> ## 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.

# 12 AIGO Improvement Schema Documentation v0.1

# AIGO — Improvement Schema Documentation

## 1. Document Purpose

This document describes the machine-readable AIGO Improvement Schema.

The schema provides the structured representation of continual-improvement activities within the AIGO AI Governance Operating Framework.

It is intended to support:

* improvement identification;
* improvement sources;
* observations and opportunities;
* problem definition;
* root-cause analysis;
* prioritization;
* urgency;
* improvement options;
* action planning;
* implementation;
* change management;
* implementation risk;
* verification;
* effectiveness evaluation;
* risk outcomes;
* control outcomes;
* monitoring outcomes;
* stakeholder outcomes;
* assurance;
* evidence;
* lessons learned;
* standardization;
* portfolio impact;
* closure;
* follow-up;
* management review; and
* traceability.

The JSON schema defines structural requirements.

This documentation explains the intended meaning, governance context, validation expectations, and traceability model for improvement records.

***

## 2. Schema Information

| Field               | Value                                          |
| ------------------- | ---------------------------------------------- |
| Schema              | AIGO Improvement Schema                        |
| Schema Identifier   | `https://aigo.example/schema/improvement/v0.1` |
| Schema Version      | `0.1`                                          |
| JSON Schema Dialect | JSON Schema Draft 2020-12                      |
| Object Type         | `IMPROVEMENT`                                  |
| File                | `12-AIGO-Improvement-Schema-v0.1.json`         |
| Status              | Draft                                          |
| Framework           | AIGO — AI Governance Operating Framework       |

***

## 3. Scope

The Improvement Schema applies to continual-improvement activities arising from AIGO governance and operational processes.

Improvement opportunities may originate from:

* management review;
* risk assessment;
* control assessment;
* assurance;
* audit;
* incident management;
* monitoring;
* change management;
* stakeholder feedback;
* affected-person feedback;
* regulatory developments;
* legal review;
* technology developments;
* model evaluation;
* data assessment;
* supplier review;
* lessons learned;
* maturity assessment; or
* strategic review.

Improvements may address governance, processes, controls, technology, data, models, human oversight, competence, evidence, monitoring, assurance, suppliers, or other AIGO domains.

***

## 4. Object Model

The primary object represented by this schema is:

```text id="3i2t4m" theme={null}
IMPROVEMENT
```

An Improvement record represents a defined opportunity or action intended to improve the suitability, adequacy, effectiveness, resilience, efficiency, or maturity of an AIGO-governed arrangement.

The Improvement record should remain distinct from:

* the source finding or observation;
* the Risk record;
* the Control record;
* the Change record;
* the Assessment record;
* the Assurance record;
* the Management Review record;
* the Evidence record; and
* the Retirement record.

Related records should normally be connected through stable identifiers.

***

## 5. Core Identity

An Improvement record should contain stable identity information.

Key fields include:

* `id`;
* `objectType`;
* `objectVersion`;
* `schemaVersion`;
* improvement title;
* source;
* objective;
* owner; and
* status.

Example:

```json id="a9x7pv" theme={null}
{
  "id": "IMPROVE-001",
  "objectType": "IMPROVEMENT",
  "objectVersion": "1.0",
  "schemaVersion": "0.1",
  "status": "OPEN"
}
```

The improvement identifier should remain stable throughout the improvement lifecycle.

A materially separate improvement should normally receive a new identifier.

***

## 6. Improvement Purpose

The improvement record should clearly state what is intended to change or improve.

The objective should explain:

* the current condition;
* the desired condition;
* the reason improvement is needed;
* the expected benefit;
* the governance significance; and
* the intended measurable or observable outcome.

An objective should be sufficiently specific to support later verification.

***

## 7. Improvement Sources

An improvement may originate from one or more governance sources.

The schema supports source categories including:

```text id="e7q0u1" theme={null}
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
```

The exact enumeration defined in the JSON schema is authoritative.

Where multiple sources contribute to the same improvement, they should all be traceable.

***

## 8. Source Record Relationships

The improvement should reference the records that generated the improvement opportunity.

Examples include:

```text id="f7izt9" theme={null}
INC-004
ASSURE-003
RISK-002
CTRL-005
MGMTREV-002
MON-007
```

The source record remains authoritative for the original observation, finding, incident, or decision.

