AI Governance

Bridging the Gap: Cross Framework Mapping for AI Governance Controls

Mapping of controls across SOC-2, GDPR, and ISO-42001 can allow efficient implementation of AI governance requirements under the EU AI Act.

Rafae Bhatti

May 14, 2025 • 5 min read

Cross-Framework Mapping of Controls for AI Governance. [AI Generated] Source: ClaritasGRC

The EU AI Act outlines a set of technical controls based on the risk level of the organization. The challenge for most organizations is to know where to start when faced with these new control requirements introduced under the Act.

Instead of starting from scratch, the process can be made more efficient by leveraging the overlap between the controls that the organization may already have in place based on frameworks such as SOC-2 and GDPR and those required by the frameworks such as ISO-42001 to demonstrate compliance with the Act.

This post will analyze the common controls across these frameworks and provide an approximate coverage that reflects the extent of this overlap. This information can be helpful for organizations to plan their implementation efforts for AI governance.

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Our analysis provides an approximate coverage that reflects the extent of overlap between existing controls and AI governance requirements.

Cross-Framework Mapping

We begin with a high-level cross-framework mapping that compares controls in SOC-2* and GDPR with those in ISO-42001 aligned with the requirements of the EU AI Act.

*The analysis covers SOC-2 criteria CC & P, for Security & Privacy, respectively.

AI Governance Domain	EU AI Act Requirement	SOC 2 Alignment	GDPR Alignment	ISO/IEC 42001 Alignment
Risk Management	Art. 9 & 17 – Risk management system	CC3.2, CC9.2 – Risk assessment	Art. 24–25 – 35- DPIAs, risk mitigation	Clause 6.1–6.3 – Risk and opportunity identification
Data Governance	Art. 10 – Data quality, relevance, minimization	CC5.0-5.3, CC3.2, CC6.8, CC8.1 – Data handling controls	Art. 5 – Accuracy, data minimization	Clause 6.1, 6.2, 8.2, 8.4 – Data quality and lifecycle control
Transparency	Art. 13, 52 – AI system disclosures	CC2.2, 9.2 – Communication of changes, sub-processsors	Art. 12–15, 22 – Transparency obligations	Clause 5.2, 6.2.1, 6.3.1, 8.3, 8.4.4-5 – Explainability and transparency processes
Human Oversight	Art. 14 – Human in/on-the-loop controls	CC1.2, CC1.3, CC3.2, CC5.3 – Oversight roles	Art. 22(3), Recital 71 – Right to human intervention	Clause 5.2, 6.1.2, 6.2.1, 8.4.6, 8.5 – Oversight responsibilities and human control
Security & Resilience	Art. 15 – Robustness, cybersecurity	CC6.1-8, CC7.1-5 – Logical and physical security	Art. 32, Rectials 39, 83 – Security of processing	Clause 6.1.2, 8.2.2, 8.4.2, 8.4.8 – Security and resilience in AI operations
Logging & Traceability	Art. 12 – Automatic logs of system activity	CC6.6, CC7.2 – Audit logs	Art. 5(2), 30, 33-34 – Record of processing activities	Clause 6.1.2, 8.2.2, 8.4.7, 8.6, 9.1– Logging, monitoring, and post-deployment traceability
Data Subject Rights	Art. 5, 52, 68, 84 – Interaction, access, and explanation rights	P3.1-3.6, P4.1-2, P6.1-2 – User request handling	Art. 12–23 – Access, erasure, objection	Clause 5.2-3, 6.1.3, 6.2.2, 8.4.1, 8.4.4 – User communication and rights handling
Incident & Post-Market Monitoring	Art. 23, 61, 62, 67, 84 – Monitoring and reporting failures	CC3.2, CC7.2-5, CC9.2-4, P6.2 – Monitoring, remediation	Art. 24, 32-35 – Risk monitoring and breach notification	Clause 9.1, 10.2 – Incident tracking and continual improvement
Accountability & Roles	Art. 4, 16–29, 61 – Role of provider, deployer, importer, distributor	CC1.2-3, CC2.2, CC5.3 – Governance & accountability	Art. 5(2), 24-28, 30, 32, 35 – Controller and processor roles, Security measures, DPIA	Clause 5.1–5.3, 6.1.3, 8.4.1-5 – Leadership, responsibilities, accountability
Lifecycle Management	Art. 9–15, 61 – Technical documentation, updates	CC5.1-2, CC6.1-2, CC7.1, 8.1 – Change management	Art. 5(1), 25, 30, 35 – Documentation of processing, DPIA	Clause 6.1.3, 8.1, 8.4, 8.5.2 – AI lifecycle and documentation

Domain-Level Breakdown

We will now break this down further into individual domain-level controls. For each domain, we will provide a coverage score, which indicates the extent of overlap between existing controls and those required under the EU AI Act.

A coverage score of X would mean that an organization that has implemented SOC-2 and GDPR controls will have X% coverage for the corresponding controls required by ISO-42001 to demonstrate compliance with the EU AI Act.

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LEGEND (for tables): ✅ = Fully Supported, ✅✅ = Strong, AI-Specific Coverage, ⚠️ = Partially Supported, ❌ = Not Explicitly Covered

[A ✅ counts as 1, ⚠️ as 0.5, and ❌ as 0 toward the coverage score.]

