Skip to main content

AIGO — ISO/IEC 42001 Lifecycle Mapping

AIGO — AI Governance Operating Framework

Version: 0.1
Status: Draft
Working Name: AIGO
Full Name: AI Governance Operating Framework
Document Identifier: AIGO-MAP-ISO42001-004
Mapping Standard: ISO/IEC 42001
Mapping Type: Lifecycle Mapping

1. Purpose

This document defines the relationship between the AIGO AI Governance Lifecycle and the ISO/IEC 42001 AI management system framework. The purpose of this mapping is to establish lifecycle traceability between AIGO governance activities and the organizational management-system processes required to establish, implement, maintain, monitor, and continually improve AI governance. ISO/IEC 42001 is an AI management system standard. It provides requirements for establishing, implementing, maintaining, and continually improving an Artificial Intelligence Management System within an organization. :contentReference[oaicite:1] AIGO translates these management-system concepts into an operational AI governance lifecycle.

2. Scope

This document maps the AIGO AI Governance Lifecycle to the relevant ISO/IEC 42001 management-system areas. The mapping covers:
  • organizational context;
  • governance establishment;
  • AI system identification;
  • classification;
  • risk assessment;
  • impact assessment;
  • control selection;
  • approval;
  • deployment;
  • operation;
  • monitoring;
  • incident management;
  • change management;
  • assurance;
  • risk acceptance;
  • retirement; and
  • continual improvement.
This document does not reproduce ISO/IEC 42001.

3. Lifecycle Mapping Principles

3.1 Governance Across the AI Lifecycle

AI governance should remain active throughout the AI system lifecycle. Governance should not be treated as a one-time approval activity.

3.2 Risk-Based Lifecycle Governance

The level of governance applied to an AI system should be proportionate to:
  • system characteristics;
  • intended purpose;
  • risk;
  • impact;
  • autonomy;
  • operating environment;
  • applicable requirements; and
  • organizational context.

3.3 Lifecycle Traceability

Each material lifecycle decision should be traceable to:
  1. The AI system.
  2. The applicable lifecycle stage.
  3. Relevant risks.
  4. Applicable controls.
  5. The responsible role.
  6. The decision or approval.
  7. Supporting evidence.
  8. Monitoring requirements.
  9. Subsequent review.

3.4 Lifecycle Continuity

AIGO treats AI governance as a continuous lifecycle rather than a sequence of isolated compliance activities. Changes in risk, technology, purpose, environment, or requirements may require the lifecycle to return to earlier governance activities.

4. AIGO Governance Lifecycle

The AIGO lifecycle is represented as:
The lifecycle is iterative. Monitoring, incidents, assurance, changes, and emerging risks may trigger reassessment and movement back to earlier lifecycle stages.

5. ISO/IEC 42001 Management-System Relationship

The AIGO lifecycle supports the management-system approach of ISO/IEC 42001. The relationship can be represented as:
ISO/IEC 42001 uses a management-system approach that includes leadership, planning, support, operation, performance evaluation, and continual improvement. Relationship: Direct Status: Covered

6. Lifecycle Stage 1 — Governance Establishment

6.1 Objective

Establish the organizational governance foundation for AI.

6.2 AIGO Activities

Activities include:
  • establishing governance authority;
  • defining governance principles;
  • establishing governance domains;
  • assigning roles;
  • defining accountability;
  • defining decision rights;
  • defining organizational scope; and
  • establishing governance objectives.

6.3 Primary AIGO References

  • framework/01-charter/AIGO-Framework-Charter-v0.1.md
  • framework/02-principles/AIGO-Framework-Principles-v0.1.md
  • framework/03-domains/AIGO-Governance-Domains-v0.1.md
  • framework/04-roles/AIGO-Governance-Roles-v0.1.md

6.4 ISO/IEC 42001 Relationship

This stage supports the establishment of organizational context, leadership, policy, responsibilities, and objectives necessary for an AI management system. Relationship: Direct Status: Covered

7. Lifecycle Stage 2 — AI System Identification

7.1 Objective

Identify and register AI systems that fall within organizational governance scope.

7.2 AIGO Activities

Activities include:
  • identifying AI systems;
  • identifying system owners;
  • identifying providers;
  • documenting intended purpose;
  • identifying users;
  • identifying dependencies;
  • recording system status; and
  • establishing system identity.

7.3 Primary AIGO Reference

framework/09-profiles/AIGO-AI-System-Profiles-v0.1.md

7.4 Supporting Procedure

guidance/02-procedures/02-AIGO-AI-System-Registration-Procedure-v0.1.md

7.5 ISO/IEC 42001 Relationship

This stage supports organizational control over AI systems within the defined management-system scope. Relationship: Direct Status: Covered

8. Lifecycle Stage 3 — AI System Classification

8.1 Objective

Determine the governance classification and applicable governance requirements for an AI system.

8.2 AIGO Activities

Classification may consider:
  • intended purpose;
  • risk;
  • impact;
  • autonomy;
  • affected stakeholders;
  • operational environment;
  • regulatory exposure;
  • system criticality; and
  • organizational policy.

8.3 Supporting Procedure

guidance/02-procedures/04-AIGO-AI-Classification-Procedure-v0.1.md

8.4 ISO/IEC 42001 Relationship

Classification supports risk-based determination of applicable governance and controls. Relationship: Supporting Status: Covered

9. Lifecycle Stage 4 — Risk and Impact Assessment

9.1 Objective

Identify, analyze, evaluate, and document AI-related risks and impacts.

9.2 AIGO Activities

Activities include:
  • risk identification;
  • risk analysis;
  • risk evaluation;
  • impact assessment;
  • stakeholder analysis;
  • control-gap identification;
  • treatment planning; and
  • residual-risk determination.

