> ## 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.

# 07 AIGO ISO 42001 Evidence Mapping v0.1

# AIGO — ISO/IEC 42001 Evidence Mapping

## AIGO — AI Governance Operating Framework

**Version:** 0.1
**Status:** Draft
**Working Name:** AIGO
**Full Name:** AI Governance Operating Framework
**Document Identifier:** `AIGO-MAP-ISO42001-007`
**Mapping Standard:** ISO/IEC 42001
**Mapping Type:** Evidence Mapping

***

### 1. Purpose

This document defines the relationship between the AIGO evidence model and the evidence expectations associated with an ISO/IEC 42001-aligned AI management system.

The purpose of this mapping is to establish a consistent relationship between governance requirements, AI lifecycle activities, risks, controls, decisions, records, monitoring, assurance, management review, and evidence.

The mapping provides a foundation for demonstrating that governance requirements have been implemented, operated, monitored, reviewed, and improved.

***

### 2. Scope

This document covers evidence associated with:

* organizational governance;
* AI management-system activities;
* AI system registration;
* classification;
* risk assessment;
* risk treatment;
* control implementation;
* approval;
* deployment;
* operation;
* monitoring;
* incidents;
* changes;
* assurance;
* management review;
* corrective action;
* continual improvement; and
* retirement.

The mapping applies to evidence generated throughout the AIGO AI Governance Lifecycle.

***

### 3. Evidence Mapping Principle

Evidence is the objective record demonstrating that an AIGO requirement, activity, decision, control, or governance obligation has been performed or achieved.

The evidence relationship can be represented as:

```text theme={null}
Requirement
   ↓
Activity
   ↓
Decision / Control
   ↓
Evidence
   ↓
Verification
   ↓
Assurance
   ↓
Management Review
   ↓
Improvement
```

Evidence should be sufficiently reliable, attributable, traceable, current, and proportionate to the significance of the activity.

***

### 4. Evidence Governance Model

#### 4.1 Evidence Purpose

Evidence should enable the organization to demonstrate:

* what was required;
* what was performed;
* who performed it;
* when it was performed;
* what decision was made;
* what information supported the decision;
* what controls were applied;
* what outcome resulted; and
* whether the activity was reviewed.

#### 4.2 Evidence Architecture

```text theme={null}
Governance Requirement
       ↓
Process / Procedure
       ↓
Activity
       ↓
Responsible Role
       ↓
Record
       ↓
Evidence Repository
       ↓
Review / Assurance
```

#### 4.3 Evidence Principle

Evidence should be generated as part of normal governance and operational processes rather than created retrospectively solely for an assessment.

***

### 5. Evidence Categories

#### 5.1 Governance Evidence

Governance evidence may include:

* policies;
* governance charters;
* role definitions;
* committee records;
* governance decisions;
* approvals;
* risk acceptance records;
* exceptions; and
* management reviews.

#### 5.2 Lifecycle Evidence

Lifecycle evidence may include:

* system registration;
* classification;
* requirements;
* assessments;
* approvals;
* deployment records;
* monitoring records;
* change records; and
* retirement records.

#### 5.3 Risk Evidence

Risk evidence may include:

* risk assessments;
* risk registers;
* risk treatment plans;
* residual-risk evaluations;
* acceptance decisions;
* risk monitoring; and
* risk reviews.

#### 5.4 Control Evidence

Control evidence may include:

* control assessments;
* control implementation records;
* testing results;
* control-owner attestations;
* monitoring outputs;
* exceptions; and
* corrective actions.

***

### 6. Evidence Lifecycle

#### 6.1 Evidence Lifecycle Model

Evidence should be managed throughout its complete lifecycle.

```text theme={null}
Evidence Requirement
       ↓
Evidence Generation
       ↓
Evidence Capture
       ↓
Evidence Validation
       ↓
Evidence Storage
       ↓
Evidence Use
       ↓
Evidence Review
       ↓
Retention / Disposal
```

#### 6.2 Evidence Lifecycle Requirements

Evidence management should address:

* creation;
* identification;
* ownership;
* classification;
* validation;
* storage;
* access;
* retention;
* review; and
* disposal.

***

### 7. Evidence Ownership

#### 7.1 Purpose

Evidence ownership establishes responsibility for ensuring that required evidence exists and remains reliable.

#### 7.2 Evidence Owner

An evidence owner should be responsible for:

* identifying required evidence;
* ensuring evidence is generated;
* ensuring evidence is accurate;
* maintaining evidence availability;
* responding to evidence requests; and
* coordinating remediation where evidence is incomplete.

#### 7.3 Ownership Model

```text theme={null}
Requirement
   ↓
Evidence Requirement
   ↓
Evidence Owner
   ↓
Evidence Creation
   ↓
Evidence Validation
   ↓
Evidence Repository
```

#### 7.4 Shared Evidence

Where evidence supports multiple requirements, ownership should remain clearly assigned even when multiple functions contribute to the evidence.

***

### 8. Evidence Requirements

#### 8.1 Purpose

Evidence requirements define what records are needed to demonstrate implementation and operation.

#### 8.2 Evidence Requirement Definition

A requirement may specify:

* evidence type;
* source;
* owner;
* frequency;
* retention;
* quality criteria;
* access restrictions; and
* review requirements.

#### 8.3 Evidence Requirement Flow

```text theme={null}
Governance Requirement
       ↓
Evidence Objective
       ↓
Evidence Type
       ↓
Evidence Owner
       ↓
Generation Method
       ↓
Retention Requirement
```

***

### 9. Evidence Traceability

#### 9.1 Purpose

Evidence traceability connects evidence to the requirement, activity, control, system, and decision that generated it.

#### 9.2 Traceability Model

```text theme={null}
Requirement
   ↓
AI System
   ↓
Lifecycle Stage
   ↓
Risk
   ↓
Control
   ↓
Evidence
   ↓
Decision
   ↓
Accountable Role
```

#### 9.3 Traceability Identifier

Material evidence should, where practical, be traceable using identifiers such as:

* AI system ID;
* requirement ID;
* risk ID;
* control ID;
* decision ID;
* evidence ID;
* incident ID; or
* change ID.

