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AIGO — AI Governance Operating Framework

AI System Registration Template

Version: 0.1 Status: Draft Working Name: AIGO Full Name: AI Governance Operating Framework Document Identifier: AIGO-TPL-002 Document Type: AI System Registration Template Template Purpose: Controlled Registration of an AI System

1. Template Purpose

This template provides the structured record for registering an AI system within the AIGO AI Governance Operating Framework. The registration record establishes the authoritative baseline for identifying an AI system and connecting it to:
  • ownership;
  • intended purpose;
  • business context;
  • stakeholders;
  • data;
  • technology;
  • suppliers;
  • classification;
  • risk;
  • lifecycle;
  • controls;
  • approval;
  • monitoring;
  • assurance;
  • evidence;
  • change management;
  • retirement.
Registration should occur before the AI system enters the lifecycle stage requiring formal governance. Registration does not by itself constitute approval for deployment.

2. Registration Instructions

Complete all applicable fields. Where information is not available, record: Pending — [reason] Where a field does not apply, record: Not Applicable — [reason] Use stable identifiers so the registration record can be linked to other AIGO records. Recommended related identifiers include:
  • Risk ID;
  • Control ID;
  • Assessment ID;
  • Approval ID;
  • Incident ID;
  • Change ID;
  • Monitoring ID;
  • Assurance ID;
  • Evidence ID.

3. Registration Record

3.1 Registration Identification

AI System ID: Registration Record ID: System Name: System Version: Registration Status: Registration Date: Last Updated: Next Review Date: Registration Owner: System Owner:

3.2 Registration Status

Current Status:
  • Proposed
  • Under Assessment
  • Registered
  • Approved for Development
  • Approved for Deployment
  • Operational
  • Restricted
  • Suspended
  • Retired
Status Effective Date: Status Change Reason:

4. Organization and Business Context

4.1 Organization

Organization: Legal Entity: Business Unit: Department / Function: Geographic Scope:

4.2 Business Owner

Business Owner: Role / Position: Business Responsibility: Contact / Reference:

4.3 AI System Owner

AI System Owner: Role / Position: System Accountability: Contact / Reference:

4.4 Technical Owner

Technical Owner: Role / Position: Technical Responsibility: Contact / Reference:

5. AI System Description

5.1 System Summary

Provide a concise description of the AI system:

5.2 AI Capability

Select or describe applicable capabilities:
  • Classification
  • Prediction
  • Recommendation
  • Generation
  • Retrieval
  • Ranking
  • Detection
  • Decision Support
  • Optimization
  • Forecasting
  • Conversational Interaction
  • Computer Vision
  • Speech / Audio Processing
  • Natural Language Processing
  • Other
Applicable Capability / Capabilities:

5.3 System Function

What does the system do?

5.4 Key Outputs

What outputs, recommendations, predictions, classifications, or decisions does the system produce?

5.5 Output Consumers

Who receives or uses the AI system outputs?

6. Intended Purpose

6.1 Intended Purpose Statement

Document the approved intended purpose:

6.2 Intended Use

Describe how the AI system is intended to be used:

6.3 Authorized Users

Authorized user groups:

6.4 Prohibited or Restricted Uses

Prohibited uses: Restricted uses:

6.5 Intended Decision Role

Does the system:
  • Provide information only
  • Provide decision support
  • Recommend an action
  • Automatically execute an action
  • Make or materially influence a decision
  • Other
Decision Role Description:

7. AI System Context

7.1 Operating Context

Describe the environment in which the AI system operates:

7.2 Business Process

Business process supported:

7.3 Operational Dependency

How dependent is the business process on the AI system?

7.4 Criticality

Business Criticality:
  • Low
  • Medium
  • High
  • Critical
Criticality Rationale:

8. Stakeholders and Affected Persons

8.1 Stakeholders

8.2 Affected Persons

Who may be affected by the system or its outputs?

