AI Governance and Responsible AI Adoption
Practical AI governance for UK boards. We help you adopt artificial intelligence with the controls, evidence and reporting your regulators, clients and audit committee expect.
What AI governance is
AI governance is the set of policies, controls, accountabilities and reporting arrangements that let an organisation adopt artificial intelligence safely and demonstrably. It is a business responsibility, not a technical one, and it should sit alongside your existing information, risk and data governance frameworks rather than replace them.
ISO/IEC 42001 and standards alignment
ISO/IEC 42001 is the international management system standard for AI. We help organisations build a proportionate AI management system covering scope, leadership, planning, support, operation, evaluation and improvement, aligned with existing ISO 27001 and ISO 9001 arrangements where they exist.
EU AI Act and UK AI regulation
The EU AI Act introduces risk-tiered obligations for AI providers and deployers, with extraterritorial reach for UK firms serving EU customers. The UK's pro-innovation framework relies on sector regulators (FCA, ICO, MHRA, Ofcom) applying existing rules to AI. We translate both into practical controls for your organisation.
AI ethics and responsible AI principles
Fairness, transparency, accountability, safety and human oversight, operationalised as design principles, procurement questions, model-approval criteria and monitoring requirements. AI ethics consulting that produces artefacts, not just posters.
Model and use-case registers
A single source of truth for every AI use case in the organisation, capturing purpose, data, risk classification, owner, approval status, monitoring and retirement plan. Essential for regulatory conversations, audit and board reporting.
Third-party AI and supplier risk
Most AI in the enterprise arrives embedded in third-party products. We strengthen supplier due diligence, contract clauses, model cards, data-processing arrangements, incident notification and exit planning for AI-enabled services.
Board-level AI risk reporting
Concise, decision-focused reporting covering material AI risks, model performance, incidents, regulatory obligations, supplier exposure and progress against the AI roadmap. Designed for audit committees and boards, not data-science leads.