***

### 10. Evidence Quality

#### 10.1 Purpose

Evidence quality determines whether evidence is sufficiently reliable to support governance decisions and assurance conclusions.

#### 10.2 Quality Characteristics

Evidence should be assessed for:

* authenticity;
* accuracy;
* completeness;
* relevance;
* timeliness;
* consistency;
* traceability;
* integrity; and
* accessibility.

#### 10.3 Evidence Quality Model

```text theme={null}
Evidence
   ↓
Authenticity
   ↓
Accuracy
   ↓
Completeness
   ↓
Relevance
   ↓
Timeliness
   ↓
Traceability
   ↓
Evidence Quality
```

#### 10.4 Quality Principle

Evidence quality should be proportionate to the significance and risk of the associated requirement or decision.

***

### 11. Evidence Completeness

#### 11.1 Purpose

Evidence completeness determines whether the available evidence adequately covers the applicable requirement.

#### 11.2 Completeness Factors

Assessment may consider:

* required records;
* responsible roles;
* applicable lifecycle stages;
* applicable controls;
* decision records;
* monitoring results;
* review records; and
* corrective actions.

#### 11.3 Completeness Model

```text theme={null}
Requirement
   ↓
Required Evidence Set
   ↓
Available Evidence
   ↓
Gap Analysis
   ↓
Evidence Gap
   ↓
Remediation
```

***

### 12. Evidence Authenticity

#### 12.1 Purpose

Evidence authenticity establishes confidence that a record is what it claims to be and originated from the stated source.

#### 12.2 Authenticity Factors

Controls may include:

* source identification;
* system-generated records;
* access controls;
* timestamps;
* approvals;
* digital signatures;
* version history; and
* controlled repositories.

#### 12.3 Authenticity Relationship

```text theme={null}
Source
   ↓
Record Creation
   ↓
Identity / Attribution
   ↓
Integrity Protection
   ↓
Controlled Storage
   ↓
Authentic Evidence
```

***

### 13. Evidence Integrity

#### 13.1 Purpose

Evidence integrity ensures that records remain protected against unauthorized modification or destruction.

#### 13.2 Integrity Controls

Measures may include:

* access control;
* version control;
* immutable storage;
* audit logs;
* backups;
* change tracking; and
* segregation of duties.

#### 13.3 Integrity Model

```text theme={null}
Evidence Creation
       ↓
Integrity Control
       ↓
Controlled Storage
       ↓
Access Monitoring
       ↓
Integrity Verification
```

***

### 14. Evidence Availability

#### 14.1 Purpose

Required evidence should remain accessible to authorized persons for the required period.

#### 14.2 Availability Requirements

Evidence management should consider:

* repository availability;
* access permissions;
* backup;
* recovery;
* retention;
* searchability; and
* business continuity.

#### 14.3 Availability Model

```text theme={null}
Evidence
   ↓
Storage
   ↓
Backup
   ↓
Recovery
   ↓
Authorized Access
   ↓
Evidence Availability
```

***

### 15. Evidence Retention

#### 15.1 Purpose

Evidence should be retained for periods appropriate to legal, regulatory, contractual, operational, governance, and assurance requirements.

#### 15.2 Retention Factors

Retention decisions may consider:

* legal obligations;
* regulatory obligations;
* contractual obligations;
* AI system lifecycle;
* risk;
* audit requirements;
* incident investigation;
* management review; and
* organizational policy.

#### 15.3 Retention Lifecycle

```text theme={null}
Evidence Created
       ↓
Active Use
       ↓
Retention Period
       ↓
Review
       ↓
Archive / Dispose
```

***

### 16. Evidence Classification

#### 16.1 Purpose

Evidence may require classification according to sensitivity, confidentiality, integrity, criticality, or other organizational requirements.

#### 16.2 Classification Factors

Classification may consider:

* personal data;
* confidential information;
* security-sensitive information;
* proprietary information;
* commercially sensitive information;
* regulatory information; and
* public information.

#### 16.3 Classification Model

```text theme={null}
Evidence
   ↓
Sensitivity Assessment
   ↓
Classification
   ↓
Access Rules
   ↓
Handling Requirements
   ↓
Retention / Disposal
```

***

### 17. Evidence Access

#### 17.1 Purpose

Access to evidence should be restricted to authorized persons and purposes.

#### 17.2 Access Principles

Access should follow:

* least privilege;
* role-based access;
* need-to-know;
* segregation of duties; and
* appropriate authentication.

#### 17.3 Access Model

```text theme={null}
Evidence
   ↓
Classification
   ↓
Authorized Role
   ↓
Access Decision
   ↓
Access
   ↓
Access Record
```

***

### 18. Evidence and AI System Registration

#### 18.1 Purpose

AI system registration provides foundational evidence that an AI system has entered the organization's governance framework.

#### 18.2 Registration Evidence

Evidence may include:

* registration record;
* system identifier;
* owner;
* purpose;
* intended use;
* lifecycle stage;
* classification;
* dependencies; and
* approval status.

#### 18.3 Registration Evidence Flow

```text theme={null}
AI System
   ↓
Registration
   ↓
System Profile
   ↓
Governance Record
   ↓
Evidence Repository
```

***

### 19. Evidence and AI Classification

#### 19.1 Purpose

Classification evidence demonstrates how an AI system has been categorized according to applicable organizational or external requirements.

#### 19.2 Classification Evidence

Evidence may include:

* classification criteria;
* completed assessment;
* classification decision;
* decision authority;
* rationale;
* date; and
* review record.

