AI governance and risk management
Every AI system needs an owner.
AI tends to arrive before anyone has decided who is accountable for it. We set out who approves new AI use, how its risk is assessed, and which regulatory requirements apply, then document it so an auditor or board member can follow it.
Governance areas
Regulatory compliance
What the EU AI Act, NIST AI RMF and newer AI regulations mean for the systems you run.
Policy frameworks
AI policies covering acceptable use, data handling and risk management.
Risk management
A consistent way to identify, assess and reduce AI-related risk.
Ethical AI
Establish principles for fair, transparent, and accountable AI development and use.
Stakeholder alignment
Engage leadership, legal, compliance, and technical teams in governance programs.
Training and awareness
AI literacy and governance training for staff, managers and the board.
What an engagement can include
EU AI Act readiness
Risk classification of your AI systems, the documentation the Act asks for, and support preparing for conformity assessment.
NIST AI RMF alignment
Structure your AI risk management around the NIST AI Risk Management Framework: govern, map, measure and manage.
AI policy development
AI use policies, acceptable use guidelines and governance structures written around how your staff actually use AI.
Risk assessment frameworks
A repeatable process for evaluating AI risk across your organization, not a one-off review.
Responsible AI guidelines
Principles on bias, fairness, transparency and accountability that teams can apply to real projects.
Board and executive briefings
Plain-language briefings for leadership on AI risk, opportunity and their governance responsibilities.
How a governance engagement runs
Six steps, from finding out what AI you already use to rolling out the program.
Current state assessment
Evaluate existing AI initiatives, policies, and governance maturity.
Regulatory analysis
Identify applicable AI regulations and compliance requirements.
Risk identification
Catalog AI systems and assess associated risks and impact.
Framework design
Design a governance framework that fits your organization's size and risk profile.
Policy development
Write the AI policies, procedures and supporting documentation.
Implementation support
Guide rollout of governance program with training and change management.
What you get.
Governance framework
An AI governance structure with named roles, responsibilities and decision-making processes.
Policy documentation
AI policies covering acceptable use, risk management and ethics.
Risk assessment tools
Templates and methodologies for ongoing AI risk identification and evaluation.
Compliance roadmap
Action plan for achieving and maintaining compliance with applicable AI regulations.
Start with what AI you already run.
We'll ask which AI tools and models are in use today, which regulations you fall under, and tell you what a governance program would need to cover first.