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Responsible AI Governance with ISO/IEC 42001

ISO/IEC 42001 empowers organisations to govern AI ethically, transparently, and securely. Achieve certification to demonstrate leadership in responsible AI.

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What the Qantas Hack Reveals About Third-Party Cyber Risk in Australia?

Australia’s national carrier, Qantas, has confirmed a cyber incident involving one of its third-party contact centre providers. And while the breach didn’t involve passwords or payment data, it exposed customer records, names, email addresses, phone numbers, and Qantas Frequent Flyer details. Enough for threat actors to build social engineering attacks or pivot into more sensitive domains.
How Secure Is Your Third-Party Ecosystem?
A visual representation of the Qantas cyber incident, highlighting third-party security risk and the importance of vendor governance. This image supports a blog by Risk Associates exploring what the Qantas breach reveals about supply chain vulnerabilities.

How to Manage AI Responsibly in Your Organisation?

Artificial Intelligence (AI) is reshaping the workplace as profoundly as computers did in the 1980s and the internet in the 2000s. It’s not just another tool—it’s an intelligent assistant that understands natural language, learns from patterns, and augments human decision-making.

Yet, while AI brings efficiency and innovation, it also raises ethical, security, and compliance challenges. Organisations must ask: Who is accountable for AI decisions? How do we ensure AI is fair and unbiased? What safeguards are in place for data privacy?
Ready to enhance your AI governance framework?
Understanding Artificial Intelligence Management System This certification ensures that organisations, while adhering to regulatory and industry requirements, focus on the establishment, implementation, maintenance, and continual improvement of Artificial Intelligence (AI) management systems. ISO/IEC 42001 offers a comprehensive framework for organisations involved in developing, deploying, or using AI systems. It emphasises a risk-based approach, requiring organisations to identify and manage the specific risks associated with their AI applications.
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