The Improvement record captures the resulting improvement lifecycle.

***

## 9. Current Condition

The record should describe the condition that currently exists.

Examples include:

* incomplete governance coverage;
* ineffective control;
* outdated procedure;
* excessive incident rate;
* insufficient monitoring;
* inadequate evidence;
* recurring assessment findings;
* regulatory gap;
* capability weakness; or
* another documented condition.

The current condition should be evidence-based where possible.

***

## 10. Desired Condition

The desired condition should describe what success looks like after the improvement.

The desired condition may include:

* stronger control effectiveness;
* reduced risk;
* improved monitoring coverage;
* improved evidence quality;
* reduced incident recurrence;
* improved stakeholder outcomes;
* improved governance maturity;
* improved compliance; or
* another defined outcome.

The desired condition should be capable of later verification.

***

## 11. Problem Statement

Where the improvement addresses a defined problem, the problem statement should identify:

* what is wrong;
* why it matters;
* who or what is affected;
* evidence supporting the problem; and
* consequences of not addressing it.

A concise problem statement helps prevent improvement activities from becoming solutions without a clearly understood problem.

***

## 12. Opportunity Statement

Not all improvements arise from failures.

An improvement may represent an opportunity to:

* improve efficiency;
* simplify governance;
* strengthen resilience;
* improve assurance;
* enhance transparency;
* improve user experience;
* reduce unnecessary risk;
* adopt better technology;
* improve sustainability; or
* increase governance maturity.

Opportunity-based improvements should have an explicit rationale.

***

## 13. Root-Cause Analysis

Where an improvement is driven by a deficiency or recurring problem, root-cause analysis should be considered.

The schema supports:

* primary cause;
* cause category;
* confidence;
* analysis method; and
* analysis narrative.

Potential root-cause categories include:

* governance;
* process;
* procedure;
* control;
* risk management;
* monitoring;
* assurance;
* incident;
* change management;
* data;
* model;
* technology;
* human;
* training;
* supplier; and
* regulatory.

Root-cause analysis should distinguish validated causes from hypotheses.

***

## 14. Contributing Causes

Multiple contributing causes may exist.

Examples include:

* unclear ownership;
* insufficient competence;
* incomplete requirements;
* inadequate tooling;
* weak evidence;
* poor system integration;
* insufficient testing;
* supplier limitations;
* process complexity; or
* resource constraints.

Contributing causes should be recorded where they materially affect treatment or recurrence.

***

## 15. Improvement Type

The schema supports classification of improvement activities.

Possible categories include:

```text id="k0c4sp" theme={null}
GOVERNANCE
RISK_MANAGEMENT
CONTROL
MONITORING
ASSURANCE
INCIDENT
CHANGE_MANAGEMENT
PROCESS
PROCEDURE
DOCUMENTATION
EVIDENCE
TECHNOLOGY
DATA
MODEL
HUMAN_OVERSIGHT
TRAINING_CAPABILITY
SUPPLIER
REGULATORY_COMPLIANCE
STRATEGIC
OTHER
```

The authoritative enumeration in the JSON schema is controlling.

Improvement type should support reporting and prioritization.

***

## 16. Improvement Owner

Every active improvement should have an accountable owner.

The owner is responsible for:

* defining the improvement;
* coordinating prioritization;
* obtaining approvals;
* assigning actions;
* monitoring progress;
* ensuring implementation;
* arranging verification;
* evaluating effectiveness; and
* closing the improvement.

Action execution may be delegated.

Accountability should remain explicit.

***

## 17. Sponsor and Action Owner

The schema may distinguish:

* improvement owner;
* sponsor;
* action owner;
* reviewer; and
* approval authority.

This is useful where improvements are cross-functional or strategically significant.

Roles should be aligned with the organization's governance structure.

***

## 18. Improvement Lifecycle

A typical improvement lifecycle is:

```text id="l8y5ra" theme={null}
Opportunity Identified
        ↓
Problem / Opportunity Defined
        ↓
Root Cause
        ↓
Prioritization
        ↓
Option Analysis
        ↓
Objective
        ↓
Action Plan
        ↓
Approval
        ↓
Implementation
        ↓
Verification
        ↓
Effectiveness Evaluation
        ↓
Standardization
        ↓
Closure
        ↓
Follow-Up
```

The actual lifecycle should follow the applicable AIGO continual-improvement process.

