What is AI Governance?

AI governance is the framework of policies, processes, and controls that organizations use to manage AI systems responsibly. It ensures AI is developed and deployed ethically, safely, and in compliance with regulations.

Why AI Governance Matters

Without governance, AI systems can:

• Produce biased or discriminatory outcomes
• Violate privacy regulations
• Create legal and reputational risks
• Cause harm to users and society

Key Components

AI Policy

Define acceptable use, risk tolerance, and ethical principles for AI in your organization.

Risk Management

Identify, assess, and mitigate AI-specific risks including safety, security, and compliance.

Accountability

Clear ownership and responsibility for AI systems, decisions, and outcomes.

Transparency

Documentation, explainability, and disclosure of AI use to stakeholders.

Implementing AI Governance

• Establish oversight: AI ethics board or governance committee
• Create policies: Acceptable use, data handling, risk thresholds
• Implement controls: Technical safeguards, monitoring, auditing
• Train teams: AI literacy, ethics, and policy awareness
• Monitor continuously: Track compliance and outcomes

Regulatory Landscape

AI governance must account for emerging regulations:

• EU AI Act: Risk-based regulation of AI systems
• NIST AI RMF: US framework for AI risk management
• Industry standards: ISO/IEC 42001 for AI management
• Sector regulations: HIPAA, GDPR, financial services rules

DriftRail for AI Governance

DriftRail provides governance infrastructure:

• Compliance reports for SOC2, GDPR, HIPAA, ISO27001
• Immutable audit logs for accountability
• Risk classification and monitoring
• Guardrails for policy enforcement
• Industry benchmarks for comparison

FAQ