Managing AI privacy risk with ISO 42001

As artificial intelligence becomes more deeply embedded in business operations, Australian organisations are facing a growing set of privacy challenges. These challenges go beyond technology - they affect strategy, compliance, and public trust.

Organisations must now navigate a landscape where public expectations around data use are rising, regulatory scrutiny is intensifying, and the risks of mismanaging personal information are more consequential than ever. Automated AI decision-making has come under close scrutiny, with its potential to impact individuals in ways that are often unexplainable or unfair.

Adding to this is the increasing use of shadow AI. This is where employees adopt AI tools without formal approval or oversight, creating blind spots in data governance and privacy compliance.

Responsible AI governance is no longer a "nice-to-have". It is now a must-have. Thankfully, ISO 42001 offers a timely and practical framework. As the first international standard for AI management systems, it provides a structured approach to managing AI risks, aligning with privacy principles, and preparing for the next wave of regulatory change.

The AI Privacy Challenges You’re Already Facing

• Uncontrolled Data Flows: AI systems often rely on large, diverse datasets. Without robust data governance, it becomes difficult to track how personal data is collected, processed, and shared – especially across third-party platforms.
• Shadow AI: Employees are increasingly using generative AI tools (e.g., ChatGPT, GitHub Copilot) without formal approval. This “shadow AI” introduces unmanaged privacy risks, including inadvertent exposure of sensitive or regulated data.
• Opaque Decision-Making: AI models can make decisions that affect individuals – such as eligibility for services or pricing – without clear explanations or audit trails, raising concerns under both current and forthcoming privacy obligations. This includes the requirement for greater transparency for individuals affected by automated decision making that will be required under provisions within the Privacy and Other Legislative Amendment Act 2024 (POLA Act) - more on that below.
• Cross-Border Data Exposure: Many AI tools operate in cloud environments with global infrastructure, complicating compliance with Australian privacy laws and international frameworks like the GDPR.
• Lack of Privacy Engineering Capabilities: Mid-sized organisations often lack in-house expertise in privacy-preserving techniques such as anonymisation, federated learning, or differential privacy.

Preparing for Regulatory Change

The need for robust AI governance is further underscored by recent reforms to Australia’s privacy framework. The Privacy and Other Legislation Amendment Act 2024 introduces new obligations for organisations using automated decision-making (ADM). From 10 December 2026, privacy policies must clearly disclose when personal information is used in ADM processes that significantly affect individuals’ rights or interests – including the types of decisions made and the data involved.

Another significant change to the Act, which commenced on 10th June 2025, opens a pathway for individuals to take direct action against organisations who seriously intrude on their seclusion (such as through watching, listening, or recording their private activities) or who misuse their private information.

These changes reflect a broader regulatory trend toward greater transparency, accountability, and individual empowerment in the context of AI. For Australian organisations, it signals the importance of embedding explainability and auditability into AI systems now - before these requirements become enforceable.

How ISO 42001 Helps You Take Control

ISO 42001 provides a management system approach to AI governance, similar to ISO 27001 for information security. It enables organisations to:

• Establish clear AI governance policies aligned with business objectives and legal obligations.
• Conduct risk assessments that include privacy impact evaluations for AI systems.
• Define roles and responsibilities for AI oversight, including data protection and ethical review.
• Integrate with ISO 27701, the privacy extension of ISO 27001, to ensure end-to-end privacy compliance.
• Monitor and manage AI lifecycle risks, including model drift, data misuse, and unauthorised access.

Importantly, ISO 42001 also addresses the human element, encouraging organisations to implement training, awareness, and controls to mitigate the risks of shadow AI.

Why ISO 42001 has benefits over ISO 27701

While ISO 27701 extends ISO 27001 to address privacy information management, it was not designed with artificial intelligence in mind. ISO 27701 focuses on traditional data privacy controls, such as consent management, data subject rights, and data minimisation, within the context of general IT systems. These are essential, but they don’t fully address the unique challenges posed by AI.

On the other hand, ISO 42001 is purpose-built for AI governance. It goes beyond conventional privacy frameworks by embedding AI-specific risk controls, including:

• Model transparency and explainability: ISO 42001 encourages organisations to document and communicate how AI models make decisions - an essential requirement under Australia’s Privacy and Other Legislation Amendment Act 2024.
• Bias and fairness assessments: It includes mechanisms to identify and mitigate discriminatory outcomes, which are not explicitly covered in ISO 27701.
• Lifecycle risk management: ISO 42001 supports continuous monitoring of AI systems, including model drift and data misuse, which are critical for maintaining privacy over time.
• Human oversight and accountability: The standard promotes clear governance structures for AI, including roles for ethical review and privacy impact assessments tailored to AI contexts.

Moreover, ISO 42001 integrates well with ISO 27701, allowing organisations to build on existing privacy programs while extending their capabilities to cover AI-specific risks. This layered approach ensures that privacy is not just protected at the data level, but also at the algorithmic and decision-making levels, where many of today’s AI privacy risks originate.

AI adoption is accelerating, but so are the expectations around how it’s governed. For Australian organisations, ISO 42001 offers a practical, scalable framework to manage AI risks, protect privacy, and strengthen stakeholder trust. By taking a proactive approach today, you can ensure your organisation is not only compliant but also remains competitive in the AI-driven economy of tomorrow.

Need assistance?

If you would like assistance with implementing ISO 42001 or ISO 27701, we'd love to chat. We support organisations Australia wide, with specialists in Brisbane and Toowoomba.