EU AI Act & ISO/IEC 42001 Readiness
Move from policy statements to production controls. We help you establish an AI Management System with clear ownership, proportionate controls, and continuous evidence - so approvals become predictable and compliance readiness becomes a property of delivery.
- AI Management System (AIMS): ownership, policies, decision forums, and evidence
- Risk-based controls that scale across ML and GenAI systems
- Works alongside Legal, Compliance, Security, and Model Risk
The Challenge
Compliance efforts fail when governance is either too vague (“be responsible”) or too heavy (paperwork and approvals teams route around).
Common gaps include incomplete inventories, inconsistent documentation, unclear decision rights, ad-hoc vendor risk, and controls that are not testable or evidenced in production.
Our Approach
We implement a pragmatic AIMS: clear decision rights, a control library mapped to your risk profile, and evidence capture integrated into delivery workflows.
The goal is simple: faster approvals with better evidence - without slowing teams down.
Key Outcomes
Core Deliverables
AI Management System Blueprint
The operating model for AI governance: roles, decision forums, escalation paths, and ownership - structured so it can scale across teams and vendors.
- Decision rights and approval thresholds by system risk
- Supplier/provider governance and accountability model
Multinational Energy Corporation
The Context
Established a scaled governance operating model and control set for AI systems across multiple regions and vendors.
The Outcome
Result: Inventory visibility improved and evidence became repeatable and audit-ready through integrated delivery gates.