AI Governance: Building Business-Specific Contextual Intelligence
How to implement AI governance that balances innovation with risk management. Frameworks for business-specific contextual decision-making.
Why AI Governance Matters Now
As AI systems make more consequential decisions, governance becomes critical. Without proper oversight, AI can amplify biases, violate privacy, and create legal liability.
But governance isn't about stopping innovation—it's about innovating responsibly.
The Contextual Intelligence Approach
Effective AI governance requires business-specific context. Generic frameworks fail because:
- Industries have different risk profiles
- Use cases vary in stakes and sensitivity
- Organizational culture affects adoption
Building Contextual Governance
**1. Risk Assessment by Use Case**
Not all AI applications need the same oversight:
| Risk Level | Examples | Governance |
|------------|----------|------------|
| Low | Content recommendations | Light monitoring |
| Medium | Customer service bots | Regular audits |
| High | Credit decisions, hiring | Heavy oversight, human review |
| Critical | Medical diagnosis | Regulatory compliance, extensive testing |
**2. Industry-Specific Considerations**
- **Financial services**: Fair lending, explainability requirements