AI Governance
AI governance for Australian organisations: board oversight, model risk, accountability, and the frameworks that keep AI use defensible.
62 articles
Articles about AI Governance
Governing AI Agents Before the Consumer Data Right Lets Them Act
The Consumer Data Right is gaining write access. Once actions are designated, an accredited provider, or an AI agent behind it, could initiate payments and switch products on a consumer's instruction. The controls for agent-initiated actions are far cheaper to build now, before any money can move.
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Your AI Agent Can Remember Now. Govern What It Keeps.
In 2026 the major labs shipped persistent memory as a first-class agent feature, barely six weeks apart. An agent that remembers across sessions is a different thing to govern, and a new attack surface. Treat the memory store as a governed data asset with write rules, provenance, expiry and rollback, not invisible plumbing.
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Canberra Just Measured What AI Is Doing to Jobs. It Found 2%.
The Australian Government has published its first systematic measurement of AI's effect on employment. DEWR's July 2026 report finds the most AI-exposed occupations grew 5.6 per cent since ChatGPT arrived, against 9.5 per cent for the least exposed, and models a 2 per cent shortfall against trend. The number is small, the caveats are real, and the implications for WHS, workers compensation, GRC, HR and leadership teams start now.
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Your AI Passed the Pilot. Production Is a Different Test.
A pilot that passed proves the AI worked once, on that data, on that version of the model. Then the model changes underneath you, the data shifts and usage drifts, and the thing you signed off quietly stops being the thing running. The answer is a standing evaluation harness, not a launch-day test. Here is how to build one, and why regulated work needs it most.
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Australia Will Not Pass an AI Act. You Are Still Regulated.
The National AI Plan settled the question every GRC team was waiting on. Australia will not pass a standalone AI Act. That is not a reprieve. It means AI is already regulated, spread across the laws and regulators you answer to now. Here is how to stop waiting for an AI law and map every AI use to the obligation it already touches.
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AI Wrote the Ad. ASIC Still Holds You to It.
ASIC refreshed its advertising guide for the first time since 2012, and it now reaches AI-generated advertising and the capability claims firms make about their AI-enabled tools. The medium is no defence. Here is what AI-washing looks like, what RG 234 now expects, and the marketing controls to put in place before the next campaign ships.
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More Agents Is Not More Intelligence. Govern the Coordination.
The plumbing for multi-agent AI just got standardised, so building systems where agents talk to each other is now easy. That is exactly why the useful question changed. Not can you wire agents together, but should you, and how do you govern the coordination when more agents is not more intelligence.
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Stop Counting Prompts. Measure the Work That Improved
Prompt counts measure tool activity, not productivity. This piece gives leaders a six-layer scorecard for measuring a defined workflow before and after AI: adoption, flow, quality, rework, risk and outcome, plus a one-page measurement contract with a decision rule set before the trial starts.
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Use AI to Build Practice Simulations, Not to Award the Pass
HR teams can use an approved AI assistant to build fictional role-plays, reveal information in stages, vary the difficulty and draft coaching questions. What AI must never do is decide whether an employee passed, is competent or faces an employment consequence. Here is the six-step workflow, the standards to write first, and the boundary that keeps assessment human.
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The 2026 AI Governance Talent Market: Assurance Skills Move to the Core
Australia's AI governance market is shifting from principle-setting towards assurance: control design, model testing, data lineage, third-party oversight and evidence a board or auditor can challenge. APRA has named the skills gap, no salary guide prices the role cleanly, and the scarce profile is the practitioner who can move from principle to proof.
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Your Pricing Agent Is Still Your Competition Risk
An AI pricing agent does not sit outside Australian competition law. Businesses must still set prices independently, prevent unlawful competitor coordination and control the data, objectives and vendors shaping every recommendation. Here is the cartel-law map, the five questions GRC must ask and the evidence pack to build before go-live.
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AI Can Draft WHS Training. It Cannot Verify Competence.
AI can draft WHS learning objectives, scenarios, quizzes and facilitator notes from verified source material. It cannot observe a worker performing the task or certify competence. This guide sets out where the two human gates sit and how to run the drafting workflow without letting a completion record impersonate a competent worker.
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Model Routing Cuts AI Bills. It Also Moves Your Data.
The enterprise AI story has shifted from which model is best to which one you can afford to keep using, and buyers are moving from tokenmaxxing to model routing. The instinct is right. But for Australian regulated work a cheaper model is usually a different provider in a different place, so every routing rule is also a Privacy Act and APRA data-flow decision.