9.3 Primary AIGO Reference

framework/06-risk/AIGO-AI-Risk-Management-v0.1.md

9.4 Supporting Procedure

guidance/02-procedures/03-AIGO-AI-Risk-Assessment-Procedure-v0.1.md

9.5 ISO/IEC 42001 Relationship

Risk and impact management is a central component of AI management-system operation. Relationship: Direct Status: Covered

10. Lifecycle Stage 5 — Control Selection and Treatment

10.1 Objective

Select and implement appropriate controls to address identified AI risks and governance requirements.

10.2 AIGO Activities

Activities include:
  • identifying applicable controls;
  • evaluating control requirements;
  • assigning control owners;
  • determining implementation requirements;
  • identifying evidence;
  • establishing monitoring;
  • documenting residual risk; and
  • establishing treatment actions.

10.3 Primary AIGO Reference

framework/07-controls/AIGO-AI-Governance-Controls-v0.1.md

10.4 Supporting Implementation Guidance

guidance/01-implementation/05-AIGO-Control-Implementation-v0.1.md

10.5 Supporting Procedure

guidance/02-procedures/05-AIGO-AI-Control-Assessment-Procedure-v0.1.md

10.6 ISO/IEC 42001 Relationship

This stage translates identified risks and governance objectives into operational controls. Relationship: Direct Status: Covered

11. Lifecycle Stage 6 — Approval

11.1 Objective

Determine whether an AI system is authorized to proceed to the next lifecycle stage.

11.2 AIGO Activities

Approval should consider:
  • classification;
  • risk assessment;
  • impact assessment;
  • applicable controls;
  • control status;
  • testing;
  • validation;
  • human oversight;
  • monitoring;
  • residual risk;
  • applicable requirements;
  • required evidence; and
  • accountable approval authority.

11.3 Supporting Procedure

guidance/02-procedures/06-AIGO-AI-Approval-Procedure-v0.1.md

11.4 ISO/IEC 42001 Relationship

Approval provides governance authorization before an AI system or material change proceeds to an operational stage. Relationship: Supporting Status: Covered

12. Lifecycle Stage 7 — Deployment

12.1 Objective

Ensure that an approved AI system is deployed within its authorized scope and governance conditions.

12.2 AIGO Activities

Deployment activities may include:
  • confirming approval;
  • verifying required controls;
  • confirming monitoring;
  • confirming human oversight;
  • confirming operational ownership;
  • validating deployment configuration;
  • documenting deployment;
  • confirming rollback or recovery arrangements; and
  • confirming applicable restrictions.

12.3 Primary AIGO References

  • framework/05-lifecycle/AIGO-AI-Governance-Lifecycle-v0.1.md
  • framework/07-controls/AIGO-AI-Governance-Controls-v0.1.md
  • framework/09-profiles/AIGO-AI-System-Profiles-v0.1.md

12.4 ISO/IEC 42001 Relationship

Deployment represents the transition from governance preparation to controlled operational use. Relationship: Direct Status: Covered

13. Lifecycle Stage 8 — Operation

13.1 Objective

Operate the AI system within approved governance, risk, control, and lifecycle conditions.

13.2 AIGO Activities

Operational governance should include:
  • maintaining authorized use;
  • maintaining controls;
  • maintaining human oversight;
  • monitoring performance;
  • monitoring risks;
  • maintaining records;
  • managing incidents;
  • managing changes;
  • reviewing system status; and
  • maintaining accountability.

13.3 Primary AIGO References

  • framework/05-lifecycle/AIGO-AI-Governance-Lifecycle-v0.1.md
  • framework/07-controls/AIGO-AI-Governance-Controls-v0.1.md

13.4 Supporting Procedures

  • guidance/02-procedures/07-AIGO-AI-Change-Management-Procedure-v0.1.md
  • guidance/02-procedures/08-AIGO-AI-Incident-Management-Procedure-v0.1.md
  • guidance/02-procedures/09-AIGO-AI-Monitoring-Procedure-v0.1.md

13.5 ISO/IEC 42001 Relationship

Operation represents the controlled execution of AI systems within the organization’s AI management system. Relationship: Direct Status: Covered

14. Lifecycle Stage 9 — Monitoring

14.1 Objective

Monitor AI system performance, risks, controls, and governance effectiveness during operation.

14.2 AIGO Activities

Monitoring should include, as applicable:
  • system performance;
  • risk indicators;
  • control effectiveness;
  • incidents;
  • anomalies;
  • deviations;
  • changes in operating conditions;
  • stakeholder impacts;
  • compliance indicators; and
  • emerging risks.

14.3 Primary AIGO References

  • framework/07-controls/AIGO-AI-Governance-Controls-v0.1.md
  • framework/08-maturity/AIGO-AI-Governance-Maturity-v0.1.md

14.4 Implementation Guidance

guidance/01-implementation/07-AIGO-Monitoring-Assurance-Implementation-v0.1.md

14.5 Supporting Procedure

guidance/02-procedures/09-AIGO-AI-Monitoring-Procedure-v0.1.md

14.6 ISO/IEC 42001 Relationship

Monitoring supports performance evaluation and ongoing management-system oversight. Relationship: Direct Status: Covered

15. Lifecycle Stage 10 — Incident Management

15.1 Objective

Identify, respond to, manage, and learn from AI-related incidents.

15.2 AIGO Activities

Incident management should include:
  • incident detection;
  • incident registration;
  • incident classification;
  • severity assessment;
  • escalation;
  • containment;
  • investigation;
  • response;
  • communication;
  • corrective action;
  • lessons learned; and
  • closure.

15.3 Supporting Procedure

guidance/02-procedures/08-AIGO-AI-Incident-Management-Procedure-v0.1.md

15.4 ISO/IEC 42001 Relationship

Incident management provides an operational mechanism for addressing AI system failures, risks, and governance deviations. Relationship: Supporting Status: Covered

16. Lifecycle Stage 11 — Change Management

16.1 Objective

Ensure that material changes to AI systems are assessed and governed before and during implementation.