***

## 19. Improvement Status

The schema supports controlled improvement status.

Typical conceptual states include:

```text id="s3x9de" theme={null}
IDENTIFIED
PROPOSED
UNDER_REVIEW
APPROVED
PLANNED
IN_PROGRESS
BLOCKED
IMPLEMENTED
VERIFICATION
EFFECTIVE
PARTIALLY_EFFECTIVE
INEFFECTIVE
CLOSED
DEFERRED
CANCELLED
REOPENED
```

The exact status values defined in the JSON schema are authoritative.

Status indicates lifecycle state and does not independently establish authorization.

***

## 20. Priority

Improvement priority should reflect governance significance.

Priority may consider:

* risk reduction;
* regulatory significance;
* control criticality;
* affected-person scale;
* urgency;
* strategic importance;
* cost;
* feasibility; and
* organizational capacity.

The priority should have an explicit rationale.

***

## 21. Urgency

Urgency should distinguish whether action is:

* immediate;
* near-term;
* planned; or
* long-term.

Time-sensitive improvements should identify relevant deadlines.

An improvement may be high priority but not immediately executable due to dependencies or resource constraints.

***

## 22. Option Analysis

Where more than one approach is possible, the improvement record may compare options.

Options may be assessed against:

* effectiveness;
* risk reduction;
* cost;
* feasibility;
* dependencies;
* implementation complexity;
* unintended consequences;
* sustainability; and
* strategic alignment.

Option analysis is particularly useful for significant governance improvements.

***

## 23. Selected Option

Where alternatives were assessed, the selected option should identify:

* selected option;
* rationale;
* decision authority; and
* decision date where applicable.

The selection should remain traceable to the alternative options considered.

***

## 24. Improvement Objective

The objective is the central statement of intended improvement.

A strong objective should identify:

* desired outcome;
* affected area;
* expected benefit;
* relevant constraints;
* target timeframe; and
* success criteria.

The objective should be specific enough to support effectiveness assessment.

***

## 25. Success Criteria

Success criteria define how the organization will determine whether the improvement worked.

Criteria may include:

* risk reduction;
* control effectiveness;
* process performance;
* monitoring performance;
* incident reduction;
* evidence quality;
* stakeholder outcome;
* compliance status;
* maturity improvement;
* operational performance; or
* other measurable outcomes.

Success criteria should be established before implementation where practical.

***

## 26. Action Plan

An improvement may contain multiple actions.

Each action should identify, where applicable:

* action identifier;
* action description;
* action type;
* owner;
* dependency;
* priority;
* target date;
* status; and
* completion evidence.

Action types may include:

* correction;
* corrective action;
* preventive action;
* control change;
* process change;
* procedure change;
* technical change;
* documentation change;
* training;
* monitoring; and
* assurance.

***

## 27. Resources

Improvements should consider required resources.

Resources may include:

* people;
* technology;
* budget;
* expertise;
* training;
* external support;
* infrastructure; and
* management attention.

Insufficient resources should be treated as an explicit dependency or risk rather than hidden within the plan.

***

## 28. Dependencies

Improvements may depend on:

* approvals;
* projects;
* technology;
* supplier action;
* governance decisions;
* data;
* staffing;
* training;
* other improvements; or
* related changes.

Dependencies should have identifiable owners and status.

A blocked dependency may affect the target completion date.

***

## 29. Improvement Implementation

Implementation should document:

* status;
* start date;
* completion date;
* activities completed;
* issues;
* blockers;
* deviations; and
* implementation evidence.

The implementation should remain aligned with the approved objective and action plan.

***

## 30. Implementation Deviations

A deviation may occur when implementation differs from the approved plan.

Material deviations should identify:

* deviation;
* impact;
* owner;
* escalation;
* approval where required; and
* evidence.

A material deviation may require reassessment or change management.

***

## 31. Change Management Relationship

An improvement may require changes to:

* AI systems;
* models;
* data;
* controls;
* monitoring;
* procedures;
* governance;
* infrastructure;
* suppliers; or
* business processes.

Where change-management requirements apply, the Improvement record should reference the Change record.

