Govern capability before dependence becomes exposure
AI Governance
CEREARK helps boards and institutions establish practical AI governance that connects policy, authority, evidence, risk, assurance and operating behaviour.
Review your AI governanceMany AI governance programmes stop at principles, policies or committees. The organisation remains unable to show what AI is used for, who is accountable, what evidence supports it or when intervention is required.
What changes
Outcomes the engagement is designed to support
- Clear AI decision rights and accountability
- Use-case inventory and risk classification
- Evidence-based approval and monitoring
- Defined human authority and escalation thresholds
- Governance that works in delivery rather than only on paper
What the work can include
Core components
- AI governance operating model
- Use-case intake and classification
- Control framework
- Evidence and assurance requirements
- Third-party and model dependency review
- Board and executive reporting
Engagement model
Proportionate to the decision and the risk.
Work can begin with a focused use-case review or a wider enterprise governance design, depending on maturity and risk.
CEREARK does not claim measurable improvement without a defined baseline and evaluation method. Evidence and acceptance criteria are agreed at the outset.
Begin with a consequential question