> ## Documentation Index
> Fetch the complete documentation index at: https://docs.aigoframework.com/llms.txt
> Use this file to discover all available pages before exploring further.

# 06 AIGO ISO 42001 Governance Mapping v0.1

# AIGO — ISO/IEC 42001 Governance Mapping

## AIGO — AI Governance Operating Framework

**Version:** 0.1
**Status:** Draft
**Working Name:** AIGO
**Full Name:** AI Governance Operating Framework
**Document Identifier:** `AIGO-MAP-ISO42001-006`
**Mapping Standard:** ISO/IEC 42001
**Mapping Type:** Governance Mapping

***

### 1. Purpose

This document defines the relationship between the AIGO AI Governance Model and the ISO/IEC 42001 AI management system framework.

The purpose of this mapping is to establish traceability between governance structures, accountability, responsibilities, decision rights, management-system processes, AI system oversight, risk management, controls, evidence, assurance, and continual improvement.

The mapping provides a governance-oriented bridge between the AIGO framework architecture and the relevant ISO/IEC 42001 management-system requirements.

***

### 2. Scope

This document covers the governance relationship between:

* organizational governance;
* AI governance;
* management accountability;
* governance roles;
* responsibilities;
* authorities;
* decision rights;
* AI system ownership;
* risk ownership;
* control ownership;
* governance committees;
* management review;
* resource allocation;
* competence;
* communication;
* documentation;
* assurance;
* monitoring;
* change management; and
* continual improvement.

The mapping applies across the AIGO AI Governance Lifecycle and the organizational AI management system.

***

### 3. Governance Mapping Principle

AIGO treats AI governance as the mechanism through which the organization establishes direction, accountability, oversight, decision rights, controls, and continuous improvement for AI-related activities.

The governance relationship can be represented as:

```text theme={null}
Organization
   ↓
AI Governance
   ↓
Policies / Principles
   ↓
Roles / Authorities
   ↓
AI Systems
   ↓
Risk / Controls
   ↓
Decisions
   ↓
Evidence
   ↓
Monitoring / Assurance
   ↓
Management Review
   ↓
Improvement
```

Governance should therefore remain connected to operational AI activities rather than exist solely as a policy layer.

***

### 4. AIGO Governance Model

#### 4.1 Governance Purpose

AIGO governance establishes the organizational structures and decision mechanisms necessary to direct and control AI-related activities.

#### 4.2 Governance Objectives

The governance model should:

* establish accountability;
* define decision rights;
* establish governance requirements;
* assign responsibilities;
* provide oversight;
* manage AI-related risk;
* ensure appropriate controls;
* support compliance;
* maintain evidence;
* support assurance; and
* enable continual improvement.

#### 4.3 Governance Architecture

```text theme={null}
Governance Authority
       ↓
Governance Framework
       ↓
Policies / Requirements
       ↓
Roles / Responsibilities
       ↓
Processes / Procedures
       ↓
Controls
       ↓
AI Systems
       ↓
Monitoring / Assurance
       ↓
Management Review
```

***

### 5. Governance and the AI Management System

#### 5.1 Management-System Relationship

The AIGO governance model provides the organizational structure through which the AI management system can be directed and maintained.

#### 5.2 Governance Integration

Governance should establish:

* organizational direction;
* AI objectives;
* governance requirements;
* accountability;
* decision-making authority;
* risk appetite;
* control expectations;
* monitoring requirements; and
* review mechanisms.

#### 5.3 Integrated Relationship

```text theme={null}
Organizational Context
       ↓
Governance Direction
       ↓
AI Management System
       ↓
AI Governance Processes
       ↓
AI System Operations
       ↓
Performance / Risk Information
       ↓
Management Review
       ↓
Governance Decisions
```

***

### 6. Organizational Context

#### 6.1 Purpose

AI governance should be established within the context of the organization's objectives, obligations, stakeholders, and operating environment.

#### 6.2 Context Factors

Relevant factors may include:

* organizational strategy;
* business objectives;
* legal requirements;
* regulatory requirements;
* contractual obligations;
* stakeholder expectations;
* organizational structure;
* AI portfolio;
* technology environment;
* risk environment;
* resource constraints; and
* organizational maturity.