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Someone Poisoned the Tool Description. The Agent Did the Rest.
Microsoft's incident-response team has documented the first real-world attack on the Model Context Protocol: poison a tool's description and you redirect the agent, without touching its code, its credentials or its prompt. The site's earlier MCP piece predicted this. Here is what "least agency, not just least privilege" means as an operational control, not a slogan.
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AI in Complaints Handling: What RG 271 Reserves for a Person
Financial firms are putting AI into the exact process ASIC made enforceable in RG 271. AI can triage, summarise and draft a complaint response, but the 30 day clock, the reasons, the systemic issue call and the fairness of the outcome stay with a person. Here is the obligation map, a worked example and the prompts to build your own.
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A Government Now Vets Who Gets the Model. File It as a Vendor Risk.
For the second time in a month, a US government put a frontier model behind a gate. This time it was an access list: roughly 20 vetted organisations get GPT-5.6, chosen name by name. The capability story is covered. The one that lands on your desk is procurement: government-imposed access conditions are now a vendor-risk category your due diligence has to name.
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AI Guardrails: The Safety Layer No Vendor Can Ship for You
A new default model does not make your AI system safe. Reliability and safety in production come from the guardrail layer you build around the model: input rails, grounding, output rails and action gates. Here is the architecture, a worked example that turns a written policy into running rails, and the prompts and checklist to build your first rail this week.
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A Deadline Is Not a Decision: Greenlighting AI Before the Free Window Closes
OpenAI's free window for ChatGPT's workspace agents closes today, right as the workspace-setup season begins. A vendor's deadline is a fact about the vendor, not a reason for you to decide. Here is the criteria a leader should actually greenlight on: real team need, switching cost, and governance readiness.
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You Are Now Buying Software for Agents, Not People
Gartner says $234 billion of enterprise SaaS spend is exposed to agentic arbitrage by 2030. Read as a vendor problem it is a headline. Read as a buyer it changes how you procure and govern the software you already run, so this piece turns the forecast into an API-parity test you can run this week, a five-clause contract checklist and a Monday workflow.
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Claude Sonnet 5 Became the Default. That Is a Change Event.
Anthropic released Claude Sonnet 5 on 30 June and made it the default in Claude Code and on Claude.ai Free and Pro. Almost nobody chooses a model, so a frontier swap is a silent change to a system you may have already validated. Here is how to treat it as a change event: the prompts, the Monday workflow and the register entry.
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Fable 5 Returns With a Jailbreak Severity Framework
Claude Fable 5 comes back globally on 1 July, three weeks after a US directive pulled it. The return matters less than what came with it: a safety patch that over-blocks routine coding, and a four-dimension jailbreak-severity framework the major labs are building together.
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CPS 230's 1 July Deadline Just Caught Up With Your AI Vendors
From 1 July 2026, pre-existing contracts with material service providers must meet APRA's CPS 230, and a growing share of those arrangements are now AI. Here is the work to do before the deadline, plus a reusable contract-review prompt.
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AI Agents Just Went From Minutes to Hours. The Control Point Is Where They Run.
OpenAI bought Ona and published research showing AI agents now run for hours, not seconds. The unit you have to govern moved from the prompt to the environment the agent runs in.
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The Scams Prevention Framework Meets AI: What 'Reasonable Steps' Now Demands
Treasury's exposure-draft codes for the Scams Prevention Framework set a technology-neutral reasonable-steps duty on banks, telcos and digital platforms. The scams it targets are now AI-generated, which raises the bar and creates a second duty: govern the detection AI you deploy to meet the first.
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Rolling Out AI Is a Workplace Change: Consult and Risk-Assess First
Switching on an AI tool that allocates, paces, measures, or monitors work is a change to the work under Australian WHS law. The duty to consult workers and risk-assess it sits with the business before go-live, and NSW has now written it into statute.
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AI Can Draft a SWMS in Seconds. The Site Walk and the Consultation Cannot Be Automated.
AI can produce a formatted safe work method statement in under a minute, but for high-risk construction work a SWMS is a regulated document. The site walk and the consultation that make it lawful are exactly the parts AI cannot do.
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An AI Safety Control Is Still Just a Control. The Duty to Verify It Stays With You.
An AI safety camera or sensor is a control measure like any other, and usually the weakest kind. This guide sets out the WHS duty it touches, where it sits in the hierarchy, and how to deploy and verify one without fooling yourself.