#### 19.3 Classification Traceability

```text theme={null}
Classification Criteria
       ↓
AI System Assessment
       ↓
Classification Decision
       ↓
Rationale
       ↓
Approval
       ↓
Evidence
```

***

### 20. Evidence and Risk Assessment

#### 20.1 Purpose

Risk evidence demonstrates that AI risks have been identified, analyzed, evaluated, and treated.

#### 20.2 Risk Evidence

Evidence may include:

* risk assessment;
* risk register;
* impact analysis;
* likelihood assessment;
* risk rating;
* treatment decision;
* residual risk; and
* acceptance record.

#### 20.3 Risk Evidence Flow

```text theme={null}
AI System
   ↓
Risk Identification
   ↓
Risk Analysis
   ↓
Risk Evaluation
   ↓
Treatment
   ↓
Residual Risk
   ↓
Acceptance / Escalation
   ↓
Evidence
```

***

### 21. Evidence and Risk Treatment

#### 21.1 Purpose

Risk-treatment evidence demonstrates that identified risks have been addressed according to approved requirements.

#### 21.2 Treatment Evidence

Evidence may include:

* treatment plan;
* selected controls;
* implementation records;
* residual-risk assessment;
* responsible owner;
* completion evidence; and
* effectiveness assessment.

#### 21.3 Treatment Traceability

```text theme={null}
Risk
   ↓
Treatment Decision
   ↓
Control
   ↓
Implementation
   ↓
Evidence
   ↓
Effectiveness
```

***

### 22. Evidence and Control Assessment

#### 22.1 Purpose

Control-assessment evidence demonstrates whether applicable controls have been implemented and are operating effectively.

#### 22.2 Assessment Evidence

Evidence may include:

* control assessment;
* test procedure;
* test result;
* supporting record;
* control-owner confirmation;
* deficiency;
* corrective action; and
* reassessment.

#### 22.3 Control Assessment Flow

```text theme={null}
Control Requirement
       ↓
Control Implementation
       ↓
Assessment
       ↓
Evidence
       ↓
Effectiveness Result
       ↓
Corrective Action
```

***

### 23. Evidence and Approval

#### 23.1 Purpose

Approval evidence demonstrates that an authorized person or body approved a required AI governance decision.

#### 23.2 Approval Evidence

Approval records may contain:

* subject;
* decision;
* authority;
* date;
* conditions;
* supporting evidence;
* approver; and
* review requirements.

#### 23.3 Approval Flow

```text theme={null}
Assessment
   ↓
Evidence Package
   ↓
Authorized Review
   ↓
Approval Decision
   ↓
Approval Record
   ↓
Implementation
```

***

### 24. Evidence and Deployment

#### 24.1 Purpose

Deployment evidence demonstrates that an AI system was deployed under an approved governance state.

#### 24.2 Deployment Evidence

Evidence may include:

* deployment approval;
* release record;
* configuration;
* validation;
* security checks;
* monitoring configuration;
* responsible owner; and
* deployment date.

#### 24.3 Deployment Flow

```text theme={null}
Approved AI System
       ↓
Deployment Preparation
       ↓
Validation
       ↓
Deployment
       ↓
Verification
       ↓
Operational Evidence
```

***

### 25. Evidence and Operation

#### 25.1 Purpose

Operational evidence demonstrates that the AI system is operating according to defined requirements.

#### 25.2 Operational Evidence

Evidence may include:

* operational logs;
* system performance;
* access records;
* human oversight records;
* control checks;
* incidents;
* exceptions; and
* operational reviews.

#### 25.3 Operational Evidence Flow

```text theme={null}
AI System
   ↓
Operation
   ↓
Operational Data
   ↓
Monitoring
   ↓
Review
   ↓
Evidence
```

***

### 26. Evidence and Monitoring

#### 26.1 Purpose

Monitoring evidence demonstrates that relevant AI system, risk, control, and governance indicators are being observed.

#### 26.2 Monitoring Evidence

Evidence may include:

* monitoring reports;
* dashboards;
* alerts;
* performance records;
* risk indicators;
* control indicators;
* threshold breaches; and
* management responses.

#### 26.3 Monitoring Evidence Flow

```text theme={null}
Monitoring Requirement
       ↓
Indicator
       ↓
Measurement
       ↓
Result
       ↓
Analysis
       ↓
Decision / Action
       ↓
Evidence
```

***

### 27. Evidence and Incident Management

#### 27.1 Purpose

Incident evidence supports investigation, response, accountability, corrective action, and lessons learned.

#### 27.2 Incident Evidence

Evidence may include:

* incident report;
* detection record;
* timeline;
* investigation;
* impact assessment;
* response actions;
* communications;
* root-cause analysis; and
* corrective action.

#### 27.3 Incident Evidence Flow

```text theme={null}
Incident
   ↓
Detection
   ↓
Recording
   ↓
Investigation
   ↓
Response
   ↓
Corrective Action
   ↓
Closure
   ↓
Lessons Learned
```

***

### 28. Evidence and Change Management

#### 28.1 Purpose

Change evidence demonstrates that material changes were appropriately assessed, approved, implemented, and reviewed.

#### 28.2 Change Evidence

Evidence may include:

* change request;
* impact assessment;
* risk assessment;
* approval;
* implementation record;
* validation;
* post-change review; and
* updated documentation.

#### 28.3 Change Evidence Flow

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

***

### 29. Evidence and Assurance

#### 29.1 Purpose

Evidence provides the foundation for assurance activities.

#### 29.2 Assurance Evidence

Assurance may use:

* governance records;
* risk records;
* control evidence;
* monitoring evidence;
* operational records;
* incident records;
* change records; and
* management-review records.

#### 29.3 Assurance Flow

```text theme={null}
Evidence Set
   ↓
Evidence Review
   ↓
Testing / Verification
   ↓
Assurance Finding
   ↓
Conclusion
   ↓
Corrective Action
```

***

### 30. Evidence and Management Review

#### 30.1 Purpose

Management review should be supported by relevant evidence regarding AI governance performance and the effectiveness of the AI management system.

