Australian Privacy Trends in 2026: What We Think is Coming Next Year

We asked our team of privacy professionals to see where they think privacy in Australia is headed in 2026. The key undercurrent to their predictions? Privacy matters – to regulators and a public that is increasingly weary of data breaches and algorithmic manipulation. Organisations need to adapt, starting with finding their positioning on privacy and learning to communicate it. 

Here are the key trends and challenges that will define Australia’s privacy landscape in 2026:

Our 5 Predictions for Privacy in Australia in 2026

Privacy reform to be a vehicle for regulating AI risk 

A key priority for 2026 will be the advancement of the Privacy Act’s second tranche of reforms. Because the Government has noted its preference to embed AI obligations into existing frameworks rather than creating standalone legislation, privacy reform will become one of the primary vehicles for regulating AI risk.

It’s probable that the Australian government’s decision to move away from a dedicated AI regulation model to an integrative approach may leave Australians exposed to harm. These aren’t hypothetical harms either, the world is already seeing: 

• Social harms, such as algorithmic bias in hiring and healthcare tools, as well as harms from predictive policing (which we saw in Australia with the AFP adopting the Auror technology).
• Information and safety harms, ranging from disinformation and deepfakes to dark patterns designed to maximise engagement with platforms with no regard for mental health risk. 
• Not to mention systemic risks and environmental impact, and the risks of exploitative labour. 

Finally, the fracturing approach to AI regulation globally means Australian organisations will need to absorb the regulatory complexity. The EU, Americas, and Asia Pacific region are adopting different approaches to AI regulation – and these approaches are all being challenged by US dominance in AI development and the economic pressures that come with it. If you haven’t already considered your organisation’s position on slow innovation vs rapid adoption of AI, it may be time to start.

Human oversight in AI systems to face legal challenges

Since AI adoption became more widespread, we’ve seen regulators around the world call for organisations to ensure there’s a human-in-the-loop. What this should mean is that there’s a human who understands the risk AI use poses to the organisation and who is ready and willing to step in when AI makes decisions that are non-compliant – or even just not in the best interest of the organisation. 

We predict that 2026 will see increased interrogation from regulators and courts about whether human oversight of AI is real or performative. The key question will be whether humans can genuinely challenge, override and take responsibility for AI-driven decisions.

Data minimisation to be challenged

Data minimisation remains one of the most helpful tools available to organisations for reducing or eliminating privacy risk. You can’t lose what you don’t have, as the saying goes. But 2026 looks poised to introduce yet more confusion for organisations and the Australian public about what ‘fair collection’ looks like. 

We predict this because we’re seeing the tension between data-driven harm prevention and data-driven public good showing up in Australian law reform. As thousands of organisations begin mandatory identity verification under AML/CTF reforms, Australians will experience firsthand what it means to hand over more data in the name of safety. We also discussed balancing data collection for age verification with the obligation to minimise data in our recent piece covering Australia’s social media ban legislation.

It’s interesting to think about this in the context of the tension between AI’s demand for ever-larger datasets and privacy principles of data minimisation. AI thrives on vast, diverse datasets, yet the law increasingly requires organisations to justify every scrap of personal information they hold. We think that organisations will increasingly need to be able to demonstrate why they are collecting data to regulators and the public. It’ll become more important to be able to show more data actually delivers better, fairer outcomes, especially in high-impact sectors like health, employment, and finance. 

A shift from ‘who stole my data?’ to ‘what is being inferred about me’?

It has taken some time for the public to digest the data economy, with the focus so far being in data breaches. But, we are starting to notice a shift in public perception about data collection and usage – especially when it comes to inferences. 

We expect 2026 to see a shift in sentiment from the public from ‘who stole my data?’ to ‘what is being inferred about me without my knowledge, and where might it resurface?’. 

Privacy professionals evolve into decision-risk translators

Privacy is becoming less about checkbox compliance, and more about connecting design choices to downstream legal, ethical, reputational and social impacts. This shift has been a long time coming. 

As a result, we predict that successful privacy professionals will be valued less as compliance specialists and more as translators of decision risk throughout 2026. We also think this shift will mean more organisations adopt an approach that links its privacy teams to executive decision-making and board-level risk.

2026 Privacy Readiness Checklist

To prepare for these evolving trends, Australian organisations should consider the following:

• Audit AI Implementations.

Organisations need to ensure appropriate mechanisms are embedded to continuously monitor AI-enabled processes for privacy compliance. This is becoming urgent, as regulators are set to launch compliance sweeps of public-facing policies at the start of the year.

• Update Privacy Policies for AI. 

In the same vein, organisations should ensure public-facing privacy policies clearly articulate how AI is used, what data it processes, and what inferences might be drawn. 

• Implement “Explainable AI” Principles. 

Can you clearly and simply explain how your AI systems make decisions to a non-technical audience? Systems that are lawful but unintelligible will increasingly struggle to maintain trust, so it’s important to ensure yours are explainable, not just compliant. 

• Strengthen Human Oversight Mechanisms. 

Establish clear processes for humans to genuinely challenge, override, and take responsibility for AI-driven decisions.

• Re-evaluate Data Minimisation Strategies. 

Review data collection practices, especially for AI. Can you demonstrate that collecting more data genuinely leads to better, fairer outcomes, particularly in sensitive areas? If not, you may need to rethink your approach to data use. 

• Upskill Privacy Professionals. 

Empower privacy teams to act as “decision-risk translators,” equipping them to assess the broader legal, ethical, reputational, and social impacts of AI and data initiatives. Need some additional privacy training to get there? Privacy 108 offers IAPP training courses for privacy professionals looking to take the next step in their career, as well as tailored privacy training for organisations looking to improve privacy posture. Reach out to us at hello@privacy108.com.au to discuss your privacy training needs. 

• Monitor Legal Precedents. 

Stay informed about the outcomes from significant privacy-related cases, such as Optus and Medibank, as they will shape future compliance expectations. We share information about significant privacy developments in our bi-monthly newsletter, so it’s worth signing up if you’d like a low-touch, informative newsletter to help you.