What is AI Governance?

Explained

AI governance encompasses the policies, processes, and controls that organizations put in place to ensure AI is used responsibly, ethically, and in compliance with regulations. It covers security, cost control, audit trails, and ROI measurement.

Decision guides that use this term

• Microsoft Copilot vs custom AI agents: when is the suite assistant enough, and when do you need your own agents?
• In-house team, AI consultancy or platform: who should build your AI?
• EU AI Act provider vs deployer: which role are you, and what does each one owe?
• Centralised vs federated AI governance: who should decide what in your organisation?

Further reading

• Ethical AI: Building Responsible AI Experiences for Enhanced User Trust

Related terms

• Ethical AI AI designed and deployed with ethical principles (transparency, fairness, privacy).
• ROI Key metric for justifying AI projects.
• Acceptance Criteria Testable conditions that define when a feature or model output is “done” and correct.
• AI Bill of Materials Inventory of model lineage, datasets, dependencies, and licenses for an AI system.
• AI Native Architecture and processes designed from the ground up for AI, not as an afterthought.
• CRM System for managing customer relationships; AI augments it with prediction and automation.