#### 30.2 Management Review Evidence

Evidence may include:

* performance information;
* risk information;
* monitoring results;
* incidents;
* assurance findings;
* stakeholder feedback;
* compliance information;
* corrective actions; and
* improvement opportunities.

#### 30.3 Management Review Evidence Flow

```text theme={null}
Evidence
   ↓
Management Information
   ↓
Management Review
   ↓
Decision
   ↓
Action
   ↓
Recorded Outcome
```

***

### 31. Evidence and Corrective Action

#### 31.1 Purpose

Corrective-action evidence demonstrates that identified deficiencies have been addressed.

#### 31.2 Corrective Action Evidence

Evidence may include:

* finding;
* root-cause analysis;
* corrective-action plan;
* assigned owner;
* implementation evidence;
* effectiveness assessment; and
* closure approval.

#### 31.3 Corrective Action Flow

```text theme={null}
Finding
   ↓
Root Cause
   ↓
Corrective Action
   ↓
Implementation
   ↓
Evidence
   ↓
Effectiveness Review
   ↓
Closure
```

***

### 32. Evidence and Continual Improvement

#### 32.1 Purpose

Improvement evidence demonstrates that lessons learned and performance information are converted into governance or operational improvements.

#### 32.2 Improvement Evidence

Evidence may include:

* improvement proposal;
* decision;
* change request;
* revised control;
* revised procedure;
* implementation record;
* effectiveness assessment; and
* management-review record.

#### 32.3 Improvement Flow

```text theme={null}
Performance / Finding
       ↓
Improvement Opportunity
       ↓
Decision
       ↓
Change
       ↓
Implementation
       ↓
Verification
       ↓
Evidence
```

***

### 33. Evidence and Retirement

#### 33.1 Purpose

Retirement evidence demonstrates that an AI system has been appropriately decommissioned and that relevant records and obligations have been addressed.

#### 33.2 Retirement Evidence

Evidence may include:

* retirement decision;
* approval;
* risk assessment;
* dependency assessment;
* data disposition;
* access removal;
* decommissioning record;
* verification; and
* closure record.

#### 33.3 Retirement Evidence Flow

```text theme={null}
Retirement Decision
       ↓
Planning
       ↓
Decommissioning
       ↓
Verification
       ↓
Data / Record Disposition
       ↓
Closure
       ↓
Evidence
```

***

### 34. Evidence Repository

#### 34.1 Purpose

A controlled repository should provide an appropriate location for governance and AI lifecycle evidence.

#### 34.2 Repository Requirements

The repository should support, as appropriate:

* controlled access;
* search;
* metadata;
* version control;
* auditability;
* retention;
* backup;
* retrieval; and
* secure disposal.

#### 34.3 Repository Model

```text theme={null}
Evidence
   ↓
Classification
   ↓
Metadata
   ↓
Controlled Repository
   ↓
Access / Retrieval
   ↓
Review / Assurance
```

***

### 35. Evidence Metadata

#### 35.1 Purpose

Metadata improves evidence identification, retrieval, classification, and traceability.

#### 35.2 Recommended Metadata

Evidence records may include:

* evidence ID;
* title;
* source;
* owner;
* AI system ID;
* lifecycle stage;
* requirement ID;
* risk ID;
* control ID;
* creation date;
* effective date;
* review date;
* classification;
* retention period; and
* status.

#### 35.3 Metadata Model

```text theme={null}
Evidence
   ↓
Identity
   ↓
Context
   ↓
Ownership
   ↓
Classification
   ↓
Lifecycle Information
   ↓
Retention Information
```

***

### 36. Evidence Version Control

#### 36.1 Purpose

Version control ensures that the organization can identify the applicable version of a governance record or evidence artifact.

#### 36.2 Version-Control Requirements

Where applicable, records should maintain:

* version;
* revision date;
* author;
* approver;
* change description;
* effective date; and
* superseded version.

#### 36.3 Version Flow

```text theme={null}
Evidence Version 1
       ↓
Change
       ↓
Review
       ↓
Approval
       ↓
Evidence Version 2
       ↓
Superseded Version Retained
```

***

### 37. Evidence Review

#### 37.1 Purpose

Evidence should be periodically reviewed to ensure that it remains accurate, relevant, complete, and accessible.

#### 37.2 Review Triggers

Review may be triggered by:

* scheduled review;
* material change;
* incident;
* audit;
* assurance;
* regulatory change;
* control failure; or
* management review.

#### 37.3 Review Flow

```text theme={null}
Evidence
   ↓
Review Trigger
   ↓
Evidence Review
   ↓
Valid?
 ↙       ↘
Yes       No
 ↓         ↓
Retain   Update / Replace
```

***

### 38. Evidence Gaps

#### 38.1 Purpose

Evidence gaps identify situations where required evidence is missing, incomplete, unreliable, or inaccessible.

#### 38.2 Evidence Gap Categories

Gaps may include:

* missing evidence;
* incomplete evidence;
* outdated evidence;
* inconsistent evidence;
* inaccessible evidence;
* unverifiable evidence; or
* insufficient evidence.

#### 38.3 Gap Management

```text theme={null}
Requirement
   ↓
Evidence Expected
   ↓
Evidence Available
   ↓
Gap Identified
   ↓
Impact Assessment
   ↓
Remediation
   ↓
Verification
```

***

### 39. Evidence Deficiencies

#### 39.1 Purpose

Evidence deficiencies should be evaluated according to their potential effect on governance, risk, control effectiveness, compliance, and assurance conclusions.

#### 39.2 Deficiency Evaluation

The organization may consider:

* severity;
* scope;
* recurrence;
* affected systems;
* affected controls;
* associated risk; and
* management impact.

#### 39.3 Deficiency Flow

```text theme={null}
Evidence Deficiency
       ↓
Assessment
       ↓
Risk / Impact
       ↓
Corrective Action
       ↓
Verification
       ↓
Closure
```

***

### 40. Evidence and ISO/IEC 42001 Traceability

#### 40.1 Purpose

The evidence mapping establishes a relationship between relevant ISO/IEC 42001 requirements and AIGO evidence artifacts.