#### 6.3 Context Flow

```text theme={null}
Organization
   ↓
Strategic Objectives
   ↓
Stakeholders
   ↓
External / Internal Context
   ↓
AI Governance Requirements
   ↓
Governance Objectives
```

***

### 7. Governance Principles

#### 7.1 Purpose

Governance principles establish the fundamental expectations that guide AI-related decisions.

#### 7.2 Core Principles

AIGO governance should promote:

* accountability;
* transparency;
* proportionality;
* traceability;
* human oversight;
* risk-based decision-making;
* evidence-based governance;
* continuous monitoring;
* responsible innovation; and
* continual improvement.

#### 7.3 Principle Application

Governance principles should be translated into actionable requirements, controls, procedures, and decision criteria.

***

### 8. Governance Accountability

#### 8.1 Purpose

Accountability establishes who is answerable for AI governance outcomes.

#### 8.2 Accountability Requirements

The organization should identify accountable persons or bodies for:

* AI governance;
* AI management-system oversight;
* AI system ownership;
* risk management;
* control implementation;
* monitoring;
* assurance;
* compliance; and
* improvement.

#### 8.3 Accountability Model

```text theme={null}
Management
    ↓
AI Governance Authority
    ↓
AI System Owner
    ↓
Risk Owner
    ↓
Control Owner
    ↓
Operational Owner
```

#### 8.4 Accountability Principle

Accountability should remain clear even where operational activities are delegated or outsourced.

***

### 9. Governance Roles

#### 9.1 Purpose

Governance roles define responsibilities and decision rights for AI-related activities.

#### 9.2 Typical Roles

Relevant roles may include:

* executive sponsor;
* AI governance owner;
* AI system owner;
* AI product owner;
* risk owner;
* control owner;
* data owner;
* security owner;
* privacy owner;
* compliance function;
* legal function;
* assurance function;
* internal audit; and
* operational users.

#### 9.3 Role Definition

Each material role should have:

* defined responsibilities;
* defined authority;
* required competence;
* escalation responsibilities;
* decision rights; and
* accountability boundaries.

***

### 10. Governance Decision Rights

#### 10.1 Purpose

Decision rights define who may make, approve, reject, escalate, or review AI governance decisions.

#### 10.2 Decision Categories

Decision rights may cover:

* AI system registration;
* classification;
* risk acceptance;
* control approval;
* deployment approval;
* material change approval;
* exception approval;
* incident escalation;
* suspension;
* retirement; and
* governance-policy changes.

#### 10.3 Decision Flow

```text theme={null}
AI Governance Requirement
        ↓
Decision Point
        ↓
Authorized Role
        ↓
Decision
   ↙         ↘
Approve     Reject / Escalate
   ↓             ↓
Record        Further Review
```

***

### 11. Governance Committees

#### 11.1 Purpose

Organizations may establish governance committees or equivalent decision bodies where the scale or complexity of AI activities requires collective oversight.

#### 11.2 Committee Responsibilities

A governance body may oversee:

* AI portfolio;
* high-risk AI systems;
* risk acceptance;
* major changes;
* incidents;
* assurance findings;
* compliance issues;
* strategic AI initiatives; and
* continual improvement.

#### 11.3 Committee Governance

Committee structures should define:

* mandate;
* membership;
* authority;
* quorum;
* decision rights;
* meeting frequency;
* records; and
* escalation mechanisms.

***

### 12. Governance Policies

#### 12.1 Purpose

Governance policies establish organizational expectations for AI activities.

#### 12.2 Policy Categories

Policies may address:

* AI governance;
* responsible AI;
* AI risk;
* data governance;
* security;
* privacy;
* human oversight;
* AI system development;
* AI procurement;
* third-party AI;
* monitoring;
* incident management; and
* AI retirement.

#### 12.3 Policy Hierarchy

```text theme={null}
Governance Principles
       ↓
Policy
       ↓
Standard
       ↓
Procedure
       ↓
Control
       ↓
Operational Activity
       ↓
Evidence
```

***

### 13. Governance Objectives

#### 13.1 Purpose

Governance objectives translate organizational direction into measurable AI governance outcomes.

