AI GOVERNANCE FRAMEWORK

[ORGANIZATION NAME]

DOCUMENT CONTROL

1. EXECUTIVE SUMMARY

1.1 Purpose

This AI Governance Framework establishes the structures, processes, roles, and controls for the responsible development, deployment, and management of artificial intelligence systems at [ORGANIZATION NAME].

1.2 Scope

This Framework applies to:
- All AI systems developed, deployed, or used by [ORGANIZATION NAME]
- All personnel involved in AI-related activities
- Third-party AI systems and vendors

1.3 Objectives

1. Ensure AI systems are developed and used responsibly
2. Comply with applicable laws and regulations
3. Manage AI-related risks effectively
4. Build trust with stakeholders
5. Enable innovation within ethical boundaries
6. Align AI activities with organizational values

2. GOVERNANCE STRUCTURE

2.1 Three Lines Model

First Line: Business Operations
- AI system owners and users
- Development and operations teams
- Day-to-day management of AI

Second Line: Oversight Functions
- AI Governance Office
- Risk Management
- Compliance
- Policy and standards setting

Third Line: Independent Assurance
- Internal Audit
- External Auditors
- Independent assessments

2.2 Governance Bodies

2.2.1 Board of Directors / Executive Committee

Responsibilities:
☐ Ultimate accountability for AI governance
☐ Approve AI strategy and policies
☐ Oversee significant AI risks
☐ Review AI governance reports

Frequency: [QUARTERLY/AS NEEDED]

2.2.2 AI Governance Committee

Composition:
| Role | Member | Alternate |
|------|--------|-----------|
| Chair | [TITLE] | [TITLE] |
| Technology | [TITLE] | [TITLE] |
| Legal/Compliance | [TITLE] | [TITLE] |
| Risk | [TITLE] | [TITLE] |
| Business | [TITLE] | [TITLE] |
| Privacy | [TITLE] | [TITLE] |
| Ethics/HR | [TITLE] | [TITLE] |

Responsibilities:
☐ Oversee AI governance framework implementation
☐ Approve high-risk AI systems
☐ Review AI policies and standards
☐ Monitor AI risk posture
☐ Resolve escalated issues
☐ Report to Executive/Board

Frequency: [MONTHLY/QUARTERLY]
Quorum: [NUMBER] members
Decision Authority: [DESCRIBE]

2.2.3 AI Ethics Advisory Board (Optional)

Purpose: Provide independent ethical guidance
Composition: Internal and external ethics experts
Responsibilities:
☐ Advise on ethical dilemmas
☐ Review controversial use cases
☐ Recommend ethical standards

2.3 Key Roles

2.3.1 Chief AI Officer / AI Lead

Responsibilities:
☐ Lead AI strategy and governance
☐ Chair AI Governance Committee
☐ Ensure regulatory compliance
☐ Report to executive leadership
☐ Coordinate across functions

2.3.2 AI Risk Manager

Responsibilities:
☐ Maintain AI risk framework
☐ Conduct/coordinate AI risk assessments
☐ Monitor AI risks
☐ Report on risk posture

2.3.3 AI Ethics Officer

Responsibilities:
☐ Oversee AI ethics program
☐ Review ethical concerns
☐ Develop ethics guidance
☐ Conduct ethics training

2.3.4 AI System Owners

Responsibilities:
☐ Accountable for specific AI systems
☐ Ensure compliance with policies
☐ Manage system-level risks
☐ Maintain documentation

3. AI LIFECYCLE GOVERNANCE

3.1 Lifecycle Phases

[1. Ideation] → [2. Design] → [3. Development] → [4. Testing] → [5. Deployment] → [6. Operation] → [7. Retirement]

3.2 Phase Requirements

Phase 1: Ideation and Planning

Gate Criteria:
☐ Business case documented
☐ Initial risk screening completed
☐ Regulatory classification determined
☐ Resource requirements identified
☐ Stakeholder analysis completed

Required Approvals:
- Low Risk: [APPROVAL LEVEL]
- Medium Risk: [APPROVAL LEVEL]
- High Risk: [APPROVAL LEVEL]

Phase 2: Design

Gate Criteria:
☐ Technical specifications defined
☐ Data requirements documented
☐ Fairness requirements established
☐ Human oversight design completed
☐ Privacy impact assessment initiated

Phase 3: Development

Gate Criteria:
☐ Development standards followed
☐ Data quality verified
☐ Model documentation created
☐ Bias testing conducted
☐ Security requirements implemented

Phase 4: Testing and Validation

Gate Criteria:
☐ Performance requirements met
☐ Fairness metrics satisfied
☐ Security testing completed
☐ User acceptance testing passed
☐ Documentation complete

Phase 5: Deployment

Gate Criteria:
☐ All required approvals obtained
☐ Human oversight implemented
☐ Monitoring configured
☐ Incident response ready
☐ User training completed

Phase 6: Operation and Monitoring

Ongoing Requirements:
☐ Performance monitoring
☐ Drift detection
☐ Incident management
☐ Periodic reviews
☐ Documentation maintenance

Phase 7: Retirement

Gate Criteria:
☐ Retirement plan approved
☐ Stakeholders notified
☐ Data handled per policy
☐ Documentation archived
☐ Lessons learned captured

4. RISK MANAGEMENT

4.1 Risk Categories

4.2 Risk Assessment Requirements

4.3 Risk Appetite

4.4 Risk Escalation

5. POLICY FRAMEWORK

5.1 Policy Hierarchy

[AI Governance Framework]
↓
[AI Policies] (Mandatory requirements)
↓
[AI Standards] (How to comply)
↓
[AI Procedures] (Step-by-step processes)
↓
[AI Guidelines] (Best practices, recommendations)

5.2 Core Policies

5.3 Policy Development Process

1. Need identified
2. Draft developed by owner
3. Stakeholder review
4. Legal/Compliance review
5. AI Governance Committee approval
6. Communication and training
7. Implementation
8. Periodic review

6. COMPLIANCE MANAGEMENT

6.1 Regulatory Landscape

6.2 Compliance Activities

6.3 Compliance Governance

☐ Compliance Officer designated
☐ Regulatory tracking process established
☐ Compliance assessments conducted
☐ Training provided
☐ Documentation maintained

7. AI SYSTEM INVENTORY

7.1 Inventory Requirements

All AI systems must be registered with:
☐ System name and description
☐ Business purpose
☐ Risk classification
☐ Regulatory classification
☐ Data processed
☐ System owner
☐ Deployment status
☐ Key dates

7.2 Inventory Management

8. MONITORING AND ASSURANCE

8.1 Monitoring Framework

8.2 Key Metrics

8.3 Assurance Activities

9. TRAINING AND AWARENESS

9.1 Training Program

9.2 Competency Requirements

10. INCIDENT MANAGEMENT

10.1 AI Incident Definition

An AI incident includes:
- AI system causing harm to individuals
- Significant bias or discrimination discovered
- Major performance failures
- Security breaches involving AI
- Regulatory violations
- Significant stakeholder concerns

10.2 Incident Response

10.3 Incident Classification

11. CONTINUOUS IMPROVEMENT

11.1 Improvement Process

1. Identify improvement opportunities (incidents, audits, feedback)
2. Evaluate and prioritize
3. Plan improvements
4. Implement changes
5. Verify effectiveness
6. Update documentation

11.2 Framework Review

12. DOCUMENTATION REQUIREMENTS

12.1 Required Documentation

12.2 Document Management

☐ Central repository established
☐ Access controls implemented
☐ Version control maintained
☐ Retention schedules followed

13. IMPLEMENTATION ROADMAP

Phase 1: Foundation (Months 1-3)

☐ Governance structure established
☐ Key roles appointed
☐ Core policies drafted
☐ Inventory initiated

Phase 2: Build-Out (Months 4-6)

☐ Policies finalized and approved
☐ Risk framework implemented
☐ Training developed
☐ Monitoring established

Phase 3: Operationalization (Months 7-9)

☐ All systems registered
☐ Assessments completed
☐ Training delivered
☐ Full monitoring operational

Phase 4: Maturation (Ongoing)

☐ Continuous improvement
☐ External benchmarking
☐ Advanced capabilities

APPENDICES

Appendix A: Definitions

[DEFINITIONS OF KEY TERMS]

Appendix B: Policy Index

[INDEX OF ALL AI POLICIES]

Appendix C: Process Flowcharts

[KEY PROCESS DIAGRAMS]

Appendix D: Templates

[LINKS TO GOVERNANCE TEMPLATES]

APPROVAL

This AI Governance Framework template is provided for informational purposes. Organizations should customize based on their specific context and requirements.