Is your AI governance resilient?
Executive guide to building a model that withstands scrutiny, failure, and scale.
AI is moving from experimentation into the systems, workflows and decisions organisations rely on every day. Recent APRA and ASIC warnings have pushed AI governance onto the board agenda, calling out weaknesses in oversight, AI literacy, cyber resilience and control evidence.
Yet many organisations are still relying on policy-level approaches, disconnected from the controls, decision rights and evidence needed when something goes wrong.
Key takeaways: what you’ll learn
This guide helps leaders understand where AI governance breaks under pressure, and what needs to be in place to make it operational, auditable and defensible.
- Why AI governance is becoming a resilience issue
How regulatory, audit, insurance and board expectations are raising the bar for AI oversight. - Where the confidence and implementation gap is showing up
Why AI policies often fail to translate into clear controls, accountability and evidence. - How to assess governance strain across six dimensions
A practical model for identifying where AI ambition, maturity, complexity and accountability are creating risk. - Why fragmented governance creates systemic exposure
How risks emerge across cyber, privacy, data, compliance, third-party and operational resilience boundaries. - How to move from frameworks to operational reality
What boards and executives need to evidence control, oversight and accountability under pressure.
Build governance that holds up under pressure. Download the full guide now
Access the six interdependent dimensions of Mantel’s AI governance resilience model to shift from fragmented policy to integrated, auditable, and scalable control.