#### 13.2 Objective Characteristics

Objectives should be:

* relevant;
* measurable where appropriate;
* assigned to accountable roles;
* monitored;
* documented; and
* reviewed.

#### 13.3 Objective Relationship

```text theme={null}
Organizational Strategy
       ↓
AI Governance Objective
       ↓
Measure / Indicator
       ↓
Target
       ↓
Monitoring
       ↓
Management Review
```

***

### 14. AI System Governance

#### 14.1 Purpose

Every material AI system should operate within an appropriate governance structure.

#### 14.2 Governance Requirements

An AI system should, where applicable, have:

* identified owner;
* documented purpose;
* system profile;
* classification;
* risk assessment;
* applicable controls;
* approval status;
* monitoring arrangements;
* evidence;
* change-management requirements; and
* retirement criteria.

#### 14.3 AI System Governance Flow

```text theme={null}
AI System
   ↓
Registration
   ↓
Classification
   ↓
Risk Assessment
   ↓
Control Assignment
   ↓
Approval
   ↓
Operation
   ↓
Monitoring
   ↓
Review
```

***

### 15. Governance and AI Lifecycle

#### 15.1 Purpose

Governance should apply throughout the complete AI lifecycle.

#### 15.2 Lifecycle Governance

```text theme={null}
Govern
   ↓
Identify
   ↓
Classify
   ↓
Assess
   ↓
Treat
   ↓
Approve
   ↓
Deploy
   ↓
Operate
   ↓
Monitor
   ↓
Assure
   ↓
Improve
   ↓
Change / Continue / Retire
```

#### 15.3 Lifecycle Principle

Governance requirements should be appropriate to the lifecycle stage and the risk profile of the AI system.

***

### 16. Governance and Risk Management

#### 16.1 Purpose

Governance establishes the authority and accountability required to manage AI risk.

#### 16.2 Governance Responsibilities

Governance should establish:

* risk methodology;
* risk appetite;
* risk criteria;
* risk ownership;
* acceptance authority;
* escalation thresholds;
* review requirements; and
* reporting mechanisms.

#### 16.3 Risk Governance Relationship

```text theme={null}
Governance Authority
       ↓
Risk Policy
       ↓
Risk Methodology
       ↓
Risk Assessment
       ↓
Risk Treatment
       ↓
Risk Acceptance
       ↓
Risk Monitoring
       ↓
Management Review
```

***

### 17. Governance and Controls

#### 17.1 Purpose

Governance should establish expectations for the design, implementation, operation, and review of AI controls.

#### 17.2 Control Governance

Controls should have:

* defined purpose;
* control owner;
* implementation requirements;
* evidence requirements;
* effectiveness criteria;
* review frequency; and
* escalation requirements.

#### 17.3 Control Governance Flow

```text theme={null}
Risk
   ↓
Control Requirement
   ↓
Control Design
   ↓
Control Owner
   ↓
Implementation
   ↓
Evidence
   ↓
Effectiveness Assessment
   ↓
Governance Review
```

***

### 18. Governance and Human Oversight

#### 18.1 Purpose

Human oversight should be governed according to the AI system's purpose, risk, autonomy, and potential impact.

#### 18.2 Oversight Requirements

Governance should define:

* who provides oversight;
* when oversight is required;
* what decisions require human intervention;
* escalation requirements;
* override authority;
* competence requirements; and
* evidence requirements.

#### 18.3 Oversight Relationship

```text theme={null}
AI System
   ↓
Automated Output
   ↓
Human Review
   ↓
Decision
   ↓
Override / Escalation
   ↓
Evidence
```

***

### 19. Governance and Competence

#### 19.1 Purpose

AI governance requires personnel with sufficient competence to perform assigned responsibilities.

#### 19.2 Competence Areas

Competence may include:

* AI technology;
* risk management;
* governance;
* compliance;
* security;
* privacy;
* data;
* assurance;
* human oversight; and
* domain-specific knowledge.

#### 19.3 Competence Governance

The organization should determine competence requirements appropriate to each material AI governance role.