The Change Schema remains authoritative for formal change governance.

***

## 32. Implementation Risk

Improvement implementation may create temporary or new risks.

The record may identify:

* implementation risks;
* risk levels;
* treatments;
* owners;
* temporary risk; and
* mitigating controls.

Implementation risk should be managed separately from the original problem or opportunity.

***

## 33. Verification

Verification determines whether the improvement was implemented as intended.

Verification may use:

* evidence review;
* testing;
* control assessment;
* monitoring;
* independent validation;
* assurance;
* interview;
* observation; or
* performance comparison.

The verification plan should identify:

* objective;
* methods;
* owner;
* date;
* criteria; and
* expected evidence.

***

## 34. Effectiveness Evaluation

Effectiveness evaluation determines whether the improvement achieved its intended outcome.

Possible outcomes include:

```text id="5uh5f0" theme={null}
EFFECTIVE
PARTIALLY_EFFECTIVE
INEFFECTIVE
NOT_YET_DETERMINED
```

The exact enumeration defined in the JSON schema is authoritative.

Effectiveness should be evaluated against the success criteria established for the improvement.

***

## 35. Unintended Consequences

An improvement may produce unexpected effects.

The effectiveness evaluation should consider:

* new risks;
* control degradation;
* stakeholder impacts;
* operational disruption;
* new incidents;
* increased complexity;
* unintended bias; or
* other undesirable outcomes.

Unintended consequences may require additional improvement, risk treatment, or change.

***

## 36. Sustainability

Effectiveness should consider whether the improvement is sustainable.

Sustainability may depend on:

* ownership;
* resources;
* competence;
* documentation;
* monitoring;
* control integration;
* maintenance;
* technology support; and
* organizational adoption.

An improvement that works temporarily but cannot be sustained should not automatically be considered fully effective.

***

## 37. Risk Outcome

Where the improvement addresses risk, the record may capture:

* risk before;
* risk after;
* risk reduction;
* residual risk;
* risk acceptance requirements; and
* associated risk-acceptance record.

The objective is to demonstrate whether the improvement materially affected risk.

***

## 38. Control Outcome

Where the improvement affects controls, the record may compare:

* control condition before;
* control condition after;
* control effectiveness;
* result; and
* rationale.

Possible outcomes include:

```text id="d1xgk7" theme={null}
IMPROVED
PARTIALLY_IMPROVED
UNCHANGED
DETERIORATED
```

A deterioration should trigger appropriate governance response.

***

## 39. Monitoring Outcome

An improvement may affect monitoring requirements.

The record may compare:

* indicator values before;
* indicator values after;
* targets;
* thresholds;
* monitoring status; and
* overall monitoring result.

Improvement may require permanent monitoring changes or temporary enhanced monitoring.

***

## 40. Stakeholder Outcome

Improvements should consider the effect on relevant stakeholders.

Outcomes may include:

* positive feedback;
* negative feedback;
* affected-person outcomes;
* complaint changes;
* improved usability;
* reduced harm;
* unintended consequences; or
* no material change.

Where stakeholder engagement is required, the record should reference relevant engagement records.

***

## 41. Assurance Relationship

An improvement may require independent assurance where:

* the improvement is high significance;
* effectiveness is difficult to demonstrate;
* regulatory requirements require assurance;
* previous remediation failed;
* the improvement addresses a critical control; or
* management requests independent validation.

The Assurance Schema remains authoritative for the assurance activity.

***

## 42. Evidence

Improvement evidence may demonstrate:

* the original problem;
* root cause;
* approval;
* implementation;
* completion;
* verification;
* effectiveness;
* risk reduction;
* control improvement;
* stakeholder outcome; and
* closure.

Evidence should be independently represented through the Evidence Schema where appropriate.

***

## 43. Evidence Completeness

The improvement record may identify whether required evidence is:

* complete;
* substantially complete;
* partially complete; or
* incomplete.

Evidence gaps should be explicitly documented.

An improvement should not be declared fully effective when material evidence gaps prevent reliable verification.

***

## 44. Lessons Learned

Improvements should capture lessons learned where they have broader governance relevance.

Lessons may concern:

* governance;
* technology;
* process;
* controls;
* risk;
* monitoring;
* assurance;
* implementation;
* stakeholder engagement; or
* organizational capability.

