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AIGO — AI Governance Operating Framework

AI Continuous Improvement Template

Version: 0.1 Status: Draft Working Name: AIGO Full Name: AI Governance Operating Framework Document Identifier: AIGO-TPL-014 Document Type: AI Continuous Improvement Template Template Purpose: Controlled Identification, Prioritization, Implementation, Verification, and Closure of AI Governance Improvements

1. Template Purpose

This template provides the controlled structure for identifying, evaluating, prioritizing, implementing, verifying, and closing improvements to AI governance, AI systems, processes, controls, monitoring, assurance, procedures, evidence, and organizational capability within the AIGO AI Governance Operating Framework. Continuous improvement should ensure that AIGO remains:
  • suitable;
  • adequate;
  • effective;
  • risk-based;
  • proportionate;
  • evidence-based;
  • responsive to incidents;
  • responsive to assurance findings;
  • responsive to organizational change;
  • responsive to technological developments;
  • responsive to regulatory developments;
  • capable of improving governance outcomes.
This template establishes traceability between:
  • improvement opportunity;
  • source;
  • issue or observation;
  • root cause;
  • risk;
  • control;
  • governance requirement;
  • improvement action;
  • owner;
  • priority;
  • implementation;
  • evidence;
  • verification;
  • effectiveness;
  • management decision;
  • lessons learned.
This template does not replace the organization’s approved AIGO Continuous Improvement Procedure.

2. Improvement Instructions

Complete all applicable sections. Where information is not yet available, record: Pending — [reason] Where a field does not apply, record: Not Applicable — [reason] Each improvement should have a unique Improvement ID. Recommended identifiers include:
  • Improvement ID;
  • AI System ID;
  • Risk ID;
  • Control ID;
  • Finding ID;
  • Incident ID;
  • Change ID;
  • Assurance ID;
  • Management Review ID;
  • Evidence ID;
  • Action ID;
  • Verification ID.
Improvements should address the underlying cause where practical rather than only correcting an individual symptom.

3. Improvement Record

3.1 Identification

Improvement ID: AI System ID: Improvement Version: Improvement Title: Improvement Type:
  • Governance
  • Risk Management
  • Control
  • Monitoring
  • Assurance
  • Incident
  • Change Management
  • Process
  • Procedure
  • Documentation
  • Evidence
  • Technology
  • Data
  • Model
  • Human Oversight
  • Training / Capability
  • Supplier / Third Party
  • Regulatory / Compliance
  • Strategic
  • Other
Improvement Status:
  • Proposed
  • Under Assessment
  • Approved
  • Prioritized
  • In Progress
  • Implemented
  • Under Verification
  • Effective
  • Closed
  • Deferred
  • Rejected
  • Cancelled
Improvement Owner: Action Owner: Sponsor: Reviewer: Approval Authority: Date Identified: Target Completion Date: Actual Completion Date: Next Review Date:

4. Improvement Source

4.1 Source Type

Select applicable sources:
  • Management Review
  • Risk Assessment
  • Control Assessment
  • Assurance
  • Audit
  • Incident
  • Monitoring
  • Change Management
  • Stakeholder Feedback
  • User Feedback
  • Affected-Person Feedback
  • Regulatory Change
  • Legal Review
  • Technology Development
  • Model Evaluation
  • Data Assessment
  • Supplier Review
  • Lessons Learned
  • Maturity Assessment
  • Strategic Review
  • Other
Primary Source:

4.2 Source Reference

Source Record ID: Related Source IDs:

5. Improvement Opportunity

5.1 Observation

What was observed?