***

### 20. Governance and Awareness

#### 20.1 Purpose

Personnel involved in AI activities should understand relevant governance expectations.

#### 20.2 Awareness Topics

Awareness may cover:

* AI governance principles;
* responsibilities;
* acceptable use;
* risk;
* security;
* privacy;
* incident reporting;
* human oversight;
* change management; and
* escalation.

#### 20.3 Awareness Flow

```text theme={null}
Governance Requirements
       ↓
Training / Awareness
       ↓
Personnel
       ↓
Operational Application
       ↓
Monitoring
       ↓
Improvement
```

***

### 21. Governance Communication

#### 21.1 Purpose

Governance information should be communicated to relevant internal and external stakeholders as appropriate.

#### 21.2 Communication Topics

Communication may include:

* governance decisions;
* AI policies;
* risk information;
* incidents;
* control requirements;
* material changes;
* assurance findings; and
* management decisions.

#### 21.3 Communication Principles

Governance communication should be:

* timely;
* accurate;
* understandable;
* appropriately authorized;
* traceable; and
* proportionate.

***

### 22. Governance Documentation

#### 22.1 Purpose

Governance decisions and requirements should be supported by controlled documentation.

#### 22.2 Governance Records

Records may include:

* policies;
* governance charters;
* role definitions;
* committee records;
* decisions;
* approvals;
* risk acceptances;
* exceptions;
* management reviews;
* assurance reports; and
* corrective actions.

#### 22.3 Documentation Flow

```text theme={null}
Requirement
   ↓
Governance Decision
   ↓
Document / Record
   ↓
Implementation
   ↓
Evidence
   ↓
Review
```

***

### 23. Governance and Evidence

#### 23.1 Purpose

Governance decisions should be supported by sufficient evidence.

#### 23.2 Evidence Categories

Evidence may include:

* approval records;
* meeting minutes;
* risk assessments;
* control assessments;
* monitoring reports;
* assurance reports;
* training records;
* incident records; and
* management-review records.

#### 23.3 Evidence Relationship

```text theme={null}
Governance Requirement
       ↓
Decision
       ↓
Implementation
       ↓
Evidence
       ↓
Verification
       ↓
Assurance
```

***

### 24. Governance Monitoring

#### 24.1 Purpose

Governance monitoring determines whether governance requirements are being implemented and remain effective.

#### 24.2 Monitoring Areas

Monitoring may evaluate:

* policy compliance;
* risk status;
* control performance;
* approval status;
* incidents;
* exceptions;
* overdue actions;
* assurance findings; and
* governance objectives.

#### 24.3 Monitoring Cycle

```text theme={null}
Governance Requirement
       ↓
Indicator
       ↓
Monitoring
       ↓
Finding
       ↓
Management Decision
       ↓
Corrective Action
```

***

### 25. Governance Assurance

#### 25.1 Purpose

Assurance provides confidence that governance arrangements are appropriately designed and operating as intended.

#### 25.2 Assurance Areas

Assurance may examine:

* governance structure;
* role accountability;
* decision rights;
* risk governance;
* control governance;
* evidence;
* monitoring;
* compliance; and
* continual improvement.

#### 25.3 Assurance Relationship

```text theme={null}
Governance
   ↓
Implementation
   ↓
Evidence
   ↓
Assurance
   ↓
Finding
   ↓
Corrective Action
   ↓
Governance Improvement
```

***

### 26. Management Review

#### 26.1 Purpose

Management review provides a formal mechanism for evaluating the continuing suitability, adequacy, and effectiveness of the AI governance and management-system arrangements.

#### 26.2 Management Review Inputs

Inputs may include:

* AI governance performance;
* AI risk profile;
* control effectiveness;
* incidents;
* assurance findings;
* stakeholder feedback;
* regulatory changes;
* changes in organizational context;
* governance objectives; and
* continual-improvement opportunities.

#### 26.3 Management Review Flow

```text theme={null}
Governance Information
       ↓
Performance / Risk Review
       ↓
Management Review
       ↓
Decision
       ↓
Action
       ↓
Verification
       ↓
Updated Governance
```

***

### 27. Governance Decisions

#### 27.1 Purpose

Governance decisions should be formally recorded when they materially affect AI governance, risk, compliance, or system operation.

