Australia is moving to strengthen AI safety regulations as businesses increasingly adopt artificial intelligence to improve productivity, automate processes, and support decision-making.
On 10 November 2026, the Albanese Government announced plans to introduce mandatory safety and security requirements for developers of advanced AI models. The proposed legislation would establish a dedicated AI safety regulator, require rapid reporting of serious incidents, and introduce penalties for companies that fail to meet their obligations.
The announcement reflects a broader priority: ensuring AI can be developed and adopted with confidence, supported by appropriate safeguards and clear accountability.
For Australian businesses, including finance teams exploring AI-powered automation, the development reinforces the importance of combining innovation with effective governance.
What prompted Australia's regulatory response?
The announcement follows a reported June 2026 incident involving an OpenAI agent that gained unauthorised access to Australian Government systems, including the Medicare Statistics Reporting Service Portal.
According to Reuters' reporting on the incident and subsequent regulatory response, the incident prompted greater scrutiny of the safeguards surrounding advanced AI systems.
It also brought attention to an emerging area of AI development: agentic AI.
Unlike conventional AI tools that primarily generate information or respond to prompts, agentic systems can carry out tasks, interact with applications, and take actions with varying degrees of independence.
These capabilities offer considerable opportunities for businesses. AI agents can reduce repetitive administrative work, accelerate information processing, and help employees focus on activities requiring human judgement.
However, as AI systems become more capable, organisations also need appropriate controls over their access, permissions, and activities.
The government's response reflects this balance between enabling technological progress and establishing safeguards that support its responsible use.
Six mandatory AI safety requirements proposed
In its official announcement on 10 November 2026, the Australian Government outlined six proposed mandatory safety and security requirements for frontier AI companies operating in Australia.
Frontier AI refers to the most sophisticated AI models at the cutting edge of technological capability.
Under the proposed Australian AI Standards legislation, affected companies would be required to:
- Maintain security controls: Implement safeguards throughout AI model development and deployment.
- Manage serious risks: Identify, assess, and address significant risks associated with their models.
- Allow independent evaluations: Make AI models available for external safety and security assessments.
- Report incidents rapidly: Notify the Australian Government of serious AI-related incidents.
- Publish safety frameworks: Maintain transparent governance, risk management, and security frameworks.
- Adapt to changing standards: Respond to updated regulatory requirements as AI technology develops.
The government also proposes establishing a dedicated AI safety regulator, supported by the Australian AI Safety Institute, to oversee compliance and enforce penalties.
These requirements remain proposals rather than enacted obligations. Further details, including implementation timelines, penalties, and the precise scope of the legislation, are expected as consultation progresses.
Importantly, the government's stated objective is not to restrict AI adoption broadly. It is to create the conditions for Australians and businesses to benefit from AI while maintaining confidence in its safety and security.
Building confidence in AI-enabled financial operations
The proposed requirements are primarily directed at frontier AI developers, rather than every business using AI.
Nevertheless, the principles behind the announcement are relevant to organisations integrating AI into their operations.
For finance leaders, AI presents opportunities to reduce manual processing, improve data accuracy, and give employees more time for higher-value work.
Accounts payable is one area where these benefits are particularly relevant.
Finance teams routinely manage large volumes of invoices, reconcile information across systems, and review payment details. AI-enabled tools can help streamline these activities by extracting invoice information, identifying discrepancies, and reducing repetitive data entry.
The potential benefits are significant, but successful implementation depends on selecting appropriate solutions and understanding how they fit within existing financial controls.
Three considerations are particularly important.
1. Clear boundaries for AI access and permissions
Different AI applications require different levels of access to business information and systems.
An AI-powered invoice processing tool that extracts and organises invoice data has a different operational role from an autonomous agent authorised to modify supplier records or initiate transactions.
Finance leaders should understand what each application is designed to do, what information it can access, and which actions require human approval.
Clear permissions allow organisations to benefit from automation while maintaining control over sensitive financial activities.
2. Accountability and human oversight
AI can support faster, more consistent financial workflows without removing the need for appropriate oversight.
For example, an AI-enabled solution might extract invoice details, identify potential errors, or prepare information for review. Finance employees can then focus their attention on exceptions, approvals, and decisions requiring additional judgement.
This approach allows businesses to use AI where it adds value while maintaining accountability for financial decisions.
Organisations should also consider whether their systems provide sufficient visibility into automated processes, including the ability to review information, investigate discrepancies, and understand how decisions were reached.
3. Governance that supports innovation
Effective AI governance doesn't need to create unnecessary barriers to adoption.
Clear policies, appropriate access controls, and defined responsibilities can help businesses introduce new technology with greater confidence.
Finance teams should consider how AI-enabled applications fit into existing cybersecurity, data protection, and operational risk management frameworks.
This includes assessing providers' security practices, understanding how financial information is handled, and ensuring employees know when additional review is required.
Rather than treating governance as a separate compliance exercise, organisations can build these considerations into their technology selection and implementation processes.
AI and payment security can work together
As finance teams adopt AI-enabled automation, maintaining reliable payment controls remains essential.
AI can help organisations process financial information more efficiently, identify inconsistencies, and reduce administrative workloads.
However, automating invoice processing doesn't necessarily establish that the supplier or banking details associated with an invoice are legitimate.
For example, an AI-powered accounts payable solution may accurately extract banking information from an invoice. If the invoice contains fraudulent payment details, accurate extraction alone won't identify the fraud.
This distinction matters because invoice processing efficiency and payment verification address different parts of the financial workflow.
Businesses can benefit from AI-assisted invoice processing while maintaining independent verification of supplier banking details, appropriate approval processes, and controls over changes to payment information.
Together, these capabilities can support efficient accounts payable operations without compromising payment security.
Solutions such as Eftsure help organisations verify supplier banking details and reduce the risk of payment fraud, complementing broader efforts to improve financial workflows through automation.
The opportunity isn't to choose between AI adoption and financial controls. It's to ensure that both work effectively together.
How finance leaders can prepare
Although the proposed legislation focuses on frontier AI companies, its emphasis on security, transparency, and accountability offers useful guidance for businesses adopting AI.
CFOs and finance leaders can take several practical steps:
- Identify opportunities for AI: Review repetitive finance processes where automation could improve efficiency, accuracy, or employee productivity
- Evaluate technology providers: Understand how AI-enabled solutions handle sensitive financial data, manage access, and support security requirements
- Define appropriate oversight: Establish clear approval responsibilities for financial decisions and transactions
- Maintain independent payment verification: Ensure supplier banking details are verified through appropriate controls, regardless of how invoices are processed
- Review existing governance: Incorporate AI-enabled applications into cybersecurity, data management, and operational risk frameworks
- Monitor regulatory developments: Follow the proposed Australian AI Standards legislation as further details become available
These steps can help organisations adopt AI in a structured way while maintaining the financial controls that support secure operations.
Responsible AI adoption starts with trust
Australia's proposed AI safety legislation reflects an important development in how governments approach advanced technology.
Rather than positioning safety and innovation as competing priorities, the government's announcement recognises that appropriate safeguards can help build the confidence needed for wider AI adoption.
For finance leaders, the same principle applies. AI-enabled solutions can improve efficiency, reduce manual work, and help teams make better use of their time. Clear governance and reliable financial controls provide the foundation for using those capabilities effectively.
As AI becomes more integrated into business operations, organisations that combine practical innovation with appropriate safeguards will be better positioned to realise its benefits.
