Practice guide
AI governance
AI governance is how an organisation directs, oversees and controls its use of AI. Done well, artificial intelligence governance turns responsible AI from a slogan into an operating model — with a real AI policy behind it.
The basics
What is AI governance?
Governance drives AI compliance
Strong AI governance is the foundation of AI compliance with the EU AI Act and ISO 42001. Without it, compliance becomes a scramble every time a new model ships.Direction and oversight
Artificial intelligence governance sets who decides, who is accountable, and how AI decisions are reviewed across the lifecycle.
Responsible AI in practice
Responsible AI means fairness, transparency and safety are designed in — not bolted on after an incident.
From principles to policy
A written AI policy (or artificial intelligence policy) turns high-level values into rules people can actually follow.
The building blocks of AI governance
Accountability
Clear roles and an oversight body for AI decisions.
AI policy
Acceptable use, review gates and documentation standards.
Risk controls
Governance connected to AI risk management and monitoring.
Transparency
Explainability and disclosure that satisfy responsible AI expectations.
Where to next
Connect governance to the rules
EU AI Act
Governance is how you meet AI Act obligations in practice.
ISO 42001
A certifiable AI management system built on governance.
AI risk management
The risk engine your governance model steers.
AI governance FAQs
What is AI governance?
The framework of roles, policies and controls that direct and oversee an organisation’s use of AI.
What is responsible AI?
An approach that builds fairness, transparency, safety and accountability into AI systems by design.
Do we need an AI policy?
Yes. An AI policy translates governance principles into concrete rules and is a common first ask in an AI compliance review.
Stand up AI governance that holds.
Build your framework and AI policy in a hands-on workshop.