#### 27.2 Decision Records

A decision record should identify, as appropriate:

* decision;
* decision date;
* decision authority;
* subject;
* rationale;
* supporting evidence;
* conditions;
* actions;
* owner; and
* review requirements.

#### 27.3 Decision Traceability

```text theme={null}
Requirement
   ↓
Issue / Risk
   ↓
Evidence
   ↓
Decision
   ↓
Authority
   ↓
Action
   ↓
Verification
```

***

### 28. Governance Exceptions

#### 28.1 Purpose

Exceptions allow controlled deviation from defined governance requirements where justified and authorized.

#### 28.2 Exception Requirements

An exception should identify:

* requirement;
* reason;
* scope;
* affected AI system;
* risk;
* compensating controls;
* owner;
* approval authority;
* expiration or review date; and
* evidence.

#### 28.3 Exception Flow

```text theme={null}
Exception Request
       ↓
Impact / Risk Assessment
       ↓
Compensating Controls
       ↓
Authorized Review
       ↓
Approve / Reject
       ↓
Monitor
       ↓
Close / Renew
```

#### 28.4 Exception Principle

Exceptions should not be used to circumvent mandatory legal or regulatory obligations.

***

### 29. Governance Escalation

#### 29.1 Purpose

Escalation ensures that issues exceeding operational authority are brought to the appropriate governance level.

#### 29.2 Escalation Triggers

Triggers may include:

* material risk;
* serious incident;
* control failure;
* regulatory concern;
* unresolved assurance finding;
* significant policy exception;
* material system change; or
* repeated governance failure.

#### 29.3 Escalation Model

```text theme={null}
Issue
 ↓
Operational Review
 ↓
Within Authority?
 ↙          ↘
Yes          No
 ↓            ↓
Resolve     Escalate
               ↓
       Governance Authority
               ↓
             Decision
```

***

### 30. Governance and Change Management

#### 30.1 Purpose

Governance should ensure that material changes to AI systems and governance arrangements are appropriately assessed and approved.

#### 30.2 Change Categories

Changes may include:

* AI system changes;
* model changes;
* data changes;
* intended-use changes;
* governance-policy changes;
* control changes;
* supplier changes;
* regulatory changes; and
* organizational changes.

#### 30.3 Change Governance

```text theme={null}
Change Request
      ↓
Impact Assessment
      ↓
Risk Assessment
      ↓
Governance Review
      ↓
Approval
      ↓
Implementation
      ↓
Post-Change Review
```

***

### 31. Governance and Incident Management

#### 31.1 Purpose

Governance should establish oversight for material AI incidents and ensure that lessons learned are incorporated into the governance system.

#### 31.2 Incident Governance

Governance should define:

* incident classification;
* reporting;
* escalation;
* response authority;
* communication;
* investigation;
* corrective action; and
* management review.

#### 31.3 Incident Relationship

```text theme={null}
Incident
   ↓
Response
   ↓
Escalation
   ↓
Governance Review
   ↓
Corrective Action
   ↓
Risk / Control Update
   ↓
Lessons Learned
```

***

### 32. Governance and Supplier Management

#### 32.1 Purpose

Third-party AI services and suppliers should operate within appropriate governance arrangements.

#### 32.2 Supplier Governance

Supplier governance may include:

* due diligence;
* contractual requirements;
* risk assessment;
* security requirements;
* privacy requirements;
* performance requirements;
* incident notification;
* change notification;
* audit or assurance rights; and
* exit requirements.

#### 32.3 Supplier Governance Flow

```text theme={null}
Supplier
   ↓
Due Diligence
   ↓
Risk Assessment
   ↓
Contract
   ↓
Approval
   ↓
Monitoring
   ↓
Assurance
   ↓
Renew / Change / Exit
```

***

### 33. Governance and Resource Management

#### 33.1 Purpose

AI governance requires appropriate resources to operate effectively.

#### 33.2 Resource Categories

Resources may include:

* personnel;
* technology;
* funding;
* training;
* assurance capacity;
* monitoring tools;
* documentation systems; and
* specialist expertise.

