Artificial Intelligence (AI)

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.

AI risk management often focuses on defensive controls, but this mindset limits business value and slows innovation. Leaders must reframe AI risk as a tool to enable success, balancing risk and opportunity through clear ownership, tailored evidence, and ongoing assurance.

OAIC has published its 2026 Australian Community Attitudes to Privacy Survey, showing rising privacy concern, very low trust in AI and stronger expectations for transparency, fairness and complaint handling.

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.

AI risk management is often seen as a defensive exercise, but this mindset limits business value and slows innovation. Leaders must reframe AI risk as a tool to enable success, balancing risk with opportunity through clear ownership, tailored evidence, and ongoing assurance.