16.2 AIGO Activities

Changes may include:
  • model changes;
  • training-data changes;
  • data-source changes;
  • architecture changes;
  • system configuration changes;
  • deployment changes;
  • intended-purpose changes;
  • changes in autonomy;
  • changes in users;
  • changes in operating environment;
  • third-party changes; and
  • material regulatory changes.

16.3 Change Assessment

A material change should be evaluated for potential effects on:
  • risk;
  • impact;
  • classification;
  • controls;
  • human oversight;
  • monitoring;
  • approval;
  • evidence; and
  • residual risk.

16.4 Supporting Procedure

guidance/02-procedures/07-AIGO-AI-Change-Management-Procedure-v0.1.md

16.5 ISO/IEC 42001 Relationship

Change management supports controlled operation and continued suitability of the AI management system and associated AI systems. Relationship: Supporting Status: Covered

17. Lifecycle Stage 12 — Control Assessment

17.1 Objective

Evaluate whether applicable AI governance controls are implemented and operating effectively.

17.2 AIGO Activities

Control assessment should determine:
  • whether the control is defined;
  • whether ownership is assigned;
  • whether implementation exists;
  • whether evidence exists;
  • whether the control operates;
  • whether the control remains appropriate;
  • whether the control addresses the intended risk; and
  • whether corrective action is required.

17.3 Primary AIGO Reference

framework/07-controls/AIGO-AI-Governance-Controls-v0.1.md

17.4 Supporting Procedure

guidance/02-procedures/05-AIGO-AI-Control-Assessment-Procedure-v0.1.md

17.5 ISO/IEC 42001 Relationship

Control assessment contributes to evaluation of the effectiveness of the AI management system and its operational controls. Relationship: Direct Status: Covered

18. Lifecycle Stage 13 — Assurance

18.1 Objective

Provide an appropriately objective evaluation of AI governance, controls, risks, and lifecycle processes.

18.2 AIGO Activities

Assurance activities may include:
  • governance review;
  • control review;
  • evidence review;
  • testing;
  • sampling;
  • internal assessment;
  • independent assessment;
  • audit;
  • management review; and
  • assurance reporting.

18.3 Primary AIGO Reference

guidance/01-implementation/07-AIGO-Monitoring-Assurance-Implementation-v0.1.md

18.4 Supporting Procedure

guidance/02-procedures/10-AIGO-AI-Assurance-Procedure-v0.1.md

18.5 ISO/IEC 42001 Relationship

Assurance supports performance evaluation and provides evidence for determining whether governance arrangements remain suitable and effective. Relationship: Direct Status: Covered

19. Lifecycle Stage 14 — Risk Acceptance

19.1 Objective

Provide a controlled mechanism for accepting residual AI risk when the organization determines that continued operation is justified.

19.2 AIGO Activities

Risk acceptance should include:
  • identification of residual risk;
  • risk evaluation;
  • justification;
  • accountable approval;
  • documented acceptance;
  • applicable conditions;
  • review date;
  • monitoring requirements; and
  • reassessment triggers.

19.3 Primary AIGO Reference

framework/06-risk/AIGO-AI-Risk-Management-v0.1.md

19.4 Supporting Procedure

guidance/02-procedures/11-AIGO-AI-Risk-Acceptance-Procedure-v0.1.md

19.5 ISO/IEC 42001 Relationship

Risk acceptance provides a governance mechanism for formally addressing residual risk after risk treatment. Relationship: Complementary Status: Covered

20. Lifecycle Stage 15 — Continual Improvement

20.1 Objective

Continuously improve the effectiveness and suitability of AI governance.

20.2 AIGO Activities

Improvement inputs may include:
  • incidents;
  • monitoring results;
  • control assessments;
  • assurance findings;
  • audit findings;
  • risk assessments;
  • stakeholder feedback;
  • regulatory developments;
  • technological developments;
  • changes in organizational objectives; and
  • maturity assessments.

20.3 Primary AIGO Reference

framework/08-maturity/AIGO-AI-Governance-Maturity-v0.1.md

20.4 Supporting Implementation Guidance

guidance/01-implementation/08-AIGO-Continuous-Improvement-v0.1.md

20.5 Supporting Procedure

guidance/02-procedures/13-AIGO-Continuous-Improvement-Procedure-v0.1.md

20.6 ISO/IEC 42001 Relationship

Continual improvement is a core management-system principle and provides the mechanism through which the AI management system is maintained and improved over time. Relationship: Direct Status: Covered

21. Lifecycle Stage 16 — Retirement

21.1 Objective

Ensure that AI systems are retired in a controlled and documented manner.

21.2 AIGO Activities

Retirement activities may include:
  • retirement decision;
  • authorization;
  • system shutdown;
  • access removal;
  • dependency assessment;
  • data disposition;
  • record retention;
  • security review;
  • contractual review;
  • stakeholder communication;
  • residual-risk assessment;
  • evidence preservation; and
  • closure verification.

21.3 Primary AIGO Reference

framework/05-lifecycle/AIGO-AI-Governance-Lifecycle-v0.1.md

21.4 Supporting Procedure

guidance/02-procedures/12-AIGO-AI-Retirement-Procedure-v0.1.md

21.5 ISO/IEC 42001 Relationship

Retirement supports controlled lifecycle management and ensures that governance responsibilities continue through the termination of AI system operation. Relationship: Complementary Status: Covered

22. Lifecycle Reassessment Triggers

The AIGO lifecycle should return to an earlier stage when material circumstances change. Reassessment triggers may include:
  • significant AI system changes;
  • material changes in intended purpose;
  • changes in risk;
  • changes in impact;
  • serious incidents;
  • control failures;
  • changes in operating environment;
  • changes in users;
  • changes in data;
  • changes in technology;
  • changes in suppliers;
  • regulatory changes;
  • new stakeholder concerns;
  • assurance findings; and
  • changes in organizational objectives.

