What AI governance actually means
AI governance is the set of arrangements that make an organisation's use of artificial intelligence explainable, accountable and defensible. It answers four questions a board will eventually ask: what AI are we using, who approved it, what happens when it produces a wrong output, and can we show that to a regulator.
The AI frameworks that now apply
ISO/IEC 42001 is the first certifiable management system standard for AI and has become the reference point for organisations wanting an auditable position. The NIST AI Risk Management Framework provides the risk taxonomy. The UAE AI Charter sets national expectations, and organisations with European exposure are also mapping against the EU AI Act. These are complementary rather than competing, and most organisations need a view across all of them.
How CLA Emirates approaches it
We start with an inventory, because almost no organisation has a complete list of the AI already in use, including what has arrived inside purchased software. From there we design the governance framework proportionate to actual risk, establish model documentation and approval routes, and test high-impact systems for bias, drift and explainability. Where certification is the objective, we prepare against ISO/IEC 42001 and support the audit.
What an engagement typically covers
- AI inventory and risk classification
- ISO/IEC 42001 framework and certification readiness
- NIST AI RMF mapping
- Model risk and algorithmic audit
- AI policy and approval routes
- Third-party and embedded AI review