Risk Management

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Formal Risk Management Process	✅	✅	✅	✅✅
Lifecycle Risk Monitoring	✅	⚠️	⚠️	✅✅
AI-Specific Risk Criteria	✅	❌	⚠️	✅✅
Accountability Framework	✅	✅	✅	✅✅
Post-Deployment Risk Updates	✅	⚠️	❌	✅✅

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Coverage score: 60%

Data Governance

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Data Accuracy & Completeness	✅	✅	✅	✅✅
Data Documentation & Traceability	✅	⚠️	⚠️	✅✅
Bias/Fairness Mitigation	✅	❌	⚠️	✅✅
AI-Specific Dataset Governance	✅	❌	❌	✅✅
Lifecycle Integration	✅	⚠️	❌	✅✅

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Coverage score: 40%

Transparency

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
User-Facing Transparency	✅	⚠️	✅	✅✅
Model Explainability	✅	❌	⚠️	✅✅
System Documentation	✅	✅	⚠️	✅✅
AI Interaction Disclosure	✅	❌	⚠️	✅✅
Communication of Limitations	✅	❌	❌	✅✅

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Coverage score: 40%

Human Oversight

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Human-in-the-loop Oversight	✅	⚠️	✅	✅✅
Right to Manual Override	✅	❌	✅	✅✅
Documentation of Oversight	✅	⚠️	⚠️	✅✅
Risk-Based Oversight Implementation	✅	⚠️	❌	✅✅
Operational Mechanisms for Intervention	✅	❌	⚠️	✅✅

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Coverage score: 45%

Security & Resilience

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
System Security	✅	✅	✅	✅✅
Threat Detection & Monitoring	✅	✅	⚠️	✅✅
Adversarial Attack Mitigation	✅	❌	❌	✅✅
System Resilience & Fault Tolerance	✅	✅	⚠️	✅✅
AI-Specific Risk Modeling & Controls	✅	❌	❌	✅✅

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Coverage score: 50%

Logging & Traceability

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Logging of Operations	✅	✅	⚠️	✅✅
Auditability of AI Decisions	✅	⚠️	❌	✅✅
Model Lifecycle Traceability	✅	❌	❌	✅✅
Logging for Compliance Demonstration	✅	✅	✅	✅✅
Incident & Breach Logging	✅	✅	✅	✅✅

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Coverage score: 60%

Data Subject Rights

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Right to Access / Correction	✅	✅	✅	✅✅
Right to Deletion / Objection	✅	✅	✅	✅✅
Transparent AI Decision Use	✅	⚠️	⚠️	✅✅
Human Override / Avoid Automation	✅	⚠️	✅	✅✅
Redress / Complaint Mechanisms	✅	✅	✅	✅✅

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Coverage score: 85%

Incident & Post-Market Monitoring

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Continuous Monitoring Post-Deployment	✅	⚠️	⚠️	✅✅
Incident Detection and Logging	✅	✅	✅	✅✅
Regulatory / Authority Reporting	✅	❌	⚠️	✅✅
Trend & Root Cause Analysis	✅	✅	✅	✅✅
Process Improvement Based on Incidents	✅	✅	✅	✅✅

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Coverage score: 75%

Accountability & Roles

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Role-Based Obligations	✅	✅	✅	✅✅
Defined Responsibilities for Compliance	✅	✅	✅	✅✅
Assignment of Internal Oversight	✅	✅	✅	✅✅
Contractual / Legal Accountability	✅	⚠️	✅	✅✅
Continuous Responsibility in Lifecycle	✅	⚠️	⚠️	✅✅

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Coverage score: 85%

Lifecycle Management

Capability	EU AI Act	SOC 2	GDPR	ISO/IEC 42001
Full AI Lifecycle Coverage	✅	⚠️	⚠️	✅✅
Design/Development Risk Controls	✅	✅	✅	✅✅
Post-Deployment Feedback Integration	✅	✅	✅	✅✅
Change Management During Lifecycle	✅	✅	✅	✅✅
Formal Decommissioning Guidance	⚠️	❌	❌	✅✅

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Coverage score: 70%

Key Observations

Based on the above cross-framework mapping and domain-level breakdown, its helpful to note the following observations:

Out of the 10 categories, the coverage based on existing controls ranges from high (> 75% ) for 2 of them, to medium (50-75%) for 5 of them, and to low (< 50%) for 3 of them.
SOC 2 contributes strong operational controls, —but lacks AI-specific provisions like bias mitigation or human oversight.
GDPR aligns closely with the data governance and individual rights aspects of the EU AI Act.
ISO/IEC 42001 is the most AI-specific standard, directly supporting structured implementation of EU AI Act requirements across the entire lifecycle, from design to monitoring.

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The coverage for categories ranges from high (> 75% ) for 2 of them, to medium (50-75%) for 5 of them, and to low (< 50%) for 3 of them.

Conclusion

This post analyzed the common controls across SOC-2, GDPR, and ISO-42001 aligned with the EU AI Act, and provided a coverage score for the various control categories to indicate the extent of overlap between them. This information can be helpful for organizations to plan their implementation efforts for AI governance.

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Bridging the Gap: Cross Framework Mapping for AI Governance Controls

Rafae Bhatti

Cross-Framework Mapping

Domain-Level Breakdown

Key Observations

Conclusion

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