23. Lifecycle Decision Gates

AIGO lifecycle governance should use decision gates at appropriate points.

24. Lifecycle Evidence Model

Each material lifecycle stage should generate sufficient evidence to demonstrate governance activity and decision-making. Evidence may include:
  • AI system records;
  • classification records;
  • risk assessments;
  • impact assessments;
  • control assessments;
  • approval records;
  • deployment records;
  • monitoring reports;
  • incident records;
  • change records;
  • assurance reports;
  • risk acceptance records;
  • improvement records; and
  • retirement records.

25. Lifecycle Roles and Accountability

Lifecycle activities should be assigned to appropriate governance roles. Responsibilities may include:
  • governance authority;
  • AI system owner;
  • risk owner;
  • control owner;
  • operational owner;
  • approval authority;
  • monitoring owner;
  • incident manager;
  • assurance function; and
  • executive accountability.
The specific allocation of responsibilities should be defined by the organization’s governance structure. Primary AIGO Reference: framework/04-roles/AIGO-Governance-Roles-v0.1.md

26. Lifecycle Risk Relationship

The AIGO lifecycle and risk-management process should remain continuously connected. The relationship can be represented as:
A change in lifecycle conditions may require the risk assessment to be repeated. Primary AIGO Reference: framework/06-risk/AIGO-AI-Risk-Management-v0.1.md

27. Lifecycle Control Relationship

Controls should be applied according to lifecycle stage, risk, and governance requirements. The relationship can be represented as:
Primary AIGO Reference: framework/07-controls/AIGO-AI-Governance-Controls-v0.1.md

28. Lifecycle Monitoring Relationship

Monitoring should provide information that allows governance decisions to be made during the lifecycle. Monitoring information may trigger:
  • continued operation;
  • additional controls;
  • reassessment;
  • incident management;
  • change management;
  • risk acceptance;
  • suspension; or
  • retirement.
The relationship can be represented as:

29. Lifecycle Assurance Relationship

Assurance should evaluate whether the lifecycle is operating as intended. Assurance should consider:
  • lifecycle governance;
  • role accountability;
  • risk management;
  • control implementation;
  • evidence;
  • monitoring;
  • decision gates;
  • incident management;
  • change management;
  • approval;
  • risk acceptance; and
  • continual improvement.
Supporting Procedure: guidance/02-procedures/10-AIGO-AI-Assurance-Procedure-v0.1.md

30. Lifecycle Control and Assurance Integration

30.1 Objective

Ensure that lifecycle governance, control implementation, monitoring, and assurance operate as an integrated governance mechanism. The lifecycle should not treat controls and assurance as separate activities. Control requirements should be established during planning, implemented before approval, monitored during operation, and evaluated through assurance activities.

30.2 Integrated Lifecycle Model

The integrated relationship can be represented as:

30.3 Control Integration

Controls should be linked to: identified risks; applicable governance requirements; lifecycle stages; accountable owners; implementation evidence; monitoring requirements; assurance activities; and corrective actions. 30.4 Assurance Integration Assurance should evaluate whether: lifecycle activities are being performed; governance responsibilities are effective; controls are implemented; controls operate as intended; evidence is sufficient; risks remain within approved tolerance; monitoring is effective; and improvement actions are completed. 30.5 ISO/IEC 42001 Relationship This integrated approach supports the management-system requirements for operational control, performance evaluation, and continual improvement. Relationship: Direct Status: Covered

31. Lifecycle Management Review

31.1 Objective

Provide management with sufficient information to determine whether the AI governance lifecycle remains suitable, adequate, effective, and aligned with organizational objectives.

31.2 Management Review Inputs

Management review inputs may include:
  • changes in organizational context;
  • changes in AI governance objectives;
  • changes in applicable legal, regulatory, and contractual requirements;
  • changes in the AI portfolio;
  • AI system risk information;
  • risk and impact assessment results;
  • monitoring results;
  • control assessment results;
  • incident trends;
  • assurance findings;
  • audit findings;
  • stakeholder feedback;
  • corrective actions;
  • continual improvement actions;
  • changes in AI technology;
  • changes in suppliers and third-party dependencies; and
  • resource and competence requirements.

31.3 Management Review Activities

Management should evaluate whether:
  1. The AI governance lifecycle remains appropriate for the organization’s context.
  2. Governance objectives remain relevant.
  3. AI-related risks remain appropriately identified and controlled.
  4. Applicable controls remain suitable and effective.
  5. Monitoring activities provide sufficient information.
  6. Incidents and corrective actions are being appropriately managed.
  7. Material changes are being governed effectively.
  8. Assurance activities provide sufficient confidence.
  9. Resources remain adequate.
  10. Improvement opportunities have been identified and prioritized.

31.4 Management Review Outputs

Management review may result in:
  • governance changes;
  • policy changes;
  • changes to governance objectives;
  • changes to lifecycle requirements;
  • additional controls;
  • changes to risk treatment;
  • changes to monitoring requirements;
  • additional assurance activities;
  • resource allocation;
  • competence and training actions;
  • corrective actions;
  • improvement initiatives;
  • changes to AI system authorization;
  • suspension of an AI system; or
  • retirement of an AI system.

31.5 Management Review Decision Model

The management review process can be represented as:

31.6 Management Review Frequency

Management review should occur at a frequency appropriate to:
  • organizational context;
  • AI governance maturity;
  • AI portfolio size and complexity;
  • AI system risk profile;
  • regulatory and contractual requirements;
  • incident frequency and severity;
  • material changes to AI systems or governance processes;
  • assurance and audit findings;
  • stakeholder concerns; and
  • organizational governance requirements.
Management review should be performed at planned intervals and may also be initiated when significant events or changes require management attention. The frequency should be sufficient to ensure that management can maintain effective oversight of the AI governance lifecycle and make timely decisions when risks, deficiencies, or material changes arise. A practical review model may be:
The organization should define and document the minimum review frequency within its governance arrangements while retaining the ability to initiate additional reviews whenever circumstances require.