5.2 Current Condition

Current State:

5.3 Desired Condition

Desired Future State:

5.4 Improvement Opportunity

Describe the improvement opportunity:

5.5 Why Improvement Is Needed

Rationale:

6. Problem and Root Cause

6.1 Problem Statement

Problem:

6.2 Root Cause

Primary Root Cause:

6.3 Contributing Causes

6.4 Root Cause Confidence

Confidence:
  • High
  • Medium
  • Low
  • Preliminary
Rationale:

6.5 Temporary Measures

Temporary / Containment Measures Already Applied:

7. Risk Relationship

7.2 Risk Reduction Objective

How the improvement is expected to reduce or manage risk:

7.3 Expected Risk Outcome

Expected Risk After Improvement:

8. Control Relationship

8.2 Control Improvement Objective

Control Objective:

8.3 New or Modified Controls

Controls to be created or modified:

9. Governance Relationship

9.1 Governance Area

Governance Area Affected:
  • Governance Structure
  • Roles and Accountability
  • Decision Authority
  • Policy
  • Lifecycle
  • Risk
  • Controls
  • Monitoring
  • Assurance
  • Incident Management
  • Change Management
  • Approval
  • Evidence
  • Management Review
  • Other
Applicable Area:

9.2 Governance Requirement

Requirement Affected:

9.3 Governance Change

Required Governance Change:

10. AI Lifecycle Impact

10.1 Affected Lifecycle Stages

  • Govern
  • Identify
  • Classify
  • Assess
  • Treat
  • Approve
  • Deploy
  • Operate
  • Monitor
  • Assure
  • Improve
  • Change
  • Continue
  • Retire
Applicable Stages:

10.2 Lifecycle Impact

How the improvement affects the lifecycle:

11. Stakeholder and Affected-Person Impact

11.1 Stakeholders

11.2 Affected Persons

Potential Impact on Affected Persons:

11.3 Stakeholder Engagement

Required Engagement: Evidence IDs:

12. Improvement Priority

12.1 Priority Factors

Priority should consider:
  • risk reduction;
  • potential harm reduction;
  • regulatory significance;
  • control criticality;
  • number of affected persons;
  • urgency;
  • recurrence;
  • operational impact;
  • strategic importance;
  • cost;
  • feasibility;
  • dependency.
Priority Factors:

12.2 Priority

Priority:
  • Critical
  • High
  • Medium
  • Low
Priority Rationale:

13. Improvement Urgency

13.1 Urgency

Urgency:
  • Immediate
  • Near-Term
  • Planned
  • Long-Term
Rationale:

13.2 Time Sensitivity

Time-Sensitive Requirement:

14. Improvement Options

14.1 Options Considered

14.2 Selected Option

Selected Option:

14.3 Selection Rationale

Rationale:

15. Improvement Plan

15.1 Improvement Objective

Objective:

15.2 Success Criteria

Success Criteria:

15.3 Action Plan


16. Resources and Dependencies

16.1 Required Resources

People: Technology: Budget: Expertise:

16.2 Dependencies

Dependencies:

16.3 Dependency Owners


17. Implementation

17.1 Implementation Status

Status:
  • Not Started
  • Planned
  • In Progress
  • Blocked
  • Complete
Current Status Summary:

17.2 Implementation Activities

Activities Completed:

17.3 Implementation Evidence

Evidence IDs:

17.4 Implementation Issues

Issues / Blockers:

18. Change Management Relationship

18.1 Change Required

Does implementation require an AIGO change-management process?
  • Yes
  • No
  • To Be Determined

18.2 Change Record

Change ID:

18.3 Change Classification

Change Classification:

18.4 Change Approval

Approval Status:

19. Risk During Implementation

19.1 Implementation Risk

Risks introduced by implementation:

19.2 Temporary Risk

Temporary / Transitional Risk:

19.3 Mitigating Controls

Controls:

20. Verification Plan

20.1 Verification Required

Verification Required:

20.2 Verification Objective

Objective:

20.3 Verification Method

Potential methods include:
  • evidence review;
  • testing;
  • control assessment;
  • monitoring;
  • independent validation;
  • assurance;
  • interview;
  • observation;
  • performance comparison.
Selected Method:

20.4 Verification Owner

Owner:

20.5 Verification Date

Planned Date:

