Risk classification
AI uses tiered by impact, with the checks each tier must pass before release.
Service offering
Responsible AI governance
Rules that decide which AI uses are allowed, how they are tested and who answers for them.
We set up the governance that decides which AI uses are allowed and how they are checked: a risk classification, model cards, bias and robustness testing, and human review where decisions affect people. We align it with published guidance, such as national AI ethics guidance in the UAE and the SDAIA AI ethics principles in Saudi Arabia, as context for your own policy.
For health uses, the framework also covers the UAE law on the use of ICT in health fields (Federal Law No. 2 of 2019) and SFDA guidance on AI-based medical devices in Saudi Arabia.
What the engagement covers
Model documentation
Model cards recording purpose, data, limits, test results and the accountable owner.
Testing and oversight
Bias, robustness and red-team tests, plus human review and rollback criteria for high-impact uses.
Data protection by design
Personal and sensitive data classified and access-controlled from the first pipeline.
Ownership and quality
Named data owners and quality checks, so issues are fixed at source rather than in reports.
When AI governance cannot wait
It cannot wait once AI moves from experiments into decisions that affect customers, patients or staff.
- Teams use AI tools without an agreed list of allowed uses.
- A model influences decisions about people and has no named owner.
- Nobody can show how a model was tested for bias.
Talk to us about responsible AI governance
Tell us what you need to achieve and by when. We will propose a scope, a team and an itemised quotation.