31.7 Triggered Management Review

A management review should be considered when there is:
  • a significant AI-related incident;
  • a material change to an AI system;
  • a material change to organizational strategy;
  • a significant change in AI risk;
  • a major control failure;
  • significant assurance or audit findings;
  • a material regulatory change;
  • a significant stakeholder concern;
  • a major technology change;
  • a significant third-party change; or
  • evidence that the AI governance lifecycle is no longer effective.

31.8 Management Review Evidence

Management review should generate documented evidence sufficient to demonstrate:
  • review date;
  • participants;
  • information considered;
  • decisions made;
  • identified issues;
  • identified opportunities;
  • assigned actions;
  • accountable owners;
  • target dates; and
  • follow-up requirements.

31.9 Management Review Accountability

Management review should be performed by the appropriate governance authority. Participation should be proportionate to the subject matter and may include:
  • executive management;
  • AI governance leadership;
  • AI system owners;
  • risk owners;
  • control owners;
  • compliance;
  • legal;
  • security;
  • privacy;
  • technical leadership;
  • assurance; and
  • other relevant stakeholders.

31.10 ISO/IEC 42001 Relationship

Lifecycle management review supports the management-system approach of ISO/IEC 42001 by providing a structured mechanism for evaluating the continuing suitability, adequacy, and effectiveness of AI governance arrangements. The review connects lifecycle performance information with management decisions and continual improvement. Relationship: Direct Status: Covered

32. Lifecycle Corrective Action

32.1 Objective

Ensure that identified nonconformities, control failures, incidents, and governance deficiencies are addressed systematically.

32.2 Corrective Action Sources

Corrective actions may originate from:
  • incidents;
  • control assessments;
  • monitoring;
  • assurance;
  • audits;
  • management review;
  • risk assessments;
  • stakeholder complaints;
  • regulatory findings; or
  • internal governance reviews.

32.3 Corrective Action Process

The corrective action process should include:
  1. Identify the issue.
  2. Record the issue.
  3. Determine the cause.
  4. Assess the associated risk.
  5. Define corrective action.
  6. Assign ownership.
  7. Establish a target date.
  8. Implement the action.
  9. Verify effectiveness.
  10. Close the action.

32.4 Corrective Action Traceability

Corrective actions should maintain traceability between:

32.5 Corrective Action Effectiveness

Effectiveness should be evaluated after implementation to determine whether:
  • the original issue has been resolved;
  • the root cause has been addressed;
  • the issue has not recurred;
  • associated risks have been reduced;
  • controls have been improved; and
  • additional actions are required.

32.6 ISO/IEC 42001 Relationship

Corrective action supports the management-system improvement cycle by providing a structured response to identified deficiencies and opportunities for improvement. Relationship: Direct Status: Covered

33. Lifecycle Evidence and Records

33.1 Objective

Ensure that lifecycle governance decisions and activities are supported by reliable documented information.

33.2 Evidence Requirements

Evidence should be:
  • attributable;
  • accurate;
  • complete;
  • current;
  • traceable;
  • protected from unauthorized modification;
  • retained according to organizational requirements; and
  • accessible to authorized users.

33.3 Lifecycle Evidence Categories

Evidence may include:
  • governance decisions;
  • AI system registrations;
  • system profiles;
  • classifications;
  • risk assessments;
  • impact assessments;
  • control records;
  • approval records;
  • testing results;
  • deployment records;
  • monitoring records;
  • incident records;
  • change records;
  • assurance records;
  • risk acceptance records;
  • corrective actions;
  • management reviews; and
  • retirement records.

33.4 Evidence Traceability

The lifecycle evidence relationship can be represented as:

33.5 Evidence Quality

Evidence should be sufficient to allow an appropriately authorized reviewer to determine:
  1. What was required.
  2. What was performed.
  3. Who performed it.
  4. When it was performed.
  5. What decision was made.
  6. What evidence supports the decision.
  7. What risks were considered.
  8. What controls were applied.
  9. What follow-up actions were required.

33.6 ISO/IEC 42001 Relationship

Documented information and evidence support effective operation, performance evaluation, governance accountability, and demonstration of management-system implementation. Relationship: Direct Status: Covered

34. Lifecycle Competence and Awareness

34.1 Objective

Ensure that personnel involved in AI governance have the competence and awareness necessary to perform assigned lifecycle responsibilities.

34.2 Competence Areas

Competence may include:
  • AI governance;
  • AI risk management;
  • control management;
  • AI system operation;
  • data governance;
  • security;
  • privacy;
  • legal and regulatory requirements;
  • monitoring;
  • incident management;
  • change management;
  • assurance; and
  • organizational governance.

34.3 Role-Based Competence

Competence requirements should be proportionate to the role. For example:
  • governance authorities require governance and decision-making competence;
  • system owners require AI system and lifecycle competence;
  • risk owners require risk-management competence;
  • control owners require control implementation competence;
  • assurance personnel require assessment and assurance competence.

34.4 Competence Assessment

Organizations should periodically determine whether personnel performing lifecycle activities remain competent. Assessment may consider:
  • qualifications;
  • experience;
  • training;
  • demonstrated capability;
  • role changes;
  • new technology;
  • new regulatory requirements; and
  • changes in governance responsibilities.

34.5 Awareness

Relevant personnel should understand:
  • AI governance objectives;
  • applicable responsibilities;
  • escalation requirements;
  • governance restrictions;
  • incident reporting requirements;
  • change requirements;
  • applicable controls; and
  • consequences of non-compliance.

