AI Governance Framework
Govern the responsible, accountable development and use of AI.
Methodology
Governance model covering AI inventory, risk tiering, approval gates, model oversight, human accountability and monitoring.
Components
AI inventory & tiering; Approval & gating; Model oversight; Human accountability; Policy & standards; Monitoring & audit.
Governance
Board approves AI policy; AI governance committee; model owners; second-line AI risk; audit assures. L1 Initial L2 Developing L3 Defined L4 Managed L5 Optimised Ad hoc Basic, siloed Standardised & Quantified & integrated Predictive & embedded governed
Maturity levels
Implementation roadmap
Diagnose (assess maturity) → Design (tailor framework & governance) → Build (policies, standards, controls, pipelines) → Embed (training, culture, adoption) → Assure (test, benchmark, re-score).
Deliverables
Framework document, governance & RACI, policy/standard templates, maturity score & roadmap, board reporting pack.
Advisory opportunities
AI governance build; AI policy & committee; Model oversight enablement.
Across the Data & AI ecosystem
Knowledge graph · 11 relations