#### 40.2 Traceability Model

```text theme={null}
ISO/IEC 42001 Requirement
          ↓
AIGO Governance Requirement
          ↓
AIGO Process / Control
          ↓
Required Evidence
          ↓
Evidence Record
          ↓
Verification / Assurance
```

#### 40.3 Mapping Principle

The existence of an evidence artifact does not automatically demonstrate conformity. Evidence should demonstrate that the applicable requirement has been implemented and operated effectively within the organization's context.

***

### 41. Evidence Package Model

#### 41.1 Purpose

For significant governance decisions or assurance activities, evidence may be assembled into a controlled evidence package.

#### 41.2 Evidence Package Components

An evidence package may contain:

* scope;
* requirement;
* AI system;
* risk assessment;
* controls;
* supporting evidence;
* decision;
* approval;
* monitoring results;
* assurance results; and
* conclusion.

#### 41.3 Evidence Package Flow

```text theme={null}
Requirement
   ↓
Evidence Collection
   ↓
Evidence Validation
   ↓
Evidence Package
   ↓
Review
   ↓
Decision / Assurance
```

***

### 42. Evidence Sufficiency

#### 42.1 Purpose

Evidence sufficiency determines whether available evidence is adequate for the intended governance or assurance purpose.

#### 42.2 Sufficiency Factors

Assessment may consider:

* completeness;
* reliability;
* relevance;
* independence;
* timeliness;
* traceability;
* consistency; and
* risk significance.

#### 42.3 Sufficiency Model

```text theme={null}
Evidence
   ↓
Quality Assessment
   ↓
Completeness Assessment
   ↓
Relevance Assessment
   ↓
Risk Context
   ↓
Sufficient?
 ↙        ↘
Yes        No
 ↓          ↓
Use       Remediate
```

***

### 43. Evidence for Governance Decisions

#### 43.1 Purpose

Governance decisions should be supported by evidence proportionate to the significance of the decision.

#### 43.2 Decision Evidence

Examples include evidence supporting:

* system approval;
* risk acceptance;
* material change;
* exception;
* deployment;
* suspension;
* continuation;
* retirement; and
* corrective action.

#### 43.3 Decision Evidence Model

```text theme={null}
Decision Requirement
       ↓
Supporting Information
       ↓
Risk / Impact
       ↓
Evidence
       ↓
Authorized Decision
       ↓
Decision Record
```

***

### 44. Evidence for High-Risk AI Systems

#### 44.1 Purpose

Higher-risk AI systems may require enhanced evidence because the consequences of governance failure may be greater.

#### 44.2 Enhanced Evidence

Enhanced evidence may include:

* detailed risk assessment;
* impact assessment;
* stronger approval evidence;
* control-testing evidence;
* human-oversight records;
* monitoring results;
* assurance results; and
* management-review records.

#### 44.3 Proportionality Principle

Evidence requirements should increase where risk, impact, complexity, autonomy, or regulatory significance increases.

***

### 45. Evidence and Third Parties

#### 45.1 Purpose

Third-party AI systems and services may require evidence demonstrating that relevant supplier governance requirements have been addressed.

#### 45.2 Third-Party Evidence

Evidence may include:

* supplier assessment;
* contractual requirements;
* supplier attestations;
* assurance reports;
* security documentation;
* privacy documentation;
* service performance;
* incidents; and
* change notifications.

#### 45.3 Third-Party Evidence Flow

```text theme={null}
Third-Party AI Service
       ↓
Supplier Assessment
       ↓
Contractual Requirements
       ↓
Evidence
       ↓
Monitoring
       ↓
Assurance
```

***

### 46. Evidence and External Obligations

#### 46.1 Purpose

Evidence should support applicable legal, regulatory, contractual, and organizational obligations.

#### 46.2 Obligation Traceability

```text theme={null}
External Obligation
       ↓
Internal Requirement
       ↓
Control / Procedure
       ↓
Evidence
       ↓
Verification
       ↓
Compliance / Assurance
```

#### 46.3 Obligation Principle

The organization should identify applicable obligations and determine what evidence is required to demonstrate implementation and ongoing compliance.

***

### 47. Evidence and Stakeholder Requirements

#### 47.1 Purpose

Stakeholder requirements may generate evidence obligations.

#### 47.2 Stakeholder Evidence

Relevant evidence may include:

* communications;
* disclosures;
* approvals;
* complaints;
* feedback;
* stakeholder decisions;
* consultations; and
* response records.

#### 47.3 Stakeholder Flow

```text theme={null}
Stakeholder Requirement
       ↓
Governance Requirement
       ↓
Action
       ↓
Evidence
       ↓
Stakeholder Communication
       ↓
Review
```

***

### 48. Evidence and Organizational Context

#### 48.1 Purpose

Evidence should remain aligned with the organization's current internal and external context.

#### 48.2 Context Changes

Evidence requirements may need review when there are changes to:

* organizational strategy;
* legal environment;
* regulatory environment;
* technology;
* AI portfolio;
* stakeholders;
* risk profile; or
* organizational structure.

#### 48.3 Context Review

```text theme={null}
Organizational Context
       ↓
Context Change
       ↓
Governance Review
       ↓
Evidence Requirement Review
       ↓
Updated Evidence Model
```

***

### 49. Evidence and Performance Indicators

#### 49.1 Purpose

Performance indicators provide evidence regarding the effectiveness and performance of AI governance.

#### 49.2 Example Indicators

Indicators may include:

* percentage of registered AI systems;
* percentage of completed risk assessments;
* control assessment completion;
* monitoring coverage;
* overdue corrective actions;
* incident frequency;
* assurance finding closure;
* training completion; and
* management-review action completion.