34.6 ISO/IEC 42001 Relationship

Competence and awareness support effective implementation and operation of the AI management system. Relationship: Direct Status: Covered

35. Lifecycle Communication

35.1 Objective

Ensure that relevant AI governance information is communicated to appropriate stakeholders throughout the lifecycle.

35.2 Communication Areas

Communication may include:
  • governance decisions;
  • system status;
  • risk status;
  • control status;
  • incidents;
  • material changes;
  • monitoring results;
  • assurance findings;
  • corrective actions;
  • approval status; and
  • retirement status.

35.3 Communication Principles

Communication should be:
  • timely;
  • accurate;
  • relevant;
  • understandable;
  • appropriately authorized; and
  • proportionate to stakeholder needs.

35.4 Stakeholder Considerations

Relevant stakeholders may include:
  • executive management;
  • AI system owners;
  • users;
  • affected individuals;
  • risk owners;
  • control owners;
  • technical teams;
  • legal and compliance functions;
  • security functions;
  • auditors;
  • regulators; and
  • external providers.

35.5 Communication Escalation

Material information should be escalated when it may affect:
  • AI system authorization;
  • risk acceptance;
  • regulatory obligations;
  • stakeholder safety;
  • control effectiveness;
  • operational continuity;
  • security;
  • privacy; or
  • organizational reputation.

35.6 ISO/IEC 42001 Relationship

Lifecycle communication supports effective governance, accountability, operational coordination, and management-system operation. Relationship: Supporting Status: Covered

36. Lifecycle Supplier and Third-Party Relationship

36.1 Objective

Ensure that third-party AI systems, providers, services, models, data, and dependencies are incorporated into lifecycle governance.

36.2 Third-Party Governance Considerations

Organizations should consider:
  • provider identity;
  • contractual obligations;
  • system dependencies;
  • model dependencies;
  • data dependencies;
  • security requirements;
  • privacy requirements;
  • performance requirements;
  • risk allocation;
  • monitoring;
  • incident notification;
  • change notification; and
  • termination requirements.

36.3 Third-Party Lifecycle Events

Third-party changes may trigger reassessment when they involve:
  • model changes;
  • service changes;
  • data changes;
  • infrastructure changes;
  • provider changes;
  • contractual changes;
  • security changes; or
  • changes in service conditions.

36.4 Third-Party Evidence

Organizations should retain appropriate evidence relating to:
  • supplier assessments;
  • contracts;
  • service descriptions;
  • risk assessments;
  • security requirements;
  • performance requirements;
  • monitoring results;
  • incidents;
  • material changes; and
  • termination activities.

36.5 ISO/IEC 42001 Relationship

Third-party governance supports controlled operation of AI systems and management of dependencies within the AI management system. Relationship: Supporting Status: Covered

37. Lifecycle Security and Resilience

37.1 Objective

Integrate security and resilience considerations throughout the AI governance lifecycle.

37.2 Lifecycle Security Considerations

Security should be considered during:
  • identification;
  • classification;
  • assessment;
  • design;
  • implementation;
  • deployment;
  • operation;
  • monitoring;
  • change; and
  • retirement.

37.3 Resilience Considerations

Organizations should consider:
  • availability;
  • recovery;
  • continuity;
  • fallback mechanisms;
  • incident response;
  • rollback;
  • redundancy;
  • dependency management; and
  • operational recovery.

37.4 Security and Risk Relationship

Security risks should be incorporated into the broader AI risk-management process rather than managed independently from AI governance.

37.5 Security Event Relationship

A significant security event may trigger:

37.6 ISO/IEC 42001 Relationship

Security and resilience support controlled AI operation and the organization’s ability to maintain effective governance under adverse conditions. Relationship: Supporting Status: Covered

38. Lifecycle Human Oversight

38.1 Objective

Ensure that appropriate human oversight is established and maintained throughout the AI system lifecycle.

38.2 Human Oversight Considerations

Human oversight should consider: system autonomy; decision impact; risk level; intervention capability; escalation; human review; override capability; accountability; and competence.

38.3 Oversight Across Lifecycle Stages

Human oversight may be required during: classification; risk assessment; approval; deployment; operation; monitoring; incident response; change management; and retirement.

38.4 Oversight Escalation

Human intervention should be available when: system behavior is unexpected; risk exceeds approved tolerance; control failure occurs; material incidents occur; material changes are detected; monitoring identifies unacceptable outcomes; or required governance conditions are no longer satisfied.

38.5 ISO/IEC 42001 Relationship

Human oversight supports responsible AI governance and operational control of AI systems. Relationship: Supporting Status: Covered

39. Lifecycle Stakeholder and Impact Considerations

39.1 Objective

Ensure that relevant stakeholder interests and potential impacts are considered throughout the AI lifecycle.

39.2 Stakeholder Identification

Relevant stakeholders may include: users; customers; employees; affected individuals; communities; business partners; regulators; suppliers; and other parties affected by AI system outcomes.

39.3 Impact Considerations

Impact assessment may consider: safety; fairness; discrimination; privacy; security; transparency; explainability; human autonomy; economic impact; social impact; and operational impact.

39.4 Lifecycle Integration

Stakeholder and impact information should inform: classification; risk assessment; control selection; approval; monitoring; incident management; change management; and continual improvement.

39.5 ISO/IEC 42001 Relationship

Stakeholder and impact considerations support organizational context, AI risk management, and responsible operation of AI systems. Relationship: Direct Status: Covered

40.1 Objective

Ensure that changes in applicable legal, regulatory, contractual, and policy requirements are incorporated into lifecycle governance.

40.2 Regulatory Monitoring

Organizations should monitor relevant developments affecting: AI systems; data; privacy; security; consumer protection; employment; sector-specific requirements; product requirements; intellectual property; safety; and other applicable obligations.

40.3 Regulatory Change Impact Assessment

A material regulatory change should be evaluated for potential effects on: system classification; risk; controls; documentation; monitoring; approval; operational restrictions; and continued authorization.