8.3 Potential Impacts

Potential impacts may include:
  • financial;
  • operational;
  • legal;
  • privacy;
  • security;
  • safety;
  • fairness;
  • employment;
  • access;
  • reputation;
  • individual rights or interests;
  • societal impact.
Potential Impacts:

9. Lifecycle Information

9.1 Current Lifecycle Stage

Select the applicable AIGO lifecycle stage:
  • Govern
  • Identify
  • Classify
  • Assess
  • Treat
  • Approve
  • Deploy
  • Operate
  • Monitor
  • Assure
  • Improve
  • Change
  • Continue
  • Retire
Current Lifecycle Stage:

9.2 Lifecycle Status

Lifecycle Status:

9.3 Lifecycle Entry Date

Date Entered Current Stage:

9.4 Lifecycle Owner

Lifecycle / Process Owner:

9.5 Planned Next Stage

Next Expected Lifecycle Stage: Entry Conditions:

10. Development and Deployment Information

10.1 Development Status

Development Status:
  • Not Started
  • In Development
  • Testing
  • Validated
  • Approved
  • Operational
  • Retired

10.2 Deployment Environment

Select applicable environments:
  • Development
  • Test
  • Staging
  • Production
  • Restricted Production
  • Other
Deployment Environment:

10.3 Deployment Location

Hosting / Deployment Location:

10.4 Deployment Scope

Countries / Business Units / User Groups / Locations:

11. Model Information

11.1 Model Identifier

Model ID: Model Name: Model Version:

11.2 Model Type

Model Type / Architecture:

11.3 Model Provider

Model Provider: Provider Type:
  • Internal
  • External
  • Open Source
  • Commercial
  • Managed Service
  • Other

11.4 Model Dependencies

Model dependencies:

11.5 Model Documentation

Model Documentation Reference:

12. Data Information

12.1 Data Categories

Select applicable categories:
  • Public
  • Internal
  • Confidential
  • Personal Data
  • Sensitive Personal Data
  • Financial Data
  • Health Data
  • Employee Data
  • Customer Data
  • Proprietary Data
  • Operational Data
  • Other
Applicable Data Categories:

12.2 Data Sources

12.3 Data Use

Describe how data is used by the AI system:

12.4 Data Retention

Retention Requirement:

12.5 Data Quality

Data Quality Requirements: Data Quality Owner:

13. Data Governance

13.1 Data Governance Assessment

Data governance requirements applicable:

13.2 Data Ownership

Data Owner:

13.3 Data Access

Who can access the data?

13.4 Data Controls

Applicable controls may include:
  • access control;
  • data minimization;
  • data quality;
  • data validation;
  • lineage;
  • retention;
  • deletion;
  • confidentiality;
  • integrity.
Applicable Controls:

13.5 Data Evidence

Supporting Data Governance Evidence IDs:

14. Technology Architecture

14.1 System Architecture

Architecture Description:

14.2 Main Components

14.3 Integrations

Systems / APIs / Services Integrated:

14.4 Dependencies

Technical Dependencies:

15. Third-Party and Supply-Chain Information

15.1 Third-Party Services

15.2 Supplier Risk

Supplier / Third-Party Risk Assessment Reference:

15.3 Supplier Change Notification

Supplier change notification mechanism:

15.4 Supplier Incident Notification

Supplier incident notification requirements:

15.5 Supplier Assurance

Supplier assurance / evidence reference:

16. AI Classification

16.1 Classification

AIGO Classification: Classification Date: Classification Owner: Classification Reviewer: Classification Approval Authority:

16.2 Classification Factors

Classification may consider:
  • intended purpose;
  • affected persons;
  • decision significance;
  • autonomy;
  • impact;
  • risk;
  • data sensitivity;
  • security;
  • privacy;
  • fairness;
  • safety;
  • scale;
  • reversibility;
  • regulatory requirements;
  • human oversight.
Key Classification Factors:

16.3 Classification Rationale

Classification Rationale:

16.4 Reclassification Triggers

Known Reclassification Triggers:

17. Risk Information

17.1 Risk Assessment Status

Risk Assessment Status:
  • Not Started
  • Planned
  • In Progress
  • Complete
  • Approved
  • Reassessment Required

17.2 Risk Assessment Reference

Risk Assessment ID: Risk Assessment Date: Risk Assessment Owner:

17.3 Overall Risk

Overall Inherent Risk: Overall Residual Risk: Risk Status:

17.4 Key Risks

17.5 Risk Acceptance

Residual Risk Acceptance Required: Risk Acceptance Record ID: Acceptance Authority:

18. Governance Requirements

18.1 Applicable Governance Requirements

18.2 Governance Conditions

Governance Conditions:

19. Control Information

19.1 Applicable Controls

19.2 Critical Controls

Critical Controls:

19.3 Control Exceptions

Control Exceptions: Exception Record IDs:

20. Human Oversight

20.1 Human Oversight Requirement

Human Oversight Required:

20.2 Oversight Role

Responsible Role:

20.3 Oversight Activities

  • review;
  • challenge;
  • override;
  • escalation;
  • approval;
  • decision;
  • monitoring.
Applicable Oversight Activities:

20.4 Human Authority

Who has final decision authority where applicable?