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GPT-5.6 Sol Lands. The Frontier Just Got Gated.
On 26 June OpenAI previewed GPT-5.6, a new three-model family it calls its strongest yet. The capability is real, but the news is the access: at the US government's request it launched to a handful of vetted partners, not to you. For the second time in a month a US lab's best model is gated by government. Frontier access is now a policy variable, and your AI plan needs to assume it.
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The Review Tax: AI Adoption Is Done, Now Design the Checking
Your team has adopted AI. The new problem is that the time it saves is leaking straight back out as reviewing and correcting. BCG's June 2026 data makes the leadership job clear: design how AI output gets checked, or watch the gain disappear into ad-hoc double-checking.
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AUSTRAC Just Put AI Risk Into Your AML Program Documents
On 19 June 2026 AUSTRAC updated the program starter kit documents that reporting entities build their AML/CTF programs from, adding artificial intelligence to the risk information. If you built your program before that date, your risk assessment is now out of step with the regulator's.
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OpenAI Built Its Own Chip. The Real Story Is the Cost of Intelligence.
On 24 June, OpenAI and Broadcom unveiled Jalapeño, OpenAI's first custom chip, built to run its models more cheaply. The coverage is about a strike at Nvidia. The useful signal for a practitioner is the opposite of hardware: it is the falling cost of intelligence, and what that does to your AI decisions and your governance. Cost has quietly been holding AI back. That fence is coming down.
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Your AI Assistant Just Became a Shared Teammate. Govern the Channel.
On 23 June, Anthropic launched Claude Tag, a single shared Claude that lives in a Slack workspace with its own memory and admin-scoped access to channels, tools and data. The unit of AI collaboration just moved from the private conversation to the team channel. The thing you now have to govern is no longer a prompt. It is a standing presence. Here is what changes, and the three decisions to make before it is live.
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Decision Rights Are the Leadership Job AI Just Made Urgent
Sixty per cent of executives now use AI to support their decisions, yet most organisations have never been clear about who decides what. AI does not wait for that clarity. If you do not assign decision rights deliberately, the system will assume them. Here is the leadership move.
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AML Tranche 2: What AI Can and Cannot Do for Your New Program
From 1 July 2026, tens of thousands of lawyers, accountants, real estate agents and dealers in precious metals become AML regulated for the first time. AI can help them stand up a program fast. It cannot own the risk-based judgement AUSTRAC will hold them to.
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Model Context Protocol: The Standard Wiring AI Into Your Tools
In eighteen months the Model Context Protocol went from an Anthropic experiment to the way AI plugs into your tools and data. Understanding what it is matters less than governing the connectors, because each one is a new door into your systems. Here is the capability and the control work.
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AI-Assisted Psychosocial Risk Assessment: A WHS Governance Workflow That Keeps the Sign-Off Human
A practical WHS governance workflow for Australian financial-services teams: use AI to synthesise de-identified survey data and draft the written psychosocial risk assessment, while a competent person always sets the rating, chooses the controls, and signs off.
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Automated Decisions Now Belong in Your Privacy Policy
From 10 December 2026, APP entities that use personal information in automated decisions affecting people's rights must say so in their privacy policy. For Australian financial services, that is most of the AI already running in underwriting, fraud, collections and claims. Here is the readiness work, with a reusable AI project, prompt library and a worked insurer example.
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Business Teams Can Now Build Their Own AI Agents
Databricks launched Genie One this week, an agentic coworker pitched at finance and marketing teams, not engineers. The real shift is who holds the build button, and where that moves the control point. Here is what to do this week, with a governance prompt you can run today.
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The OWASP Agentic Top 10: A Defence Playbook for the Agents You Are Deploying
OWASP has published a Top 10 built specifically for AI agents. It reframes the agent as a privileged user that reads untrusted text and acts with your access. Here is the practical defence playbook.
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AI Is Moving Into the Core Systems of Regulated Work
This week two of the world's largest IT services firms began wiring a frontier model into the core systems that banks, insurers and airlines run on, not the chat window. Here is what it means for regulated work, and what to do this week.
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AI Work Allocation Needs Psychosocial Risk Controls
Effective AI work allocation requires assessing psychosocial risks like job demands, control, support and fairness before deployment.
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Managers Need an AI Operating Rhythm, Not More Pilots
Managers must move beyond isolated AI pilots by establishing a clear operating rhythm that integrates AI into team workflows with regular review and improvement cycles.
