Purpose
This framework establishes governance principles, controls, and oversight mechanisms for responsible Artificial Intelligence adoption.
Governance Objectives
- Ethical AI Usage
- Regulatory Compliance
- Risk Management
- Transparency
- Accountability
- Business Value Realization
Governance Structure
AI Steering Committee
Responsibilities:
- Strategic Oversight
- Policy Approval
- Investment Decisions
AI Governance Board
Responsibilities:
- Risk Management
- Ethics Reviews
- Compliance Monitoring
AI Product Owners
Responsibilities:
- Business Outcomes
- Operational Performance
- Model Accountability
Governance Domains
Ethics
Evaluate:
- Fairness
- Bias Management
- Transparency
- Explainability
Risk Management
Evaluate:
- Model Risks
- Operational Risks
- Security Risks
- Regulatory Risks
Data Governance
Evaluate:
- Data Quality
- Data Privacy
- Data Security
- Data Ownership
Compliance
Evaluate:
- Regulatory Requirements
- Industry Standards
- Audit Requirements
KPI Framework
- AI Adoption Rate
- Model Accuracy
- Risk Incidents
- Compliance Findings
- Business Value Generated
Conclusion
Effective AI governance enables organizations to maximize AI value while maintaining trust, compliance, and accountability.