#### 49.3 Indicator Evidence Flow

```text theme={null}
Objective
   ↓
Indicator
   ↓
Measurement
   ↓
Evidence
   ↓
Analysis
   ↓
Management Decision
```

***

### 50. Evidence and Management Information

#### 50.1 Purpose

Evidence should be transformed into useful management information for governance decision-making.

#### 50.2 Management Information

Management information may summarize:

* AI portfolio;
* risk;
* control performance;
* incidents;
* monitoring;
* assurance;
* compliance;
* changes; and
* improvement.

#### 50.3 Information Flow

```text theme={null}
Evidence
   ↓
Aggregation
   ↓
Analysis
   ↓
Management Information
   ↓
Management Review
   ↓
Decision
```

***

### 51. Evidence and Governance Reporting

#### 51.1 Purpose

Governance reporting communicates relevant evidence and conclusions to authorized decision-makers.

#### 51.2 Reporting Content

Reports may include:

* status;
* risks;
* issues;
* control effectiveness;
* incidents;
* performance;
* assurance findings;
* actions; and
* decisions required.

#### 51.3 Reporting Flow

```text theme={null}
Evidence
   ↓
Analysis
   ↓
Governance Report
   ↓
Decision Authority
   ↓
Decision
   ↓
Action
```

***

### 52. Evidence and Auditability

#### 52.1 Purpose

Auditability enables an authorized reviewer to reconstruct relevant governance activities and decisions.

#### 52.2 Audit Trail

An audit trail should, where appropriate, connect:

* requirement;
* activity;
* actor;
* timestamp;
* decision;
* evidence;
* change; and
* outcome.

#### 52.3 Auditability Model

```text theme={null}
Requirement
   ↓
Activity
   ↓
Actor
   ↓
Timestamp
   ↓
Decision
   ↓
Evidence
   ↓
Outcome
```

***

### 53. Evidence and Segregation of Duties

#### 53.1 Purpose

Where appropriate, evidence should demonstrate separation between incompatible responsibilities.

#### 53.2 Examples

Segregation may be relevant between:

* system development and approval;
* control implementation and independent assessment;
* risk treatment and risk acceptance;
* operation and assurance; and
* evidence creation and independent verification.

#### 53.3 Segregation Model

```text theme={null}
Activity
   ↓
Responsible Role
   ↓
Independent Review
   ↓
Verification
   ↓
Evidence
```

***

### 54. Evidence and Independent Assurance

#### 54.1 Purpose

Independent assurance may provide additional confidence where the significance or risk of the activity warrants it.

#### 54.2 Independence Factors

Independence may be assessed based on:

* organizational reporting;
* conflicts of interest;
* technical independence;
* decision independence; and
* scope of authority.

#### 54.3 Assurance Flow

```text theme={null}
Evidence
   ↓
Independent Review
   ↓
Testing
   ↓
Finding / Conclusion
   ↓
Management Response
```

***

### 55. Evidence and Corrective-Action Effectiveness

#### 55.1 Purpose

Evidence should demonstrate whether corrective actions actually addressed the underlying deficiency.

#### 55.2 Effectiveness Evidence

Evidence may demonstrate:

* action completion;
* root cause addressed;
* control improvement;
* recurrence reduction;
* risk reduction;
* validation; and
* closure approval.

#### 55.3 Effectiveness Flow

```text theme={null}
Deficiency
   ↓
Corrective Action
   ↓
Implementation Evidence
   ↓
Effectiveness Test
   ↓
Result
   ↓
Closure / Further Action
```

***

### 56. Evidence and Lessons Learned

#### 56.1 Purpose

Lessons learned provide evidence that experience is converted into organizational improvement.

#### 56.2 Sources

Lessons may arise from:

* incidents;
* near misses;
* assurance;
* audits;
* management reviews;
* changes;
* stakeholder feedback; and
* operational experience.

#### 56.3 Lessons-Learned Flow

```text theme={null}
Experience
   ↓
Analysis
   ↓
Lesson Identified
   ↓
Improvement Decision
   ↓
Implementation
   ↓
Evidence
```

***

### 57. Evidence and Document Control

#### 57.1 Purpose

Controlled documents are a key component of the AIGO evidence environment.

#### 57.2 Document-Control Evidence

Records may demonstrate:

* document owner;
* version;
* approval;
* effective date;
* review date;
* change history; and
* status.

#### 57.3 Document-Control Flow

```text theme={null}
Document
   ↓
Review
   ↓
Approval
   ↓
Controlled Release
   ↓
Use
   ↓
Review / Revision
```

***

### 58. Evidence and Records Management

#### 58.1 Purpose

Records management ensures that governance evidence remains identifiable, protected, retrievable, and appropriately retained.

#### 58.2 Records Requirements

Records management should address:

* identification;
* ownership;
* storage;
* access;
* retention;
* retrieval;
* protection; and
* disposal.

#### 58.3 Records Flow

```text theme={null}
Record
   ↓
Classification
   ↓
Storage
   ↓
Retention
   ↓
Retrieval
   ↓
Review
   ↓
Disposition
```

***

### 59. Evidence Mapping Matrix

#### 59.1 Conceptual Matrix

| AIGO Governance Area | Evidence Examples                             | Primary Evidence Purpose           |
| -------------------- | --------------------------------------------- | ---------------------------------- |
| Governance           | Policies, decisions, committee records        | Demonstrate governance direction   |
| Roles                | Role descriptions, responsibility assignments | Demonstrate accountability         |
| Registration         | AI system records                             | Demonstrate governance entry       |
| Classification       | Classification assessments                    | Demonstrate categorization         |
| Risk                 | Risk assessments and registers                | Demonstrate risk management        |
| Controls             | Control assessments and test results          | Demonstrate control implementation |
| Approval             | Approval records                              | Demonstrate authorized decisions   |
| Deployment           | Release and validation records                | Demonstrate controlled deployment  |
| Operation            | Operational records and logs                  | Demonstrate ongoing operation      |
| Monitoring           | Monitoring reports and indicators             | Demonstrate oversight              |
| Incidents            | Incident records                              | Demonstrate response and learning  |
| Changes              | Change records                                | Demonstrate controlled change      |
| Assurance            | Assurance reports                             | Demonstrate independent evaluation |
| Management Review    | Review records                                | Demonstrate management oversight   |
| Improvement          | Corrective-action and improvement records     | Demonstrate continual improvement  |
| Retirement           | Retirement records                            | Demonstrate controlled closure     |