21. Effectiveness Assessment

21.1 Effectiveness Criteria

The improvement should be assessed against:
  • original objective;
  • success criteria;
  • risk reduction;
  • control effectiveness;
  • stakeholder impact;
  • operational performance;
  • sustainability.
Applicable Criteria:

21.2 Effectiveness Result

Result:
  • Effective
  • Partially Effective
  • Ineffective
  • Not Yet Determined
Rationale:

21.3 Evidence of Effectiveness

Evidence IDs:

22. Risk Outcome

22.1 Risk Before Improvement

Risk Level Before Improvement:

22.2 Risk After Improvement

Risk Level After Improvement:

22.3 Risk Reduction

Risk Reduction Achieved:

22.4 Residual Risk

Residual Risk:

23. Control Outcome

23.1 Control Before Improvement

Control Effectiveness Before Improvement:

23.2 Control After Improvement

Control Effectiveness After Improvement:

23.3 Control Result

Result:
  • Improved
  • Unchanged
  • Partially Improved
  • Deteriorated
Rationale:

24. Monitoring Outcome

24.1 Monitoring Impact

Monitoring Requirements Changed:

24.2 Monitoring Indicators

24.3 Monitoring Result

Result:

25. Stakeholder Outcome

25.1 Stakeholder Feedback

Feedback After Improvement:

25.2 Affected-Person Outcome

Observed Outcome:

25.3 Unintended Consequences

Unintended Consequences:

26. Assurance and Independent Verification

26.1 Assurance Required

Assurance Required:

26.2 Assurance Record

Assurance ID:

26.3 Independent Verification

Independent Verification Required: Verification ID:

26.4 Assurance Result

Result:

27. Evidence

27.1 Evidence Repository

Evidence Repository: Evidence Owner:

27.2 Evidence Register

27.3 Evidence Completeness

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

27.4 Evidence Quality

Evidence Quality:
  • Strong
  • Adequate
  • Moderate
  • Weak
  • Insufficient
Rationale:

28. Lessons Learned

28.1 Lessons

Lessons Learned:

28.2 Reusable Improvements

Improvements That Could Be Applied Elsewhere:

28.3 Framework Lessons

Lessons for AIGO Framework Development:

29. Standardization and Reuse

29.1 Reusable Practice

Can the improvement become a standard practice?
  • Yes
  • No
  • Potentially
Rationale:

29.2 Template / Procedure Update

Does the improvement require changes to a template or procedure?
  • Yes
  • No
Affected Documents:

29.3 Control Standardization

Should the improved control be applied across other AI systems?
  • Yes
  • No
  • Assess
Rationale:

30. Portfolio-Level Improvement

30.1 Other Systems Affected

Other AI Systems That May Benefit:

30.2 Enterprise-Wide Impact

Organization-Wide Implications:

30.3 Portfolio Action

Required Portfolio Action:

31. Improvement Closure

31.1 Closure Criteria

The improvement should not be closed until applicable criteria have been satisfied.
  • Improvement objective defined
  • Root cause assessed
  • Action plan established
  • Owner assigned
  • Required resources identified
  • Implementation completed
  • Implementation evidence retained
  • Verification completed
  • Effectiveness assessed
  • Risk outcome assessed
  • Control outcome assessed
  • Monitoring outcome assessed
  • Stakeholder impact reviewed
  • Unintended consequences reviewed
  • Assurance completed where required
  • Lessons learned recorded
  • Required documents updated
  • Required portfolio actions identified
  • Management decision recorded
  • Closure authority identified

32. Closure Decision

32.1 Status

Closure Status:
  • Closed
  • Closed with Follow-Up
  • Deferred
  • Reopened
  • Cancelled

32.2 Closure Rationale

Rationale:

32.3 Closure Authority

Closure Authority: Closure Date: Closure Record ID:

33. Follow-Up

33.1 Follow-Up Required

Follow-Up Required:

33.2 Follow-Up Owner

Owner:

33.3 Follow-Up Date

Date:

33.4 Follow-Up Evidence

Evidence IDs:

34. Management Review Relationship

34.1 Management Review Reference

Management Review ID:

34.2 Review Decision

Management Decision:

34.3 Management Conditions

Conditions:

35. Improvement Traceability

The improvement should maintain links to the records that generated, support, and verify the improvement.

