AI Governance

The framework of policies, procedures, and controls that organizations implement to ensure AI systems are developed, deployed, and operated responsibly, ethically, and in compliance with regulations.

Also known as:AI Risk ManagementAI Policy Framework

What is AI Governance?

AI Governance encompasses the policies, processes, standards, and organizational structures that guide how artificial intelligence is developed, deployed, monitored, and retired within an organization. It ensures AI systems align with business objectives, ethical principles, legal requirements, and risk tolerance.

Core Components

Policy Framework

  • Acceptable use policies for AI
  • Data governance for AI training
  • Model development standards
  • Deployment and monitoring requirements

Risk Management

  • AI risk assessment methodologies
  • Bias and fairness evaluation
  • Security and privacy controls
  • Incident response procedures

Accountability

  • Clear ownership and responsibilities
  • Audit trails and documentation
  • Performance monitoring
  • Regular reviews and updates

Why AI Governance Matters

As AI becomes more prevalent in business operations, governance ensures:

  • Compliance with emerging regulations (EU AI Act, NIST AI RMF)
  • Protection against reputational and legal risks
  • Consistent quality and reliability of AI outputs
  • Ethical alignment with organizational values

Frequently Asked Questions

Who is responsible for AI governance?

AI governance typically involves cross-functional teams including IT, legal, compliance, data science, and business units, often overseen by a Chief AI Officer or AI Ethics Board.