Risk, Leadership & Resilience
AI governance and assurance advisory
AI governance is not only a policy exercise. It requires clear accountability, risk classification, control design, data governance, human oversight and evidence that decisions are being managed responsibly.
AI governance
AI risk management
ISO/IEC 42001 alignment
EU AI Act awareness
AI GOVERNANCE FRAMEWORK
A Structured Approach to Responsible AI Governance
Common client situations
- AI tools are being adopted before governance responsibilities are clear.
- The organisation needs policy, risk assessment and approval processes for AI use cases.
- Senior management needs visibility of AI risk across business units and vendors.
- Teams need practical controls for data, model, output, human oversight and monitoring.
What the engagement covers
- AI use case inventory and risk classification.
- AI governance policy and operating model design.
- Control mapping to relevant standards and regulatory expectations.
- Vendor and supply chain considerations for AI-enabled services.
- Management reporting and risk acceptance workflow.
Client deliverables
- AI governance framework.
- Use case assessment template.
- AI risk register structure.
- Policy and approval workflow.
- Board or executive briefing pack.
Service boundary
Practical governance for real AI use
Typical phases
FAQs
Everything You Need to Know About Staying Secure
Find answers to common questions about GDPR compliance, DPO-as-a-Service, and data protection.
AI governance consulting services help organizations implement frameworks, policies, and controls to manage AI systems responsibly and securely.
AI governance ensures transparency, accountability, compliance, and risk management for AI systems and business operations.
These services help organizations align with regulations such as the EU AI Act and other global AI compliance standards.
We assess AI systems for risks including bias, data privacy issues, security vulnerabilities, and compliance gaps.
Yes, we help secure AI environments, protect sensitive data, and establish strong data governance practices.
Absolutely. Startups can establish responsible AI practices early and scale securely while meeting compliance expectations.