Lessons learned may generate additional improvements.

***

## 45. Standardization

An improvement that proves effective may be considered for wider standardization.

Standardization decisions may be:

```text id="b1w5fs" theme={null}
STANDARDIZE
PILOT_FIRST
LOCAL_ONLY
DO_NOT_STANDARDIZE
PENDING
```

The decision should consider:

* applicability;
* evidence of effectiveness;
* dependencies;
* risk;
* cost;
* organizational context; and
* scalability.

Standardization may require changes to:

* templates;
* procedures;
* controls;
* guidance;
* training; and
* schemas.

***

## 46. Portfolio Impact

An improvement may affect more than one AI system or governance area.

Portfolio impact may include:

* other AI systems affected;
* enterprise impact;
* portfolio action;
* common controls;
* shared technology;
* shared procedures; and
* portfolio owner.

Portfolio-wide improvements may produce greater governance value than isolated local changes.

***

## 47. Improvement Review

Improvements should be reviewed periodically when:

* implementation is prolonged;
* dependencies change;
* risk changes;
* scope changes;
* expected benefits change;
* target dates are missed; or
* effectiveness remains uncertain.

Review should determine whether the improvement should:

* continue;
* be reprioritized;
* be modified;
* be deferred;
* be cancelled; or
* be escalated.

***

## 48. Management Review Relationship

Significant improvements should be available to management review.

Management may consider:

* major improvements;
* overdue actions;
* improvement trends;
* strategic impact;
* resource requirements;
* risk reduction;
* recurring issues; and
* improvement effectiveness.

Management review may create new improvement actions or change priorities.

***

## 49. Improvement and Risk Management

The improvement-to-risk relationship may be:

```text id="4xehq9" theme={null}
Risk / Finding
      ↓
Improvement
      ↓
Treatment
      ↓
Verification
      ↓
Residual Risk
```

The improvement record should demonstrate whether the intended risk outcome was achieved.

The Risk record remains authoritative for the enduring risk state.

***

## 50. Improvement and Controls

Improvements may:

* introduce new controls;
* modify controls;
* retire controls;
* strengthen control effectiveness;
* improve evidence; or
* improve monitoring.

Control changes should follow the applicable control and change-management processes.

***

## 51. Improvement and Incidents

Incidents are an important improvement source.

The relationship may be:

```text id="x7pn18" theme={null}
Incident
    ↓
Root Cause
    ↓
Improvement
    ↓
Corrective / Preventive Action
    ↓
Verification
```

The Incident record remains authoritative for incident investigation and closure.

The Improvement record manages the broader change needed to prevent recurrence or improve governance.

***

## 52. Improvement and Assurance

Assurance findings may produce improvements.

The relationship may be:

```text id="9z9o9c" theme={null}
Assurance Finding
       ↓
Improvement
       ↓
Corrective Action
       ↓
Verification
       ↓
Assurance Follow-Up
```

This provides a clear feedback loop between assurance and continual improvement.

***

## 53. Improvement and Monitoring

Monitoring may reveal an improvement opportunity through:

* deteriorating performance;
* repeated threshold breaches;
* ineffective indicators;
* increasing incidents;
* increased risk;
* stakeholder dissatisfaction; or
* monitoring gaps.

Monitoring evidence should remain traceable to the improvement source.

***

## 54. Improvement and Change

An improvement may be implemented through one or more Change records.

The relationship may be:

```text id="ckcxqg" theme={null}
Improvement
    ↓
Change
    ↓
Implementation
    ↓
Verification
    ↓
Effectiveness
```

A Change record remains authoritative for formal change authorization and execution.

***

## 55. Improvement Closure

An improvement should be closed only when the applicable closure criteria are satisfied.

Closure may require:

* objective achieved;
* actions complete;
* verification complete;
* effectiveness determined;
* evidence complete;
* outstanding risks addressed;
* required approvals complete;
* lessons learned captured; and
* follow-up assigned where required.

Possible closure states include:

```text id="2pcxl8" theme={null}
CLOSED
CLOSED_WITH_FOLLOW_UP
DEFERRED
REOPENED
CANCELLED
```

The exact schema enumeration is authoritative.

