AI Governance Module
Integrated AI risk and governance controls — managed alongside broader cybersecurity assurance, not in a separate silo.
The AI Governance Challenge
Organisations deploying or procuring AI systems face a rapidly evolving regulatory landscape. The EU AI Act, ISO/IEC 42001, and the NIST AI Risk Management Framework each impose distinct governance expectations — yet most organisations lack a structured mechanism to manage AI risk alongside their broader cybersecurity and compliance obligations.
C-PAP addresses this by integrating AI governance directly into the Canonical Control Model, enabling organisations to assess, evidence, and report on AI risk within the same assurance framework used for IT and OT compliance.
Framework Alignment
C-PAP's AI governance controls are mapped to all three frameworks, enabling organisations to demonstrate compliance across multiple AI governance obligations from a single set of controls and evidence.
EU AI Act Readiness
The EU AI Act introduces a risk-based classification system for AI systems, with obligations escalating by risk tier. C-PAP supports AI system classification and provides structured governance controls aligned to each tier.
Unacceptable
Prohibited AI practices — social scoring, real-time biometric identification (with exceptions).
High Risk
Conformity assessments, risk management, data governance, transparency, human oversight.
Limited Risk
Transparency obligations — users must be informed they are interacting with AI.
Minimal Risk
Voluntary codes of conduct. No mandatory requirements beyond existing obligations.
AI Governance Controls within the CCM
The CCM provides dedicated AI governance controls that extend the mandatory baseline. These controls address the specific requirements of AI risk management that sit outside traditional cybersecurity governance:
- AI system inventory and classification
- Algorithmic impact assessments
- Model governance and lifecycle management
- Training data governance and bias management
- Transparency and explainability requirements
- Human oversight and intervention mechanisms
- AI incident reporting and monitoring
Integration with Broader Assurance
AI governance does not exist in isolation. AI systems rely on the same infrastructure, data, and access controls as any other technology system. C-PAP ensures that AI-specific controls are assessed alongside and integrated with the broader CCM:
- D01 (Governance): AI governance policy and accountability structures
- D02 (Risk): AI-specific risk assessment and treatment within the enterprise risk framework
- D05 (Data Protection): Training data governance, privacy, and classification
- D12 (Supply Chain): Third-party AI model and service assurance
This integration ensures that AI governance is not a bolt-on exercise but a natural extension of the organisation's existing assurance programme.
AI Risk Assessment Methodology
C-PAP provides a structured methodology for assessing AI risk that aligns to both ISO/IEC 42001 and the NIST AI RMF. This includes identification of AI systems within the organisation's technology estate, classification by risk tier, assessment of governance controls against defined maturity criteria, and ongoing monitoring of AI-specific risk indicators.
The methodology is designed to be practical and proportionate — recognising that the governance requirements for a customer-facing recommendation engine differ substantially from those for a safety-critical autonomous system.
AI-Enabled Platform Capabilities
Beyond AI governance controls, C-PAP integrates AI tooling to enhance the platform's analytical, reporting, and monitoring capabilities. These capabilities are deployed across three maturity tiers, with human oversight embedded at every stage.
Tier 1 — Core Intelligence
AI-driven capabilities available across all platform modules:
- Gap Analysis: Automated identification of control gaps, coverage shortfalls, and evidence deficiencies across the CCM
- Natural Language Querying: Query the control model, assessment data, and framework mappings using natural language rather than structured filters
- Evidence Triage: AI-assisted classification, relevance scoring, and routing of evidence artefacts to the appropriate controls and assessments
Tier 2 — Analytical Depth
Advanced capabilities with human-in-the-loop validation:
- Regulatory Change Monitoring: Continuous monitoring of regulatory and framework updates with automated impact analysis against the organisation's control posture
- AI-Generated Assessment Reports: Automated generation of assessment reports, executive summaries, and board-level briefings from assessment data — all subject to human review and approval before issue
Tier 3 — Strategic Insight
Capabilities that provide forward-looking strategic intelligence:
- Threat-Informed Prioritisation: Integration with MITRE ATT&CK and D3FEND to prioritise control remediation based on active threat landscape and sector-specific threat intelligence
- Maturity Trend Analysis: Longitudinal analysis of maturity scoring across assessment cycles, identifying trajectory patterns, regression risks, and areas requiring intervention
Govern AI with Confidence
See how C-PAP integrates AI governance into your existing assurance programme.