20.5 Oversight Evidence

Evidence IDs:

21. Security Governance

21.1 Security Classification

Security Classification:

21.2 Security Assessment

Security Assessment ID: Assessment Status:

21.3 Security Controls

Applicable Security Controls:

21.4 Security Monitoring

Security Monitoring Requirements:

21.5 Security Evidence

Security Evidence IDs:

22. Privacy Governance

22.1 Privacy Applicability

Privacy Requirements Applicable:

22.2 Privacy Assessment

Privacy Assessment ID: Assessment Status:

22.3 Privacy Controls

Applicable Privacy Controls:

22.4 Privacy Monitoring

Privacy Monitoring Requirements:

22.5 Privacy Evidence

Privacy Evidence IDs:

23. Fairness, Impact, and Responsible AI

23.1 Applicability

Fairness / Impact Assessment Applicable:

23.2 Assessment Reference

Assessment ID:

23.3 Key Considerations

Potential considerations include:
  • fairness;
  • discrimination;
  • accessibility;
  • human impact;
  • stakeholder impact;
  • transparency;
  • explainability;
  • safety;
  • societal impact.
Key Considerations:

23.4 Assessment Results

Summary of Results:

24. Testing and Validation

24.1 Testing Status

Testing Status:

24.2 Testing Types

Applicable testing may include:
  • functional testing;
  • performance testing;
  • validation;
  • security testing;
  • privacy testing;
  • fairness testing;
  • robustness testing;
  • explainability testing;
  • human oversight testing;
  • resilience testing.
Applicable Testing:

24.3 Test Records

24.4 Validation Result

Validation Status: Validation Conclusion:

25. Approval Information

25.1 Approval Status

Approval Status:
  • Not Required
  • Pending
  • Approved
  • Approved with Conditions
  • Deferred
  • Rejected
  • Suspended

25.2 Approval Record

Approval ID: Approval Authority: Approval Date: Effective Date: Review Date:

25.3 Approval Conditions

Conditions:

25.4 Approval Evidence

Approval Evidence IDs:

26. Deployment Authorization

26.1 Deployment Status

Deployment Status:
  • Not Started
  • Planned
  • Ready
  • Approved
  • Deployed
  • Restricted
  • Suspended
  • Retired

26.2 Deployment Authorization

Deployment Authorization ID: Authorized By: Authorization Date:

26.3 Deployment Conditions

Conditions:

26.4 Deployment Evidence

Evidence IDs:

27. Monitoring

27.1 Monitoring Status

Monitoring Status: Monitoring Owner: Monitoring Plan ID:

27.2 Monitoring Requirements

27.3 Enhanced Monitoring

Enhanced Monitoring Required: Trigger: Duration:

27.4 Monitoring Escalation

Monitoring escalation process:

28. Incident Management

28.1 Incident Status

Incident Process Applicable: Incident Procedure:

28.2 Incident Triggers

Potential triggers include:
  • material harm;
  • control failure;
  • security incident;
  • privacy incident;
  • fairness issue;
  • significant model failure;
  • unauthorized operation;
  • material monitoring threshold breach.
Applicable Triggers:

28.3 Incident Records


29. Change Management

29.1 Change Status

Change Management Applicable: Change Procedure:

29.2 Material Change Criteria

Potential material changes include:
  • intended-purpose changes;
  • model changes;
  • model-version changes;
  • data changes;
  • supplier changes;
  • feature changes;
  • architecture changes;
  • control changes;
  • human-oversight changes;
  • deployment changes.
Applicable Criteria:

29.3 Change Records


30. Assurance

30.1 Assurance Status

Assurance Required: Assurance Frequency: Assurance Owner: Assurance Procedure:

30.2 Assurance Records

30.3 Open Assurance Findings


31. Evidence and Records

31.1 Evidence Repository

Evidence Repository: Evidence Owner:

31.2 Key Evidence

31.3 Evidence Completeness

Evidence Status:
  • Complete
  • Substantially Complete
  • Partially Complete
  • Incomplete
  • Under Review
Evidence Gaps:

31.4 Record Retention

Retention Requirement: Retention Owner: Retention Location: Disposition Requirement:

32. Current Governance Status

32.1 Overall Status

Current AI System Governance Status:
  • Under Registration
  • Under Assessment
  • Conditional
  • Approved
  • Operational
  • Restricted
  • Under Review
  • Suspended
  • Retiring
  • Retired

32.2 Status Rationale

Reason for Current Status:

32.3 Governance Conditions

Current Conditions:

32.4 Open Actions


33. Review and Reassessment

33.1 Periodic Review

Review Frequency: Next Review Date: Review Owner:

33.2 Triggered Review

Reassessment should be considered after:
  • significant incidents;
  • material changes;
  • risk changes;
  • control failures;
  • significant monitoring deviations;
  • classification changes;
  • regulatory changes;
  • supplier changes;
  • material stakeholder concerns.
Additional Triggers:

33.3 Reassessment Outcome

Latest Reassessment Date: Outcome: Required Actions:

34. Continual Improvement

34.1 Improvement Opportunities

Improvement Opportunities:

34.2 Improvement Records


35. Retirement

35.1 Retirement Status

Retirement Status:
  • Not Planned
  • Under Consideration
  • Approved
  • In Progress
  • Completed

35.2 Retirement Trigger

Reason / Trigger:

35.3 Retirement Approval

Retirement Approval ID: Approval Authority: Approval Date:

35.4 Retirement Evidence

Retirement Evidence IDs:

36. Registration Approval

36.1 Registration Review

Prepared By: Role: Date: Reviewed By: Role: Date:

36.2 Registration Decision

Decision:
  • Registered
  • Registered with Conditions
  • Deferred
  • Rejected
Conditions:

36.3 Registration Authority

Approval / Registration Authority: Decision Date:

37. Registration Change History


38. Registration Traceability

The registration record should maintain traceability to relevant AIGO records.

39. Registration Completion Checklist

  • AI System ID assigned
  • System name recorded
  • Organization recorded
  • Business owner assigned
  • AI system owner assigned
  • Technical owner assigned
  • Purpose documented
  • Intended use documented
  • Restricted / prohibited use documented
  • Stakeholders identified
  • Affected persons identified
  • Lifecycle stage assigned
  • Deployment context recorded
  • Model information recorded
  • Data information recorded
  • Third-party dependencies recorded
  • Classification recorded
  • Risk information linked
  • Applicable controls linked
  • Human oversight documented
  • Security requirements assessed
  • Privacy requirements assessed
  • Testing / validation status recorded
  • Approval status recorded
  • Monitoring requirements recorded
  • Incident process linked
  • Change process linked
  • Assurance requirements recorded
  • Evidence repository identified
  • Current governance status recorded
  • Review date established
  • Related records linked
  • Registration decision recorded

40. Template Usage Instructions

This template should be completed according to the organization’s approved AIGO AI System Registration Procedure. The registration record should be maintained as a controlled record throughout the AI system lifecycle. Registration information should be updated when material information changes, including:
  • intended purpose;
  • system ownership;
  • classification;
  • risk;
  • model;
  • data;
  • suppliers;
  • lifecycle stage;
  • deployment environment;
  • controls;
  • approval status;
  • monitoring status;
  • retirement status.
The registration record should not be used as a substitute for detailed:
  • risk assessments;
  • control assessments;
  • approvals;
  • incident records;
  • change records;
  • assurance records;
  • evidence records.
Where those records exist separately, this template should reference their identifiers.

41. Template Governance

41.1 Template Owner

Template Owner:

41.2 Template Review

Review Frequency: Next Review Date:

41.3 Template Change Control

Changes to this template should be managed through the applicable AIGO document and change-management process. Material changes should consider their effect on:
  • AI System Registration Procedure;
  • AI System Profile;
  • Classification Procedure;
  • Risk Assessment Procedure;
  • Control Assessment;
  • Approval;
  • Monitoring;
  • Assurance;
  • schemas;
  • mappings;
  • tools.

42. Document Control


43. Template Status

Document: AIGO — AI System Registration Template Version: 0.1 Status: Draft Working Name: AIGO Full Name: AI Governance Operating Framework Document Identifier: AIGO-TPL-002 Document Type: AI System Registration Template This template provides the controlled registration structure for identifying an AI system and maintaining its governance baseline throughout the AIGO lifecycle.

44. End of Template

AIGO — AI System Registration Template Document ID: AIGO-TPL-002 Version: 0.1 Status: Draft End of Template