AI Governance
The frameworks, policies, processes, and organizational structures that guide the responsible development, deployment, and monitoring of AI systems within organizations and across society.
Why It Matters
AI governance is moving from 'nice to have' to mandatory. The EU AI Act and similar regulations require formal governance frameworks for AI systems.
Example
A company establishing an AI review board, maintaining a model inventory, conducting regular bias audits, and implementing incident response procedures for AI failures.
Think of it like...
Like corporate governance but for AI — it is the system of rules, practices, and processes by which AI activities are directed and controlled.
Related Terms
AI Ethics
The study of moral principles and values that should guide the development and deployment of AI systems. It addresses questions of fairness, accountability, transparency, privacy, and the societal impact of AI.
Responsible AI
An approach to developing and deploying AI that prioritizes ethical considerations, fairness, transparency, accountability, and societal benefit throughout the entire AI lifecycle.
AI Regulation
Government rules and legislation governing the development, deployment, and use of artificial intelligence. AI regulation is rapidly evolving worldwide.
Model Governance
The policies, processes, and tools for managing AI models throughout their lifecycle — from development through deployment to retirement. It ensures models remain compliant, fair, and performant.
Compliance
The process of ensuring AI systems meet regulatory requirements, industry standards, and organizational policies. AI compliance is becoming increasingly complex as regulations proliferate.