Know the use case and consequence
Define what the system does, who depends on it, how it may fail and which decisions remain human.
AI Governance Architecture
Governance should make the next decision possible.
An AI policy cannot approve a live use case by itself. The people responsible must understand its purpose, who may be affected, the potential harm, the limits of the data and technology, where human judgement is available and what evidence shows that a control is working. We turn those questions into an approval route that delivery teams can use.
From policy to practice
A decision architecture for real approvals.
Control design starts with one consequential use case. Its context determines the oversight, evidence and escalation the organisation will need.
Assign authority
Set approval rights, escalation routes, supplier responsibilities and who can stop or change deployment.
Design proportionate controls
Translate policy into review, testing, monitoring and incident procedures suited to the actual risk.
Keep useful evidence
Make the rationale, decisions and results retrievable by the executives and operators accountable for them.
Applicability matters
Regulatory requirements, stated with care.
Applicable UAE privacy and sector requirements inform the design, as does the EU AI Act where a use case falls within its scope. Obligations vary by role, use case, jurisdiction and implementation phase. Specialist legal advice remains with qualified counsel.
Our work supports the organisation's own approval and oversight processes; it is not a legal opinion, regulatory certification or guarantee of compliance.
Who can approve this AI use case?
Bring one decision. We will map the human oversight it needs and the evidence required for approval.