36. Improvement Traceability Model


37. Improvement Review and Approval

37.1 Prepared By

Name: Role: Date:

37.2 Reviewed By

Name: Role: Date:

37.3 Approved By

Name: Role: Date:

37.4 Decision

Decision:
  • Approved
  • Approved with Conditions
  • Returned for Revision
  • Deferred
  • Rejected
Conditions:

38. Improvement Review Schedule

38.1 Periodic Review

Review Frequency: Next Review Date: Review Owner:

38.2 Triggered Review

Reassessment should be considered when:
  • effectiveness is uncertain;
  • intended benefits are not achieved;
  • risk changes;
  • control performance deteriorates;
  • incidents recur;
  • new information becomes available;
  • unintended consequences emerge;
  • organizational context changes.
Additional Triggers:

39. Improvement Change History


40. Improvement Completion Checklist

  • Improvement ID assigned
  • Source identified
  • Observation documented
  • Current condition documented
  • Desired condition documented
  • Root cause assessed
  • Risk relationship documented
  • Control relationship documented
  • Governance relationship documented
  • Lifecycle impact assessed
  • Stakeholder impact assessed
  • Priority assigned
  • Urgency assessed
  • Improvement options considered
  • Selected option documented
  • Objective established
  • Success criteria established
  • Action plan established
  • Owner assigned
  • Resources identified
  • Dependencies identified
  • Change-management requirements assessed
  • Implementation completed
  • Implementation evidence retained
  • Verification plan completed
  • Effectiveness assessed
  • Risk outcome assessed
  • Control outcome assessed
  • Monitoring outcome assessed
  • Stakeholder outcome reviewed
  • Unintended consequences reviewed
  • Assurance / independent verification completed where required
  • Lessons learned recorded
  • Standardization considered
  • Portfolio impact considered
  • Management review completed where required
  • Closure decision recorded
  • Follow-up requirements established
  • Related AIGO records linked

41. Template Usage Instructions

This template should be completed according to the organization’s approved AIGO Continuous Improvement Procedure. Continuous improvement should address both:
  • correction of identified weaknesses; and
  • proactive improvement of AI governance capability.
Improvement should be driven by evidence and should consider:
  • risk reduction;
  • control effectiveness;
  • operational outcomes;
  • stakeholder outcomes;
  • incidents;
  • monitoring;
  • assurance;
  • changes;
  • management review;
  • technology developments;
  • regulatory developments.
Improvement should not be considered complete merely because an action was performed. The organization should determine whether the intended outcome was achieved. Where an improvement is successful and reusable, the organization should consider standardizing it through:
  • procedures;
  • controls;
  • templates;
  • training;
  • schemas;
  • tools;
  • governance requirements.

42. Template Governance

42.1 Template Owner

Template Owner:

42.2 Template Review

Review Frequency: Next Review Date:

42.3 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:
  • Continuous Improvement Procedure;
  • Management Review;
  • AI Risk Assessment;
  • AI Control Assessment;
  • Monitoring;
  • Incident Management;
  • Change Management;
  • Assurance;
  • Approval;
  • Risk Acceptance;
  • AI System Profile;
  • schemas;
  • mappings;
  • tools.

43. Document Control


44. Template Status

Document: AIGO — AI Continuous Improvement Template Version: 0.1 Status: Draft Working Name: AIGO Full Name: AI Governance Operating Framework Document Identifier: AIGO-TPL-014 Document Type: AI Continuous Improvement Template This template provides the controlled structure for identifying, prioritizing, implementing, verifying, evaluating, standardizing, and closing improvements across the AIGO AI Governance Operating Framework.

45. End of Template

AIGO — AI Continuous Improvement Template Document ID: AIGO-TPL-014 Version: 0.1 Status: Draft End of Template