***

### 60. Evidence Traceability Matrix Structure

#### 60.1 Recommended Structure

A detailed implementation matrix may contain:

| Field             | Description                              |
| ----------------- | ---------------------------------------- |
| Requirement ID    | Identifier of the applicable requirement |
| AIGO Reference    | Relevant AIGO framework reference        |
| AI System ID      | Applicable AI system                     |
| Lifecycle Stage   | Relevant lifecycle stage                 |
| Risk ID           | Associated risk                          |
| Control ID        | Associated control                       |
| Evidence ID       | Evidence identifier                      |
| Evidence Owner    | Responsible evidence owner               |
| Evidence Location | Controlled repository reference          |
| Evidence Status   | Current evidence status                  |
| Review Date       | Date of evidence review                  |
| Assurance Status  | Assurance or verification status         |

#### 60.2 Traceability Principle

The matrix should support reconstruction of the relationship between governance requirements and evidence without requiring reliance on undocumented institutional knowledge.

***

### 61. Evidence Status

#### 61.1 Evidence Status Categories

Evidence may be classified as:

* planned;
* requested;
* generated;
* validated;
* approved;
* current;
* expired;
* superseded;
* deficient; or
* retired.

#### 61.2 Status Flow

```text theme={null}
Planned
   ↓
Requested
   ↓
Generated
   ↓
Validated
   ↓
Current
   ↓
Superseded / Expired
   ↓
Archived / Retired
```

***

### 62. Evidence Exceptions

#### 62.1 Purpose

Evidence exceptions provide a controlled mechanism for addressing situations where expected evidence cannot be produced or maintained.

#### 62.2 Exception Requirements

An evidence exception should document:

* missing evidence;
* reason;
* impact;
* associated risk;
* compensating evidence or controls;
* owner;
* approval;
* remediation plan; and
* review date.

#### 62.3 Exception Flow

```text theme={null}
Evidence Gap
   ↓
Exception Assessment
   ↓
Risk Evaluation
   ↓
Compensating Measure
   ↓
Approval
   ↓
Remediation
   ↓
Closure
```

***

### 63. Evidence Escalation

#### 63.1 Purpose

Material evidence deficiencies should be escalated to the appropriate governance authority.

#### 63.2 Escalation Triggers

Escalation may be required where:

* evidence is materially missing;
* evidence integrity is questionable;
* evidence indicates control failure;
* evidence indicates significant risk;
* repeated deficiencies occur; or
* assurance conclusions are affected.

#### 63.3 Escalation Flow

```text theme={null}
Evidence Issue
   ↓
Initial Assessment
   ↓
Material?
 ↙        ↘
No         Yes
 ↓           ↓
Resolve    Escalate
              ↓
      Governance Authority
              ↓
            Decision
```

***

### 64. Evidence and Continual Evidence Improvement

#### 64.1 Purpose

The evidence model should itself be subject to continual improvement.

#### 64.2 Improvement Inputs

Evidence-model improvement may be based on:

* assurance findings;
* audit findings;
* repeated evidence gaps;
* operational experience;
* changes in requirements;
* technology changes; and
* stakeholder feedback.

#### 64.3 Improvement Flow

```text theme={null}
Evidence Experience
       ↓
Gap / Opportunity
       ↓
Analysis
       ↓
Evidence Model Change
       ↓
Implementation
       ↓
Verification
```

***

### 65. Evidence Governance Responsibilities

#### 65.1 Governance Responsibility

AI governance should establish the overall expectations for evidence management.

#### 65.2 Evidence Owner Responsibility

Evidence owners should ensure that required records are generated and maintained.

#### 65.3 Control Owner Responsibility

Control owners should ensure that evidence demonstrates control operation.

#### 65.4 Assurance Responsibility

Assurance functions should evaluate evidence sufficiency and reliability within the defined scope of their work.

#### 65.5 Management Responsibility

Management should use relevant evidence to support governance decisions and management review.

***

### 66. Evidence and Proportionality

#### 66.1 Purpose

Evidence requirements should be proportionate to the nature and significance of the AI system and associated risks.

#### 66.2 Proportionality Factors

Factors may include:

* risk;
* impact;
* autonomy;
* scale;
* complexity;
* affected stakeholders;
* regulatory significance;
* system criticality; and
* organizational context.

#### 66.3 Proportionality Model

```text theme={null}
AI System Characteristics
       ↓
Risk / Impact
       ↓
Governance Requirements
       ↓
Evidence Requirements
       ↓
Evidence Depth
```

***

### 67. Evidence and AI Governance Maturity

#### 67.1 Purpose

Evidence maturity indicates the organization's ability to consistently produce and manage reliable governance evidence.

#### 67.2 Maturity Characteristics

Evidence maturity may progress from:

* informal;
* repeatable;
* defined;
* managed; to
* optimized.

#### 67.3 Maturity Relationship

```text theme={null}
Evidence Capture
       ↓
Consistency
       ↓
Traceability
       ↓
Measurement
       ↓
Assurance
       ↓
Optimization
```

***

### 68. Evidence and ISO/IEC 42001 Management-System Relationship

#### 68.1 Purpose

Evidence supports demonstration that the AI management system is established, implemented, maintained, and continually improved.