***

## 56. Reopening an Improvement

An improvement may need to be reopened when:

* effectiveness was overstated;
* unintended consequences emerge;
* the original problem recurs;
* implementation fails;
* new evidence changes the conclusion; or
* the improvement is found to be unsustainable.

Reopening should preserve the original closure history.

***

## 57. Improvement Reporting

Improvement records may support governance reporting.

Useful metrics include:

| Metric                           | Purpose                 |
| -------------------------------- | ----------------------- |
| Improvements identified          | Improvement pipeline    |
| Improvements by source           | Source analysis         |
| Improvements by priority         | Prioritization          |
| Improvements overdue             | Delivery performance    |
| Improvements blocked             | Dependency exposure     |
| Improvements completed           | Delivery                |
| Improvements effective           | Effectiveness           |
| Partially effective improvements | Follow-up               |
| Ineffective improvements         | Governance weakness     |
| Repeat improvements              | Recurring problems      |
| Standardized improvements        | Organizational learning |

Metrics should have controlled definitions and reporting periods.

***

## 58. Improvement Validation Requirements

A valid Improvement record should satisfy:

### Structural Validation

The JSON document must validate against:

`12-AIGO-Improvement-Schema-v0.1.json`

### Source Validation

The improvement source should be identifiable.

### Objective Validation

A clear objective should be defined.

### Ownership Validation

An accountable owner should be assigned.

### Priority Validation

Priority should have an appropriate rationale for significant improvements.

### Action Validation

Required actions should have owners and target dates.

### Dependency Validation

Material dependencies should be identified.

### Risk Validation

Implementation risks should be considered where appropriate.

### Verification Validation

The improvement should have a defined verification approach when verification is required.

### Effectiveness Validation

Effectiveness should be evaluated against defined criteria.

### Evidence Validation

Material effectiveness claims should have sufficient evidence.

### Closure Validation

Closure should satisfy the applicable closure criteria.

### Traceability Validation

The improvement should remain traceable to its source, related risks, controls, assessments, incidents, changes, assurance, evidence, management reviews, and other related records.

***

## 59. Schema Limitations

JSON Schema cannot independently determine:

* whether an improvement is genuinely needed;
* whether root cause is correct;
* whether the selected option is appropriate;
* whether implementation is effective;
* whether risk reduction actually occurred;
* whether stakeholder outcomes improved;
* whether standardization is justified; or
* whether closure is appropriate.

These matters require governance judgment, evidence, implementation controls, monitoring, and assurance.

***

## 60. Relationship to Templates

The Improvement Schema corresponds primarily to:

`guidance/03-templates/14-AIGO-AI-Continuous-Improvement-Template-v0.1.md`

It also supports improvement records generated from:

* management review;
* risk assessment;
* control assessment;
* monitoring;
* incident management;
* change management;
* assurance;
* evidence review;
* maturity assessment; and
* other AIGO governance activities.

The Markdown template provides the human-readable improvement record.

The JSON schema provides the machine-readable structure.

***

## 61. Relationship to Procedures

The schema should be used with:

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

and, where applicable:

* governance;
* risk assessment;
* control assessment;
* approval;
* monitoring;
* incident management;
* change management;
* assurance;
* management review;
* risk acceptance; and
* retirement procedures.

The procedure defines how improvements are identified, prioritized, implemented, verified, evaluated, standardized, and closed.

***

## 62. Framework Traceability

| AIGO Component          | Relationship                                      |
| ----------------------- | ------------------------------------------------- |
| Governance Domains      | Defines areas in which improvements may arise     |
| Governance Roles        | Defines improvement ownership and authority       |
| AI Governance Lifecycle | Provides lifecycle improvement context            |
| AI Risk Management      | Provides risk-reduction objectives                |
| AI Governance Controls  | Provides control-improvement relationships        |
| AI Governance Maturity  | Provides maturity gaps and improvement priorities |
| AI System Profiles      | Identifies affected AI systems                    |
| Implementation Guidance | Defines improvement implementation expectations   |
| Operational Procedures  | Defines continual-improvement workflow            |
| Templates               | Provides human-readable improvement records       |
| External Mappings       | Provides regulatory and standards context         |

***

## 63. Improvement Traceability Model

The recommended traceability chain is:

```text id="q8l6a2" theme={null}
Source / Observation / Finding
             ↓
Problem or Opportunity
             ↓
Root Cause
             ↓
Improvement Objective
             ↓
Action Plan
             ↓
Implementation
             ↓
Verification
             ↓
Effectiveness
             ↓
Standardization
             ↓
Closure
```

The improvement should maintain additional relationships to:

```text id="x3d8bl" theme={null}
AI System
Risk
Control
Assessment
Approval
Monitoring
Incident
Change
Assurance
Evidence
Management Review
Retirement
```

This supports end-to-end continual-improvement traceability.

