Applicable: 0 - Not Assessed: 6

Priority Distribution: - High Priority Findings: 0 - Medium Priority Findings: 0 - Low Priority Findings: 0

Remediation Timeline: - Immediate Actions (0-30 days): 0 - Short-term Actions (1-3 months): 0 - Long-term Actions (3+ months): 0

Additional Considerations for AI Literacy

1. Role-Based Training: Develop role-based AI literacy and training programs tailored to different job functions and responsibilities.

2. Training for Specialized Roles: Provide specialized training for CAISO and AIGC roles to ensure they have the knowledge and skills needed to fulfill their responsibilities effectively.

3. External Resources: Leverage external resources, such as industry certifications, academic partnerships, and professional organizations, to enhance AI literacy and training programs.

AI GRC Assessment - Conclusion and Next Steps

Assessment Summary

This AI Governance, Risk and Compliance (GRC) Assessment provides a comprehensive framework for evaluating an organization’s compliance with key AI governance standards and best practices. The assessment covers seven critical domains:

1. AI Governance and Risk Management
2. AI Data Governance and Privacy
3. AI Model Development and Security
4. AI Operations and Deployment
5. AI Incident Response and Recovery
6. AI Transparency and Explainability
7. AI Literacy and Training

Across these domains, the assessment includes 42 questions with detailed compliance criteria and remediation recommendations, all mapped to ISO 42001, CIS Controls, and NIST frameworks.

How to Use the Assessment Results

The results of this assessment should be used to:

1. Identify Compliance Gaps: Determine areas where your organization’s AI governance practices do not meet industry standards or regulatory requirements.

2. Prioritize Remediation Efforts: Focus on high-priority findings first, particularly those related to critical AI systems or significant compliance gaps.

3. Develop an Implementation Roadmap: Create a timeline for implementing remediation actions, assigning responsibilities, and allocating necessary resources.

4. Monitor Progress: Regularly review and update the assessment to track progress toward full compliance.

5. Demonstrate Due Diligence: Use the completed assessment to demonstrate to stakeholders that your organization is taking a structured approach to AI governance.

Specialized AI Security Roles

This assessment recognizes the importance of specialized roles in AI governance and security:

• Chief AI Security Officer (CAISO): Executive responsible for AI security governance within the organization.

• AI Governance Certifier (AIGC): Specialized role responsible for certifying compliance with AI governance standards.

• AI Security Operations Center (AiSOC): Specialized security operations center focused on monitoring and protecting AI systems.

These roles should be integrated into your organization’s governance structure to ensure effective oversight of AI systems.

Continuous Improvement

AI governance is an evolving field, and this assessment should be viewed as part of a continuous improvement process. Organizations should:

1. Regularly update the assessment to reflect changes in AI technologies, regulatory requirements, and industry best practices.

2. Conduct the assessment at least annually or when significant changes occur in AI systems or governance structures.

3. Share lessons learned and best practices across the organization to foster a culture of responsible AI use.

4. Stay informed about emerging AI governance standards and frameworks to ensure ongoing compliance.

Additional Resources

For more information on AI governance and security, refer to the following resources:

• ISO/IEC 42001:2023 - AI management systems
• NIST AI Risk Management Framework (AI RMF)
• NIST Cybersecurity Framework (CSF) 2.0
• CIS Critical Security Controls
• OWASP AI Exchange
• MIT AI Risk Repository
• Cloud Security Alliance AI Control Framework