#### 68.2 Relationship

```text theme={null}
ISO/IEC 42001 Management-System Requirement
              ↓
AIGO Governance Requirement
              ↓
AIGO Process
              ↓
AIGO Control
              ↓
Evidence
              ↓
Monitoring / Assurance
              ↓
Management Review
```

#### 68.3 Evidence Principle

Evidence should demonstrate not only that documentation exists, but that relevant processes and controls are implemented and operating.

***

### 69. Evidence and Management-System Effectiveness

#### 69.1 Purpose

Evidence should support evaluation of whether the AI management system achieves intended outcomes.

#### 69.2 Effectiveness Evidence

Evidence may include:

* performance indicators;
* risk outcomes;
* control effectiveness;
* incidents;
* assurance results;
* corrective actions; and
* management decisions.

#### 69.3 Effectiveness Model

```text theme={null}
Requirement
   ↓
Implementation
   ↓
Operation
   ↓
Outcome
   ↓
Measurement
   ↓
Evaluation
   ↓
Improvement
```

***

### 70. Evidence Review Frequency

#### 70.1 Purpose

Evidence should be reviewed at intervals appropriate to its significance and lifecycle.

#### 70.2 Scheduled Review

Scheduled review may be based on:

* organizational policy;
* risk;
* control criticality;
* evidence sensitivity;
* lifecycle stage;
* regulatory requirements; and
* management requirements.

#### 70.3 Triggered Review

Review may also be triggered by:

* incidents;
* material changes;
* audit findings;
* assurance findings;
* regulatory changes;
* risk changes; or
* evidence deficiencies.

#### 70.4 Review Flow

```text theme={null}
Evidence
   ↓
Scheduled / Triggered Review
   ↓
Validity Assessment
   ↓
Update / Retain / Replace
   ↓
Verification
```

***

### 71. Evidence Control Effectiveness

#### 71.1 Purpose

Evidence controls should themselves be assessed to ensure that evidence remains trustworthy.

#### 71.2 Control Areas

Controls may address:

* access;
* modification;
* deletion;
* versioning;
* backup;
* retention;
* retrieval; and
* audit logging.

#### 71.3 Effectiveness Model

```text theme={null}
Evidence Control
       ↓
Implementation
       ↓
Operation
       ↓
Evidence
       ↓
Control Assessment
       ↓
Effectiveness Decision
```

***

### 72. Evidence Retrieval

#### 72.1 Purpose

Evidence should be retrievable within a reasonable period for authorized governance, assurance, audit, regulatory, or operational purposes.

#### 72.2 Retrieval Requirements

Retrieval should support:

* evidence identification;
* search;
* filtering;
* authorization;
* integrity verification; and
* audit trail.

#### 72.3 Retrieval Flow

```text theme={null}
Evidence Request
       ↓
Authorization
       ↓
Evidence Search
       ↓
Retrieval
       ↓
Integrity Verification
       ↓
Delivery / Review
```

***

### 73. Evidence Disposal

#### 73.1 Purpose

Evidence should be disposed of in accordance with applicable retention requirements and authorized disposal processes.

#### 73.2 Disposal Requirements

Disposal should consider:

* retention expiry;
* legal holds;
* regulatory requirements;
* contractual requirements;
* security;
* privacy;
* business requirements; and
* authorization.

#### 73.3 Disposal Flow

```text theme={null}
Retention Expiry
       ↓
Disposition Review
       ↓
Legal / Regulatory Check
       ↓
Authorization
       ↓
Secure Disposal / Archive
       ↓
Disposal Record
```

***

### 74. Evidence Mapping Control Model

#### 74.1 Control Objective

The evidence mapping process should ensure that material AIGO and ISO/IEC 42001 requirements can be connected to objective records.

#### 74.2 Control Relationship

```text theme={null}
Requirement
   ↓
Control Objective
   ↓
Control
   ↓
Evidence Requirement
   ↓
Evidence
   ↓
Verification
   ↓
Assurance
```

***

### 75. Evidence Mapping Governance Cycle

#### 75.1 Governance Cycle

The evidence mapping should be maintained as part of the governance lifecycle.

```text theme={null}
Define Requirement
       ↓
Identify Evidence
       ↓
Assign Owner
       ↓
Generate Evidence
       ↓
Validate Evidence
       ↓
Review Evidence
       ↓
Assure Evidence
       ↓
Improve Evidence Model
```

#### 75.2 Living Document Principle

This mapping should be treated as a controlled and living document.

It should be updated when:

* AIGO requirements change;
* ISO/IEC 42001 requirements or interpretations change;
* organizational context changes;
* AI systems materially change;
* governance processes change;
* controls change;
* evidence requirements change; or
* assurance identifies a mapping deficiency.

***

### 76. Final Evidence Traceability Model

#### 76.1 End-to-End Model

```text theme={null}
Organization
      ↓
Governance
      ↓
Requirement
      ↓
AI System
      ↓
Lifecycle Stage
      ↓
Risk
      ↓
Control
      ↓
Activity
      ↓
Decision
      ↓
Evidence
      ↓
Monitoring
      ↓
Assurance
      ↓
Management Review
      ↓
Improvement
```

#### 76.2 Traceability Principle

The complete evidence chain should enable an authorized reviewer to understand how an organizational requirement was translated into an operational activity and how that activity produced evidence supporting governance, assurance, and continual improvement.

***

### 77. Document Status

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

**Version:** 0.1

**Status:** Draft

**Working Name:** AIGO

**Full Name:** AI Governance Operating Framework

**Document Identifier:** `AIGO-MAP-ISO42001-007`

**Document Type:** Evidence Mapping

This document establishes the evidence-level relationship between ISO/IEC 42001 and the AIGO AI Governance Operating Framework and provides the foundation for evidence generation, traceability, validation, retention, monitoring, assurance, management review, and continual improvement.

***

### 78. End of Mapping Document

#### 78.1 Final Status

**AIGO — ISO/IEC 42001 Evidence Mapping**

**Document ID:** `AIGO-MAP-ISO42001-007`

**Version:** 0.1

**Status:** Draft

**End of Document**