40.4 Regulatory Change Workflow

40.5 ISO/IEC 42001 Relationship

Monitoring changes in applicable requirements supports the continued suitability of the AI management system. Relationship: Direct Status: Covered

41. Lifecycle Performance Evaluation

41.1 Objective

Evaluate whether AI governance lifecycle processes achieve intended outcomes.

41.2 Performance Evaluation Areas

Evaluation should consider: governance effectiveness; lifecycle adherence; risk-management effectiveness; control effectiveness; monitoring performance; incident trends; assurance findings; stakeholder outcomes; corrective actions; and improvement performance.

41.3 Performance Indicators

Potential indicators include: lifecycle completion rate; overdue assessments; overdue approvals; control effectiveness; incident frequency; incident resolution time; change processing time; assurance findings; corrective-action closure rate; risk acceptance frequency; and governance maturity.

41.4 Performance Evaluation Model

41.5 ISO/IEC 42001 Relationship

Performance evaluation directly supports the management-system requirement to determine whether governance arrangements achieve intended results. Relationship: Direct Status: Covered

42. Lifecycle Improvement Prioritization

42.1 Objective

Ensure that improvement activities are prioritized according to risk, impact, governance importance, and organizational objectives.

42.2 Prioritization Factors

Improvement priorities may consider: severity of identified deficiencies; affected stakeholders; risk level; regulatory importance; control weakness; incident history; assurance findings; operational impact; resource requirements; and strategic importance.

42.3 Improvement Priority Model

42.4 ISO/IEC 42001 Relationship

Prioritization supports effective continual improvement and ensures that improvement resources are directed toward material governance needs. Relationship: Direct Status: Covered

43. Lifecycle Integration with AIGO Maturity

43.1 Objective

Use lifecycle performance to assess and improve organizational AI governance maturity.

43.2 Maturity Inputs

Lifecycle maturity assessment may consider: governance consistency; lifecycle coverage; process repeatability; automation; evidence quality; monitoring capability; assurance capability; risk integration; control effectiveness; and improvement capability.

43.3 Maturity Progression

AIGO maturity may progress from:

43.4 Maturity Improvement Relationship

Lifecycle maturity should improve through a continuous feedback loop:

43.5 ISO/IEC 42001 Relationship

Maturity assessment supports continual improvement of the AI management system. Relationship: Complementary Status: Covered

44. Lifecycle Mapping Conclusion

44.1 Overall Relationship

The AIGO AI Governance Lifecycle provides an operational lifecycle model that can be used to organize and implement AI governance activities within an ISO/IEC 42001-aligned management-system environment. The mapping demonstrates that AIGO lifecycle activities collectively support: governance; organizational context; AI system identification; risk and impact management; control implementation; operational governance; monitoring; performance evaluation; assurance; corrective action; change management; risk acceptance; retirement; and continual improvement. 44.2 Continuous Governance Model The overall lifecycle relationship can be represented as:

44.3 Final Mapping Statement

AIGO should be understood as an operational AI governance framework that can provide lifecycle structure around an organization’s AI management-system activities. ISO/IEC 42001 provides the management-system context, while AIGO provides detailed lifecycle governance structure, operational procedures, controls, roles, risk processes, monitoring, assurance, and continual-improvement mechanisms. The two should therefore be treated as complementary rather than interchangeable.

45. Mapping Maintenance

45.1 Review Requirement

This mapping should be reviewed periodically and whenever material changes occur to: AIGO framework requirements; AIGO lifecycle architecture; AIGO controls; AIGO procedures; ISO/IEC 42001; applicable regulatory requirements; organizational governance requirements; or material AI governance practices.

45.2 Mapping Ownership

The organization should assign an accountable owner for maintaining this mapping. The owner should ensure that changes are: identified; assessed; documented; approved where required; incorporated into the mapping; and communicated to relevant stakeholders.

46.1 AIGO Framework Documents

framework/01-charter/AIGO-Framework-Charter-v0.1.md framework/02-principles/AIGO-Framework-Principles-v0.1.md framework/03-domains/AIGO-Governance-Domains-v0.1.md framework/04-roles/AIGO-Governance-Roles-v0.1.md framework/05-lifecycle/AIGO-AI-Governance-Lifecycle-v0.1.md framework/06-risk/AIGO-AI-Risk-Management-v0.1.md framework/07-controls/AIGO-AI-Governance-Controls-v0.1.md framework/08-maturity/AIGO-AI-Governance-Maturity-v0.1.md framework/09-profiles/AIGO-AI-System-Profiles-v0.1.md

46.2 AIGO Implementation Guidance

guidance/01-implementation/01-AIGO-Implementation-Guide-v0.1.md guidance/01-implementation/02-AIGO-Governance-Implementation-v0.1.md guidance/01-implementation/03-AIGO-AI-System-Implementation-v0.1.md guidance/01-implementation/04-AIGO-Risk-Implementation-v0.1.md guidance/01-implementation/05-AIGO-Control-Implementation-v0.1.md guidance/01-implementation/06-AIGO-Lifecycle-Implementation-v0.1.md guidance/01-implementation/07-AIGO-Monitoring-Assurance-Implementation-v0.1.md guidance/01-implementation/08-AIGO-Continuous-Improvement-v0.1.md