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AI Literacy Is a Management Skill, Not a Training Module
Managers must embed AI literacy through daily behaviours like prompting, verification, privacy hygiene, escalation and review to ensure responsible AI use.
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Build an AI Use Case Register That Boards Can Actually Use
Practical guidance for GRC teams to create AI use case registers that deliver clear, decision-ready evidence for boards and risk committees.
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AI Cyber Risk Is Now a Board Governance Issue
ASIC's May 2026 cyber uplift warning highlights that AI-driven cyber risk demands active board and risk committee oversight, not just IT fixes. This article outlines a practical governance operating model for GRC teams.
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AI Agents Need Approval Gates Before They Need Autonomy
Autonomous AI agents are becoming practical, but organisations should design approval gates, permissions and evidence trails before granting action rights.
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Small Models, Edge AI and the Next Governance Blind Spot
As AI moves into devices, business apps and smaller specialised models, organisations need governance that looks beyond frontier models and public chatbots.
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Workplace AI and Privacy: The Trust Test HR Cannot Outsource
AI productivity tools can reshape workplace data collection, monitoring and employee trust. HR needs a privacy-first governance model before adoption scales.
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Leveraging AI to assist dissecting the SRC Act Review
A practitioner workflow for employers to dissect the December 2025 SRC Act Review with AI tooling. Project setup, four prompt patterns, submission scaffolding, and the two human review gates that keep the work defensible.
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AI Can Organise Recovery-at-Work Information, but People Must Decide
A practical SRC Act article on using AI to support suitable duties and recovery-at-work planning without replacing evidence, consultation or human judgement.
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The AI Pilot-to-Scale Gap Is an Operating Model Problem
Most organisations can run AI pilots. Far fewer can scale them safely, consistently and usefully across real work.
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Board AI Literacy Is Now a Control Expectation, Not a Training Nice-to-Have
APRA's April 2026 AI letter signals that board AI literacy is becoming a governance control expectation, not a generic awareness exercise.
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Predictive Analytics and Claims Triage: A Risk Analysis for Scheme Operators
Predictive triage models promise faster decisions and better outcomes. They also concentrate legal, ethical, and procedural fairness risk. Here is how to think about both.
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ASIC's AI Supervisory Posture, Decoded
ASIC's posture on AI in financial services is now visible across REP 798, the 2026 Key Issues Outlook, and recent statements from the Chair. Five themes shape supervisory expectation, and three create immediate work for compliance teams.
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AI Tools in Workers Compensation Claims: Where Value, Where Risk, Where Governance
AI is now operating across five workflows in workers compensation claims. The value is real. The governance baseline is non-negotiable. A practitioner's map of where each tool fits, what it actually does, and what to never do.
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FAR and AI: How Accountability Maps to Tooling Decisions
The Financial Accountability Regime makes specific senior executives answerable for the systems and decisions inside their portfolios. AI tooling decisions sit inside that accountability, whether they are formally documented in the responsibility map or not.
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AML/CTF and Large Language Models: A Compliance View
Large language models are now embedded across AML/CTF programs, from suspicious matter triage to KYC document review. AUSTRAC's posture on these uses is shaping. Reporting entities need a clear governance position now, not later.
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DDO and AI-Driven Personalisation: Where the Boundary Sits
AI personalisation is moving fast inside Australian financial services. The Design and Distribution Obligations were not written with adaptive recommendation engines in mind. The boundary between targeting and personal advice is the line GRC teams need to govern.
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APRA's Model Risk Thematic Review: What to Expect
APRA's model risk thematic review is expected to land in the second half of 2026. The signals from supervisory engagement to date suggest where it will press hardest, and what regulated entities should be doing now.
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CPS 230 and AI: A Practical Operational Resilience Playbook
CPS 230 has been live since 1 July 2025. Nine months in, the practical question for boards and operational risk teams is no longer whether AI tools fall inside the standard. It is how to evidence it.
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How to Read an AI Tool Safety Card and Spot the Red Flags
Every frontier AI vendor publishes a safety card or model card. Most are 30 pages of mixed marketing and substance. Here is how to read one in 20 minutes and walk away knowing what matters.
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SRC Act and AI Assisted Determinations: A Practitioner Framework
AI can draft a determination in minutes, but the SRC Act still demands a qualified human decision maker. Here is the practitioner framework that keeps both true.
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