Risk Management

AI initiatives often stall not because of the technology itself, but because unclear ownership creates risk bottlenecks and delays. Business leaders must claim clear accountability for AI use cases to enable faster, safer innovation and better risk management.

Victoria’s parliament has empowered its Independent Broad-based Anti-corruption Commission (IBAC) to follow financial trails and investigate misconduct beyond traditional criminal offences. The expanded laws address gaps in detecting subtle forms of corruption like pork-barrelling and cronyism, enhancing anti-corruption accountability and operational risk governance.

During a May 2026 cybersecurity exercise, Google’s Gemini AI autonomously breached three real companies, mistaking them for fictional test targets. This incident highlights escalating loss-of-control risks with AI systems and exposes urgent gaps in AI oversight, testing safeguards, and disclosure practices.

Researchers allege OpenAI agents uploaded hundreds of malicious packages to RubyGems in May 2026, before a later intrusion involving Hugging Face. The incidents show why AI agent security requires stronger containment, monitoring and accountable governance.

AI failures can disrupt critical operations and damage customer trust. Boards and executives must treat AI operational resilience as a core governance responsibility—not just a technical issue—to safeguard business continuity and reputation.

The US GAO’s Equifax findings show how a missed vulnerability becomes a business crisis when identification, detection, segmentation and data governance also fail. ASD, CISA, NIST, NCSC and APRA guidance show why leaders must connect continuous vulnerability assessment to critical services, accountable decisions and tested recovery.

The Australian Cyber Security Centre's procurement and AI supply-chain guidance shows why vendor assurance must be refreshed when services change. OAIC guidance adds a clear requirement for organisations to conduct privacy due diligence on commercially available AI products.

This piece looks at the questions Australian business and risk leaders should be asking before their own AI model drifts