RYRService · AI Governance
AI governance consulting that turns policy into proof.
We build the operating model, roles and controls that let you show, not just state, that your AI is under control.
The problem
Most organisations have an AI policy. Far fewer can put an operating model on the table: who owns each system, which controls apply, and where the evidence lives.
That gap between 'we have a policy' and 'we can prove control' is exactly what a regulator, a board, or an incident will test first.
Why it matters
Across the UAE and GCC, AI oversight is moving from encouragement to expectation. Boards that cannot evidence governance inherit the liability personally, and delayed decisions quietly become accepted risk.
How the engagement runs
Baseline
Map your AI estate, current policies and decision rights against ISO/IEC 42001 and the NIST AI Risk Management Framework (AI RMF).
Operating model
Design the AI operating model: committee, roles, escalation paths and decision gates.
Controls
Define proportionate controls by risk tier, from documentation to human oversight.
Embed
Stand the model up with your teams and align it to existing GRC and cyber governance.
Prove
Instrument the evidence: registers, records and reporting your board can read at a glance.
What you receive
- AI governance framework: policy, principles and decision rights mapped to a recognised standard.
- Operating model: committee terms, RACI and escalation paths for AI decisions.
- Control set: risk-tiered controls with named owners and evidence requirements.
- Board reporting pack: a one-page view of AI risk and control status for leadership.
Frequently asked questions
How is this different from writing an AI policy?
A policy states intent. Our AI governance services deliver the operating model, controls and evidence that make the policy enforceable and auditable.
Which framework do you align to?
Primarily ISO/IEC 42001 and the NIST AI Risk Management Framework (AI RMF), mapped to your existing cyber and GRC controls so you are not running parallel systems.
Do we need this if we only use third-party AI?
Yes. Procured and embedded AI still creates obligations you must govern: vendor oversight, acceptable use, and monitoring all sit inside the operating model.
How long before we see something usable?
A working operating model and control set typically take eight to twelve weeks, depending on the size of your AI estate.
Will this slow our AI adoption?
The opposite. Clear decision gates let teams ship faster, because approval criteria are known in advance rather than negotiated case by case.
Executive briefing
See what provable AI governance looks like.
A 45-minute briefing, mapped to your estate and your regulators.
Related services
Gap assessment to certification: an AI management system (AIMS) your auditors can verify.
View service Service · Executive Advisory Executive advisory for the people accountable for AI and cyber risk.Discreet board-level counsel on AI and cyber risk: briefings, decision framing and oversight structures.
View serviceRelated insights
Why one AI policy fails, and how layered controls from inventory to oversight prove governance.
AI Governance AI governance frameworks compared: which standard answers which question.ISO/IEC 42001, NIST AI RMF and the EU AI Act, compared by what each is for and how they fit together.