AI Regulations in Australia: Where We Are, Why We Need Them, and What’s Next
Artificial Intelligence is moving faster than the law can keep up, and Australia - like the rest of the world - is scrambling to figure out what to do about it.
Right now, AI is being used to generate content, automate decisions, analyse people, and even predict behaviour. And while that’s great for innovation, it also opens the door to bias, misinformation, data breaches, and ethical nightmares.
So, where does Australia stand on AI regulation? What’s being done to control the risks while still allowing businesses and researchers to innovate? And as AI gets smarter, what’s next?
Where Are We Now? Australia’s Current AI Regulations
At this stage, Australia doesn’t have a dedicated AI law like the EU’s AI Act or China’s strict AI regulations. But that doesn’t mean AI is a free-for-all. Instead, it falls under existing laws, including:
Privacy Act 1988 – Covers how businesses collect and use personal data (but is outdated for AI-driven decision-making).
Australian Consumer Law – Protects against misleading AI-driven advertising or deceptive business practices.
Anti-Discrimination Laws – AI can’t be used to make discriminatory decisions (but proving AI bias is another story).
Copyright Act 1968 – A hot topic as AI-generated content raises questions about ownership and intellectual property.
The Australian government knows this isn’t enough. That’s why they’ve been running reviews, consultations, and pilot projects to figure out what AI-specific regulations should look like.
One of the biggest moves is the Safe and Responsible AI Discussion Paper released in 2023. This outlines potential pathways for AI governance, from voluntary guidelines to outright bans on high-risk AI applications.
Why We Need AI Regulations (Like, Yesterday)
AI is already deeply embedded in Australian businesses, government agencies, and research institutions. And while it’s great at boosting efficiency, automating tasks, and analysing data, it also brings serious risks.
1. AI Bias and Discrimination
AI models learn from existing data, which means they inherit human biases. If a recruitment AI is trained on biased hiring data, it will keep making biased decisions - locking in discrimination at scale.
Without regulation, businesses using AI for hiring, banking, or customer service could unknowingly discriminate, and people wouldn’t even know how to challenge it.
2. Deepfakes and AI-Generated Misinformation
AI can create realistic fake images, videos, and voices - making misinformation easier to spread. In an election year, we’ve seen how this goes abroad.
Without clear laws on AI-generated content and verification, fake news could become indistinguishable from reality, and the consequences could be massive.
3. Data Privacy and AI Surveillance
AI thrives on data but who owns that data? How is it being used? Can AI models trained on private information be held accountable?
Right now, Australian privacy laws weren’t built for AI’s data collection, and that leaves businesses and individuals vulnerable.
Where AI Regulation Is Headed in Australia
So, what’s next?
1. Stricter AI Guidelines for Business
Expect tougher transparency and accountability rules, especially for AI used in:
Hiring and recruitment
Financial services
Healthcare decision-making
Government and legal processes
Companies using AI to make decisions that impact people’s lives will likely need to explain how their AI works, prove it’s fair, and give people ways to challenge automated decisions.
2. A Potential Ban on High-Risk AI
The government is considering bans on “high-risk” AI applications, including:
Emotion recognition AI (used in job interviews or surveillance)
AI that manipulates behaviour (think hyper-targeted political ads)
AI-generated deepfakes designed to deceive
If these bans go ahead, businesses relying on aggressive AI marketing or facial recognition tools may need to rethink their strategies.
3. More AI Oversight and Compliance Requirements
Businesses using AI tools may soon be required to conduct risk assessments before deploying AI in customer-facing roles.
We are likely to also see mandatory labelling of AI-generated content, similar to the EU’s proposed laws, so that consumers know when they’re dealing with a bot.
What This Means for Businesses and Researchers
For businesses, AI regulation means compliance is about to get more complicated. If you’re using AI for data analysis, decision-making, or customer interactions, you’ll need to:
Be transparent about how AI is used in your products and services. Consumers will demand to know when they’re interacting with AI.
Ensure AI models aren’t biased, which means testing them rigorously rather than assuming they work as intended.
Handle customer data responsibly, as privacy laws tighten and AI’s data collection comes under heavier scrutiny.
For researchers, the biggest challenge is navigating AI ethics while still pushing innovation forward. The academic world is already seeing questions around AI-generated research, fabricated citations, and non-reproducible results, and stricter oversight is coming.
AI-assisted research may soon require full disclosure, with stricter rules on how much AI-generated content can be used in academic work.
The risk of AI bias in research is real. Large language models aren’t neutral observers; they pull from existing datasets that may introduce distortions.
Reproducibility is a growing concern. If research findings rely on black-box AI models, they are impossible to verify or replicate.
Why Researchers Should Steer Towards Non-AI Software
As regulations tighten, non-AI tools, especially those based on machine learning rather than generative AI, will become the safer option for qualitative research and text analysis.
Unlike LLMs, which generate new content and risk fabricating information, machine learning-based tools like Leximancer focus on identifying patterns within existing data and without injecting bias or making assumptions.
This matters for a number of reasons:
Transparency: Non-AI software provides clear methodologies for text analysis, meaning findings can be validated and reproduced.
Bias-free insights: AI-generated summaries can be misleading; machine learning tools like Leximancer let the data speak for itself, mapping themes without distorting meaning.
Compliance-ready research: As AI oversight increases, universities and research institutions will restrict the use of generative AI. Researchers who use verifiable, non-AI tools will avoid future compliance headaches.
Ultimately, as AI-generated content faces growing scepticism, researchers who rely on trusted, transparent analysis tools will be in a stronger position to defend their work.
Now is the time to move toward proven, reproducible, and bias-free solutions, before AI regulations make it mandatory.
AI Regulation Is Inevitable - But That’s a Good Thing
Australia’s AI regulation may not be as strict or fast-moving as the EU’s, but change is coming. It’s goal is to protect consumers, prevent AI-driven harm, and ensure businesses use AI responsibly.
If you’re using AI in any capacity, now’s the time to get ahead of the rules.
Want to stay compliant while using AI to its full potential? Leximancer provides transparent, bias-free machine learning to analyse text and uncover real insights - without the risks of AI-generated misinformation. Get ahead of AI regulation and make smarter, compliant business decisions - or secure your research to withstand the test of time. Try Leximancer today.
