Navigating AI regulation in Australia: A strategic guide for business leaders (2026)

Australia's AI regulation in 2026 is governed by existing laws, not a standalone act. Learn how business leaders can navigate complexity, ensure accountability, and build trust with responsible AI governance.

As of January 2026, Australia does not have an AI Act. But that does not mean AI is unregulated. For organisations operating in or selling into Australia, 2026 is about navigating complexity, earning trust, and avoiding costly missteps.

Australia has taken a distinctive approach to AI oversight. Unlike the European Union, there is no standalone AI legislation, no mandatory "high-risk" regime, and no single AI regulator. Instead, the Australian Government adopted a standards-led approach in late 2025, relying on existing, technology-neutral laws and voluntary frameworks.

For executives, the message is clear: the absence of AI-specific legislation does not mean a lack of accountability. In practice, accountability is fragmented across multiple regulators, which often makes it more difficult, especially as AI has crept in through our tool stack.

For leaders doing business in or with Australia, the real challenge this year is threefold:

Navigating that complexity
Building trust with customers and employees
Avoiding avoidable mistakes when rolling out AI‑enabled services

The regulatory framework: What laws apply?

There's no standalone "AI law", no formal high‑risk category, and no single AI regulator in place. Instead, AI is governed through a patchwork of existing legislation and standards:

Here are the ones that come up most often in practice:

Legislation	Application to AI
Privacy Act 1988	Applies whenever your AI workflows touch personal information, imposing requirements for data collection, accuracy, and security.
Anti-discrimination laws	Employers and service providers remain liable for discriminatory outcomes from automated systems, even where there was no discriminatory intent.
Australian consumer law	Protects against “AI‑washing” (overstating capabilities) and enforces product safety and consumer guarantees.
Copyright law	Australia has no copyright carve-out for AI training; you must have legal rights to the data used.

On top of that, some sectors have extra oversight:

Healthcare: The TGA regulates certain AI tools as Software as a Medical Device
Financial services: ASIC and APRA expect strong governance, risk management, and accountability
Government: Public sector AI use comes with mandatory transparency and risk assessments

A date for the diary: 10 December 2026

The most immediate change most leaders need to plan for comes from updates to the Privacy Act around automated decision-making (ADM).

From 10 December 2026, organisations will need to clearly explain:

What personal data is used in automated decisions
Which decisions are AI-assisted or fully automated
Whether those decisions could significantly affect someone

Action point: If AI influences decisions about customers, employees, or users, now is the time to start listing those systems. Leaving this until late 2026 will be painful.

Questions we're hearing a lot

If I buy AI from a vendor, am I still responsible if something goes wrong?

Yes. In Australia, accountability doesn't shift to the vendor. If a third-party tool drives a discriminatory hiring outcome or an unfair customer decision, it's still your responsibility.

Is "human-in-the-loop" enough to stay out of trouble?

Not on its own. Transparency rules still apply if a human is involved, but it relies heavily on AI outputs. The question regulators ask is whether AI meaningfully influenced the decision.

What's the biggest risk to AI adoption in Australia right now?

Trust. Only about 30% of Australians believe the benefits of AI outweigh the risks, and nearly 80% are worried about negative impacts. Responsible AI isn't just about compliance; it's about reputation and credibility.

What does "good AI governance" look like in practice?

You don't need a huge compliance program to meet expectations, but you do need the basics in place. Organisations that are seen as doing this well usually have:

Clear ownership: Someone at exec and board level who is accountable
An AI inventory: A simple, living list of AI systems and what they're used for
Smarter procurement: Asking vendors where training data comes from, how bias is tested, and where data is stored
Explainability where it matters: Especially for high-impact decisions

Ongoing checks:

Making sure systems still behave as expected over time

Aligning with Australia's AI Ethics Principles is increasingly seen as the "reasonable" baseline.

Australia's standards-led approach gives organisations flexibility, but it also puts more responsibility on leaders to make good calls.

The organisations that will get the most out of AI in 2026 will be those of us taking a proactive and responsible approach to AI as a capability to build trust with all our stakeholders.