AI Governance Framework
Enterprise AI governance operating model aligned to EU AI Act, ISO 42001 and NIST AI RMF.
Enterprise AI governance is no longer optional. With the EU AI Act in force and regulators globally increasing scrutiny on AI systems, organisations need a structured governance operating model covering risk classification, model documentation, accountability, bias controls and ongoing oversight.
When to Use This Blueprint
- Organisations deploying AI in regulated industries (finance, healthcare, government)
- Pre-EU AI Act compliance assessment and gap remediation
- Building an AI Centre of Excellence with governance requirements
- Board-level AI risk reporting and accountability structures
- Enterprise AI programme with multiple models in production
Architecture Components
AI Model Inventory
Complete register of all AI systems in development and production. EU AI Act risk classification (Unacceptable / High / Limited / Minimal). Ownership, purpose, data lineage.
Risk Classification Framework
EU AI Act tiering, NIST AI RMF risk profiles, sector-specific overlays (financial services, healthcare, public sector).
Accountability Matrix
RACI for AI development, deployment and oversight. Model owner, risk owner, technical owner, ethics reviewer, board sponsor.
Model Documentation Suite
Model cards, system cards, data sheets. Intended use, limitations, performance, fairness evaluation. Regulatory-grade documentation standards.
Bias & Fairness Evaluation
Protected characteristic analysis, disparate impact testing, demographic performance disaggregation. Pre-deployment and continuous evaluation.
Ethics Framework
AI ethics principles, prohibited use cases, human oversight requirements, ethics review process for new AI systems.
Board AI Risk Dashboard
Quarterly AI risk reporting, portfolio performance, compliance status, incident log, model inventory summary.
Ongoing Oversight Process
AI governance committee, quarterly model reviews, annual framework review, incident response protocol.
Decision Framework
Decision: Governance Maturity Target
Decision: Committee Structure
Implementation Phases
Week 1–3
AI Estate Discovery
Full model inventory, risk classification, stakeholder mapping, gap analysis against target framework.
Week 4–7
Framework Design
Governance policy development, accountability matrix, documentation standards, committee structure.
Week 8–11
Implementation
Model documentation, bias evaluation, monitoring setup, dashboard build, training.
Week 12–16
Embedding
Committee launch, board integration, ongoing review cadence, handover to internal governance function.
Governance Controls
Key Metrics to Track
Need Help Implementing This Blueprint?
Our AI architects can design and implement this architecture for your organisation — governance-first, production-grade and aligned to your specific requirements.