AI governance

AI is already moving through most organisations. Sometimes it is visible. Sometimes it is hidden inside software, vendor tools, workflows or staff experimentation.

APRA's and ASICs AI governance letters have made one thing clear: named business ownership of AI use cases is now the regulatory minimum. Without it, your organisation is carrying unquantified executive risk.

AI initiatives often stall due to unclear ownership and generic vendor assurances. This article explains why business leaders must own AI risks from the start and demand practical, risk-based evidence from third parties to avoid costly delays.

Many organisations unknowingly inherit significant AI risks through third-party technology and vendor services. Without rigorous independent challenge and clear ownership, vendor assurances fall short. Leaders must demand tailored evidence and embed structured AI risk governance that addresses supply chain complexities and local obligations.

Third-party vendors increasingly embed AI into their services, yet many organisations rely too heavily on vendor assurances without independent verification. Effective AI risk management demands clear ownership, thorough evidence review, and ongoing oversight to meet governance and regulatory expectations.

A practical AI risk governance article focused on AI agents and non-human identity risk, evidence, ownership, challenge and maturity assessment.

A practical AI risk governance article focused on Shadow AI and uncontrolled staff usage, evidence, ownership, challenge and maturity assessment.