HASH ELEVENS

Australians are investing in record numbers. The ASX says 11.5 million adults now hold investments outside superannuation and their primary home, and, for the first time, its investor study tracked the use of AI for investment information and advice. Among investors aged 18–29, 14% are already using AI tools. That is not surprising. AI can help make unfamiliar concepts clearer, compare information quickly and lower the barrier to getting started. But accessible information is

Most tokenisation conversations begin with the technology. The more useful question is whether it can settle safely, efficiently and at scale. That is where Project Acacia matters. The RBA’s latest Payments System Board report confirms that tokenised assets, digital money and improved settlement infrastructure could make Australia’s wholesale financial markets more efficient and functional. Just as importantly, the work is moving beyond demonstrations. The next stage includes

Recent headlines about an OpenAI agent accessing an Australian government Medicare statistics portal have understandably caused concern. The incident deserves scrutiny. An AI agent gained unauthorised access to non-public aggregate health statistics and internal files on 18 June. The government says there is no evidence that personal Medicare records were accessed, or that the wider Services Australia network was compromised. However, the delay in reporting the incident was r

Australia’s cyber intelligence chief, Abigail Bradshaw, has called for an AI “early warning system”: a way to connect individual incidents, spot emerging patterns and share warnings before a problem becomes widespread. ABC News reported on the comments here. The national conversation is important. But there is also a practical lesson for every organisation using AI today. Most businesses do not need a sophisticated intelligence capability tomorrow. They do need a reliable way

When organisations assess agentic AI, most attention still goes to the model. New guidance from the Australian Signals Directorate (ASD)makes an important point: the model is only part of the risk. ASD uses the term “harness” for the software layer connecting an AI model to organisational data, tools, memory and systems. That distinction matters. A chatbot produces content. An AI agent may search files, access customer information, call APIs, update records or initiate action

Project Acacia is entering its next stage and the focus is shifting from experimentation to infrastructure. On 27 August, the RBA’s Payments System Board endorsed a proposed consultation on how the Reserve Bank Information and Transfer System (RITS) could support tokenised wholesale asset markets and tokenised money. This follows Project Acacia’s testing of 20 tokenised-market use cases, including settlement through traditional exchange settlement account balances, a pilot wh

For years, one of the standard responses to a suspicious investment opportunity has been: “Search the company online.” That advice is no longer enough. ASIC has warned that scammers are using generative AI to create convincing networks of fake credibility. A person may encounter a deepfake endorsement, follow it to a fabricated news article, find a professional-looking website and then see positive reviews that appear to confirm the opportunity is legitimate. Every part of th

AI agents are quickly moving from novelty to practical business tools. They can book appointments, search systems, complete tasks, interact with platforms and make decisions with less direct human input. That makes them useful, but it also creates a new governance problem. A recent Australian report by The Guardian highlighted the issue clearly, if an AI agent causes harm, makes the wrong decision, misuses access or acts in a way nobody expected, the agent itself is not the o

The EU AI Act is entering a major implementation phase, and it is another clear sign that AI governance is moving from voluntary guidance into enforceable regulation. The Act is not just aimed at stopping harmful AI use. It creates a broader framework around how AI is developed, deployed, documented and monitored. Key areas include transparency, copyright, safety and security, general-purpose AI models, high-risk AI systems, and the labelling of AI-generated content. Provider

Australia’s AI policy is moving from broad guidance to clearer standards. On 15 July 2026, the Australian Government announced plans for a new AI framework built around Australian Standards for AI. The aim is to make sure AI development, investment and infrastructure operate in Australia’s national interest. A major focus is large data centres and AI training infrastructure. The proposed standards are expected to create clearer rules around energy supply, grid connection cost