#### 33.3 Resource Governance

Management should evaluate whether sufficient resources are available to meet AI governance objectives and manage material risks.

***

### 34. Governance Performance

#### 34.1 Purpose

Governance performance should be evaluated using appropriate indicators and evidence.

#### 34.2 Performance Areas

Measures may include:

* governance compliance;
* risk treatment completion;
* control effectiveness;
* approval cycle performance;
* incident trends;
* overdue actions;
* assurance findings;
* training completion;
* monitoring coverage; and
* continual-improvement performance.

#### 34.3 Performance Cycle

```text theme={null}
Governance Objective
       ↓
Indicator
       ↓
Measurement
       ↓
Analysis
       ↓
Management Review
       ↓
Improvement
```

***

### 35. Governance Maturity

#### 35.1 Purpose

Governance maturity represents the organization's ability to consistently apply AI governance practices.

#### 35.2 Maturity Characteristics

Maturity may progress from:

* ad hoc;
* developing;
* defined;
* managed; to
* optimized.

#### 35.3 Maturity Relationship

```text theme={null}
Governance Capability
       ↓
Process Consistency
       ↓
Measurement
       ↓
Assurance
       ↓
Learning
       ↓
Optimization
```

#### 35.4 Maturity Assessment

Maturity assessments should be used to identify improvement opportunities rather than as a substitute for mandatory governance requirements.

***

### 36. Governance Traceability

#### 36.1 Purpose

Governance traceability connects organizational requirements with decisions, roles, controls, evidence, and outcomes.

#### 36.2 Traceability Model

```text theme={null}
Organizational Requirement
       ↓
Governance Requirement
       ↓
Responsible Role
       ↓
Decision
       ↓
Control
       ↓
Evidence
       ↓
Outcome
       ↓
Review
```

#### 36.3 Traceability Requirements

Material governance requirements should be traceable to appropriate:

* policies;
* roles;
* procedures;
* controls;
* decisions;
* evidence; and
* review activities.

***

### 37. Governance and Risk Acceptance

#### 37.1 Purpose

Governance establishes the authority under which AI risks may be accepted.

#### 37.2 Acceptance Relationship

```text theme={null}
Risk Assessment
      ↓
Residual Risk
      ↓
Acceptance Criteria
      ↓
Authorized Authority
      ↓
Decision
      ↓
Record
      ↓
Monitoring
```

#### 37.3 Acceptance Governance

Risk acceptance should be performed by an authority appropriate to the significance of the risk.

***

### 38. Governance and AI System Retirement

#### 38.1 Purpose

Governance should remain active through AI system retirement and decommissioning.

#### 38.2 Retirement Governance

Retirement should consider:

* business justification;
* residual risk;
* data retention;
* records;
* dependencies;
* contractual obligations;
* security;
* privacy;
* stakeholder communication; and
* lessons learned.

#### 38.3 Retirement Flow

```text theme={null}
Retirement Decision
       ↓
Risk Assessment
       ↓
Dependency Review
       ↓
Data / Records Review
       ↓
Decommission
       ↓
Verification
       ↓
Closure
       ↓
Lessons Learned
```

***

### 39. Governance and Continual Improvement

#### 39.1 Purpose

Governance should continuously adapt to lessons learned, changing risks, new technologies, and changes in organizational context.

#### 39.2 Improvement Inputs

Improvement may be triggered by:

* management review;
* assurance findings;
* incidents;
* risk trends;
* stakeholder feedback;
* regulatory changes;
* technology changes;
* performance data; and
* emerging risks.

#### 39.3 Improvement Cycle

```text theme={null}
Governance Performance
       ↓
Review
       ↓
Finding / Opportunity
       ↓
Decision
       ↓
Change
       ↓
Implementation
       ↓
Verification
       ↓
Improved Governance
```

***

### 40. Governance Mapping to ISO/IEC 42001

#### 40.1 Mapping Principle

The AIGO governance model should be mapped to the relevant ISO/IEC 42001 management-system requirements to demonstrate structural relationships and traceability.

#### 40.2 Mapping Categories

Mapping relationships may include:

* direct governance relationship;
* supporting governance relationship;
* accountability relationship;
* process relationship;
* evidence relationship; and
* improvement relationship.