46.3 AIGO Procedures

guidance/02-procedures/01-AIGO-AI-Governance-Procedure-v0.1.md guidance/02-procedures/02-AIGO-AI-System-Registration-Procedure-v0.1.md guidance/02-procedures/03-AIGO-AI-Risk-Assessment-Procedure-v0.1.md guidance/02-procedures/04-AIGO-AI-Classification-Procedure-v0.1.md guidance/02-procedures/05-AIGO-AI-Control-Assessment-Procedure-v0.1.md guidance/02-procedures/06-AIGO-AI-Approval-Procedure-v0.1.md guidance/02-procedures/07-AIGO-AI-Change-Management-Procedure-v0.1.md guidance/02-procedures/08-AIGO-AI-Incident-Management-Procedure-v0.1.md guidance/02-procedures/09-AIGO-AI-Monitoring-Procedure-v0.1.md guidance/02-procedures/10-AIGO-AI-Assurance-Procedure-v0.1.md guidance/02-procedures/11-AIGO-AI-Risk-Acceptance-Procedure-v0.1.md guidance/02-procedures/12-AIGO-AI-Retirement-Procedure-v0.1.md guidance/02-procedures/13-AIGO-Continuous-Improvement-Procedure-v0.1.md

47. Document Control

Field Value Document Title AIGO — ISO/IEC 42001 Lifecycle Mapping Document Identifier AIGO-MAP-ISO42001-004 Version 0.1 Status Draft Mapping Standard ISO/IEC 42001 Mapping Type Lifecycle Mapping Owner Approved By Approval Date Next Review Date

48. Document Status

Document: AIGO — ISO/IEC 42001 Lifecycle Mapping Version: 0.1 Status: Draft Document Identifier: AIGO-MAP-ISO42001-004 Mapping Type: Lifecycle Mapping This document establishes the lifecycle-level relationship between the AIGO AI Governance Operating Framework and ISO/IEC 42001. It provides the lifecycle traceability foundation for implementation, risk management, control application, approval, operation, monitoring, assurance, corrective action, change management, retirement, and continual improvement.

49.1 End of Document

This document concludes the AIGO-to-ISO/IEC 42001 lifecycle mapping. The mapping establishes the relationship between AIGO lifecycle governance activities and the corresponding management-system concepts, governance requirements, operational processes, evidence requirements, monitoring activities, assurance activities, corrective actions, and continual-improvement mechanisms. The mapping should be maintained as a controlled document and updated whenever material changes occur to the AIGO Framework, its lifecycle architecture, applicable ISO/IEC 42001 requirements, or relevant organizational and regulatory requirements.

50. Mapping Completion Statement

50.1 Completion Status

The AIGO-to-ISO/IEC 42001 lifecycle mapping is considered complete for version 0.1 when all defined lifecycle activities have been mapped to the applicable AIGO governance structures and ISO/IEC 42001 management-system relationships.

50.2 Mapping Coverage

The completed mapping provides coverage across:
  • governance;
  • organizational context;
  • interested parties;
  • AI system identification;
  • AI system classification;
  • risk management;
  • impact management;
  • controls;
  • lifecycle management;
  • approval;
  • deployment;
  • operation;
  • monitoring;
  • assurance;
  • performance evaluation;
  • management review;
  • corrective action;
  • change management;
  • human oversight;
  • supplier and third-party management;
  • security and resilience;
  • evidence and records;
  • competence and awareness;
  • stakeholder considerations;
  • regulatory change;
  • maturity management;
  • continual improvement; and
  • retirement.

50.3 Traceability Principle

The mapping should maintain the following traceability relationship:

50.4 Governance Use

The mapping should be used as a reference for: implementation planning; ISO/IEC 42001 alignment assessment; internal governance reviews; control assessment; assurance planning; audit preparation; evidence development; gap analysis; management review; and continual improvement.

51. Version 0.1 Baseline

51.1 Baseline Purpose

Version 0.1 establishes the initial AIGO-to-ISO/IEC 42001 lifecycle mapping baseline. The baseline provides a controlled starting point for subsequent mapping refinement and validation.

51.2 Baseline Limitations

Version 0.1 should not be interpreted as a certification assessment, legal determination, or formal conformity statement. The mapping provides an architectural and operational relationship between the AIGO Framework and ISO/IEC 42001. Formal conformity assessment should be performed using the applicable requirements, organizational context, documented information, objective evidence, and assessment criteria.

51.3 Future Refinement

Future versions may expand: clause-level traceability; control-level mappings; evidence mappings; implementation guidance; assessment criteria; maturity relationships; regulatory mappings; cross-standard mappings; and automated traceability.

52.1 Document Identification

Document: AIGO — ISO/IEC 42001 Lifecycle Mapping Document ID: AIGO-MAP-ISO42001-004 Version: 0.1 Status: Draft Mapping Domain: Lifecycle Management Framework: AIGO AI Governance Framework Reference Standard: ISO/IEC 42001

52.2 Document Control Principle

Changes to this document should be managed through the AIGO change-management process. Material changes should be: Identified. Assessed. Documented. Reviewed. Approved. Versioned. Communicated. Incorporated into related mappings and implementation guidance where applicable.

53. Final Traceability Model

53.1 AIGO Lifecycle to Management System

The complete relationship can be represented as:

53.2 Traceability Outcome

The traceability model ensures that AI governance does not operate as a collection of isolated activities. Instead, governance requirements, risks, controls, operational activities, evidence, decisions, monitoring, assurance, and improvement are connected through a controlled lifecycle.

53.3 Final Statement

AIGO provides the operational governance structure through which an organization can organize AI governance activities across the complete AI system lifecycle. ISO/IEC 42001 provides the management-system structure within which those activities can be governed, evaluated, maintained, and continually improved. The mapping therefore establishes a practical bridge between:

54. End of Controlled Mapping

54.1 Final Status

AIGO-to-ISO/IEC 42001 Lifecycle Mapping — Version 0.1 Status: Draft Baseline End of Controlled Document

AIGO — ISO/IEC 42001 Lifecycle Mapping

55. Post-Mapping Implementation Use

55.1 Purpose

The completed lifecycle mapping should be used as an implementation reference connecting the AIGO Framework to the organization’s ISO/IEC 42001-aligned AI management system. The mapping should not remain a static reference document. It should support operational implementation, evidence generation, assessment, assurance, and continual improvement.

55.2 Implementation Relationship

The mapping should be used to establish the following relationship: