AI governance provides the framework for responsible, compliant, and ethical AI deployment across the enterprise.
## What is AI Governance?
### Core Components - Policy Framework: Rules governing AI development and use - Oversight Mechanisms: Review boards and approval processes - Accountability Structures: Clear ownership and responsibility - Risk Management: Identification and mitigation of AI risks - Compliance: Adherence to regulations and standards
### Why Governance Matters - Prevent harmful outcomes from AI systems - Ensure regulatory compliance (EU AI Act, GDPR, etc.) - Build stakeholder trust and confidence - Manage reputational and financial risk - Enable responsible scaling of AI adoption
## Governance Structure
### AI Governance Board ``` Composition: ├── Chief AI Officer (Chair) ├── Legal / Compliance ├── Risk Management ├── Privacy / Data Protection ├── Business Unit Representatives ├── Technical AI Experts └── Ethics Committee Members ```
### Three Lines of Defense 1. First Line: Business units own AI risk 2. Second Line: Risk and compliance oversight 3. Third Line: Internal audit and assurance
## AI Inventory Management - Catalog all AI systems in production - Document purpose, data sources, and decisions made - Classify by risk level (low/medium/high) - Track model versions and updates - Assign owners and review dates