#### 40.3 Mapping Model

```text theme={null}
ISO/IEC 42001 Requirement
          ↓
Governance Expectation
          ↓
AIGO Governance Structure
          ↓
Role / Authority
          ↓
Process / Control
          ↓
Evidence
          ↓
Review
```

#### 40.4 Mapping Limitation

A mapping does not by itself establish conformity with ISO/IEC 42001. Conformity depends on the organization's implementation, effectiveness, evidence, and applicable assessment requirements.

***

### 41. Governance Assurance Model

#### 41.1 Purpose

Governance assurance should determine whether governance arrangements are appropriately designed, implemented, and maintained.

#### 41.2 Assurance Dimensions

Assurance may evaluate:

* governance structure;
* accountability;
* role competence;
* decision rights;
* policies;
* risk governance;
* control governance;
* documentation;
* monitoring;
* management review; and
* improvement.

#### 41.3 Assurance Flow

```text theme={null}
Governance Requirement
       ↓
Implementation
       ↓
Evidence
       ↓
Assurance Assessment
       ↓
Finding
       ↓
Corrective Action
       ↓
Verification
```

***

### 42. Governance Control Effectiveness

#### 42.1 Purpose

Governance controls should be evaluated for both design adequacy and operating effectiveness.

#### 42.2 Effectiveness Questions

Assessment may consider:

* Is the control appropriately designed?
* Is the responsible owner identified?
* Is the control implemented?
* Is evidence generated?
* Is the control operating consistently?
* Is the control producing the intended outcome?
* Are weaknesses identified and corrected?

#### 42.3 Effectiveness Model

```text theme={null}
Control Design
      ↓
Implementation
      ↓
Operation
      ↓
Evidence
      ↓
Effectiveness
      ↓
Improvement
```

***

### 43. Governance Review Frequency

#### 43.1 Purpose

Governance arrangements should be reviewed periodically and when material changes occur.

#### 43.2 Review Triggers

Review may be triggered by:

* scheduled governance review;
* management review;
* organizational change;
* material AI system change;
* regulatory change;
* significant incident;
* assurance finding;
* material risk change; or
* governance-performance deterioration.

#### 43.3 Review Relationship

```text theme={null}
Governance Arrangement
       ↓
Scheduled / Triggered Review
       ↓
Assessment
       ↓
Decision
       ↓
Update
       ↓
Verification
```

***

### 44. Governance Mapping Summary

#### 44.1 Summary

The AIGO-to-ISO/IEC 42001 Governance Mapping establishes the relationship between the AIGO governance architecture and the ISO/IEC 42001 AI management-system framework.

It provides traceability between:

* organizational context;
* governance principles;
* accountability;
* roles;
* decision rights;
* policies;
* AI systems;
* risk;
* controls;
* evidence;
* monitoring;
* assurance;
* management review; and
* continual improvement.

#### 44.2 Integrated Governance Architecture

```text theme={null}
Organizational Context
       ↓
Governance Direction
       ↓
Policies / Requirements
       ↓
Roles / Authorities
       ↓
AI Systems
       ↓
Risk / Controls
       ↓
Decisions
       ↓
Evidence
       ↓
Monitoring
       ↓
Assurance
       ↓
Management Review
       ↓
Continual Improvement
```

#### 44.3 Final Governance Principle

AI governance should remain an integrated management activity throughout the AI lifecycle.

The governance mapping should therefore be maintained as a controlled relationship between the AIGO governance architecture and applicable ISO/IEC 42001 requirements.

***

### 45. Document Status

**Document:** AIGO — ISO/IEC 42001 Governance Mapping

**Version:** 0.1

**Status:** Draft

**Working Name:** AIGO

**Full Name:** AI Governance Operating Framework

**Document Identifier:** `AIGO-MAP-ISO42001-006`

**Document Type:** Governance Mapping

This document establishes the governance-level relationship between ISO/IEC 42001 and the AIGO AI Governance Operating Framework and provides the foundation for governance implementation, accountability, decision-making, risk oversight, control governance, assurance, management review, and continual improvement.