***

## 64. Example Record

A conceptual Improvement record may look like:

```json id="4ayf7q" theme={null}
{
  "id": "IMPROVE-001",
  "objectType": "IMPROVEMENT",
  "objectVersion": "1.0",
  "schemaVersion": "0.1",
  "status": "IN_PROGRESS",
  "improvementTitle": "Strengthen monitoring of high-risk AI systems",
  "improvementType": "MONITORING",
  "owner": {
    "role": "AI Monitoring Owner"
  },
  "source": {
    "sourceType": "MANAGEMENT_REVIEW",
    "description": "Management review identified inconsistent enhanced-monitoring practices."
  },
  "objective": "Establish consistent enhanced-monitoring requirements for high-risk AI systems.",
  "successCriteria": [
    "All in-scope high-risk AI systems have documented enhanced-monitoring criteria.",
    "Thresholds and escalation requirements are defined.",
    "Implementation is verified through evidence."
  ],
  "relatedAiSystemIds": [
    "AI-SYS-001",
    "AI-SYS-002"
  ],
  "relatedControlIds": [
    "CTRL-010"
  ],
  "actionPlan": [
    {
      "actionId": "ACTION-001",
      "action": "Define enhanced-monitoring criteria.",
      "owner": {
        "role": "AI Monitoring Owner"
      },
      "status": "IN_PROGRESS"
    }
  ]
}
```

The actual record must conform to the authoritative JSON schema.

***

## 65. Schema Registry Relationship

This schema is registered in:

`schemas/00-AIGO-Schema-Registry-v0.1.json`

The registry should maintain:

* schema identifier;
* object type;
* version;
* controlled path;
* status;
* dependencies;
* referenced schemas;
* owner;
* documentation path; and
* traceability metadata.

***

## 66. Change and Version Management

Changes to the Improvement Schema should be managed through AIGO change management.

Potential impacts should be assessed against:

* continual-improvement procedures;
* improvement templates;
* management review;
* risk management;
* control management;
* monitoring;
* incident management;
* change management;
* assurance;
* evidence;
* reporting;
* standardization;
* external mappings; and
* validation tooling.

Breaking changes should include migration guidance where necessary.

***

## 67. Future Extensions

Future versions may support:

* improvement portfolio management;
* benefits realization;
* formal cost-benefit analysis;
* improvement dependency graphs;
* automated prioritization;
* improvement maturity scoring;
* organization-wide standardization;
* learning repositories;
* automated effectiveness analytics;
* benefit monitoring;
* policy-to-improvement traceability; and
* machine-readable improvement workflows.

Extensions should preserve stable improvement identity, evidence traceability, effectiveness verification, and historical closure records.

***

## 68. Document Control

| Field               | Value                                  |
| ------------------- | -------------------------------------- |
| Document            | AIGO Improvement Schema Documentation  |
| Version             | 0.1                                    |
| Status              | Draft                                  |
| Document Identifier | `AIGO-SCHEMA-DOC-012`                  |
| Document Type       | Schema Documentation                   |
| Schema              | `12-AIGO-Improvement-Schema-v0.1.json` |
| Owner               |                                        |
| Technical Reviewer  |                                        |
| Governance Reviewer |                                        |
| Approved By         |                                        |
| Effective Date      |                                        |
| Next Review Date    |                                        |

***

## 69. Document Status

**Document:** AIGO — Improvement Schema Documentation

**Version:** 0.1

**Status:** Draft

**Working Name:** AIGO

**Full Name:** AI Governance Operating Framework

**Document Identifier:** `AIGO-SCHEMA-DOC-012`

**Document Type:** Schema Documentation

This document provides the human-readable interpretation, governance context, validation expectations, and traceability guidance for the AIGO Improvement Schema.

End of Document