SRC Act
AI under the SRC Act 1988 and the Comcare scheme: liability, rehabilitation, and claims practice for workers compensation professionals.
55 articles
Articles about SRC Act
Your AI Register Is Not Licence Evidence Until It Maps to the SRCC Criteria
An approved AI use case records an intention. Licence evidence must show which existing obligation is engaged, what control operated, what exception occurred, who owned it and what independent assurance found. A criterion-to-evidence crosswalk makes that chain inspectable.
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Section 39 Requests Need a Branching Evidence Map, Not One Checklist
An aid can be medical treatment, rehabilitation support or something outside both routes. AI can expose the branches and assemble the evidence, but a human must select the statutory path, decide entitlement and preserve the reasons for that choice.
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TOOCS Coding Is Data Quality, Not a Liability Finding
A TOOCS code can improve national data and still prove nothing about liability. Use AI after human entry to test version, evidence traceability and cross-field consistency. Keep every correction with a human coder and every statutory finding with the delegate.
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A Complaint Is Not a Reconsideration: AI Can Route the Issue, Not Close It
A complaint can seek better service, challenge a determination and raise a licence concern in the same paragraph. AI can expose those parallel pathways, but a human must classify the message, protect every clock and approve every response.
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A Defensible Claims Audit Sample Starts With the Population, Not an AI Risk Score
An AI-selected list of unusual claims may be useful for investigation, but it cannot represent a claims management system. Start with the frozen population and Comcare's published sample bands, preserve a representative core, and keep every targeted file, substitution and finding under auditor control.
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One Serious Claim in Nine Is Now Mental Stress. A Decade Ago It Was One in Seventeen.
We computed the ten-year mental stress series from Safe Work Australia's national claims dataset. Serious mental stress claims rose from 6,261 to 16,839, their share of all serious claims nearly doubled, and each one costs around five times the median time lost. The full method is published with the finding.
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Section 54 Intake: AI Can Find Gaps, Not Move the Clock
An intake model that merges receipt, claim compliance and clock status can hide delay behind a neat dashboard. Keep those states separate. AI can reconcile dates and expose missing evidence, but a human must decide section 54 compliance and every lawful exclusion.
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Backdated Incapacity Needs Three Ledgers, Not One Payroll Fix
A retrospective incapacity determination can affect claim payments, payroll transactions and leave records at once, and those records do not carry the same legal meaning. AI should reconcile three ledgers and expose variances, while authorised claims and payroll professionals approve and post every correction.
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Statement Summaries Need Source IDs, Not a Neat Story
A polished narrative can hide who said what, where it appears and what remains contested. A source-level assertion ledger keeps each proposition attached to the original statement, so AI assists evidence navigation while the authorised decision-maker retains every factual and credibility judgement.
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Normal Weekly Earnings: AI Can Assemble the Evidence, Not Set the Figure
Most NWE mistakes start before the formula: a missing allowance rule, a distorted pay period, or overtime with no evidence of being required. AI can expose those gaps, but the relevant period and section 8 figure remain human determinations.
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A Determination Evidence-Check Skill File Under Section 14
An advanced SRC Act skill file that audits a draft determination's evidence chain against sections 5A, 5B and 14, flags hedged language and gaps, and never touches the decision itself.
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An Incident Triage Skill File That Never Decides Notifiability
The first hour after a serious incident is chaos, and chaos is where structure helps most. This skill file structures the incident record and lays the facts under each notifiable incident question, while the statutory judgement, and the immediate phone call, stay with a person.
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AI Can Run the Section 14 Clock. It Cannot Decide.
Since 1 April 2024 a determining authority has had 20 calendar days to determine an initial injury claim, 60 for a disease claim and 30 to decide a claimant's request for reconsideration. The count can be frozen, but only by specific statutory triggers. That is a tracking problem AI is genuinely good at, sitting next to a determination it must never touch.
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A Claim Chronology Skill File Built for De-Identification
A reusable six-part skill file that builds claim chronologies from de-identified material only, tags every entry to a source document, flags gaps and conflicts, and never states a view on liability.
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The Safety Comms Skill File: Alerts Workers Actually Read
Safety alerts fail when they are generic, long and blame-flavoured. A safety comms skill file encodes the plain-language, site-specific standard once, so every alert, toolbox intro and bulletin meets it, and every draft still stops at the HSR and a competent person before release.
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Section 57 Examinations: AI Can Build the Referral, Not Make the Call
Since June 2024 a decision to require a section 57 medical examination is a reviewable determination, and since October 2024 it must comply with a mandatory Guide built around ethical, transparent and accountable decision-making. That raises the stakes on the referral paperwork. AI can assemble the de-identified brief, draft the question set and produce a Guide-aligned record, while the decision to require the examination stays a human judgement.
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The Medical Report Now Has to Declare Its AI
Since 2 March 2026 an expert report prepared for the Administrative Review Tribunal has to state whether it contains generative AI content, identify that content and the applications used, and certify the expert checked all of it. Clause 3.7 is the part claims practitioners have missed. Reports commissioned during the claim end up in the Tribunal's documents and are read against a standard they were never written to meet.
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Preventing Double Payment Under the SRC Act: AI Can Flag the Overlap, Not Calculate the Offset
The SRC Act guards against paying twice for the same injury: through third-party damages, an overlapping state workers compensation claim, or a state general compensation scheme. AI can flag a file for a possible overlap early and build the chronology of the parallel claim. Calculating the offset or recovery amount is a determination that stays with the case manager.
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Reasonable Excuse Under the SRC Act: AI Can Structure the Analysis, Not Make the Finding
One test runs through five sections of the SRC Act: whether a claimant who failed to comply had a reasonable excuse. AI can structure that analysis on a de-identified file, sort the facts against the subjective and objective limbs and flag missing evidence. The reasonable-excuse finding, and any suspension or refusal that follows, stays with the human delegate.
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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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Two Doctors Disagree: AI Can Map the Conflict, Not Resolve It
When a treating doctor and an independent examiner disagree, the delegate has to weigh two medical opinions and determine liability on the balance of probabilities. AI can build the comparison so you spend your time on the judgement, not the sorting. Here is a de-identified workflow that keeps the weighing, and the decision, with the delegate.
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AI Can Map a Section 29 Household Services Claim. It Cannot Decide What Is Reasonable
AI can organise a de-identified section 29 household services claim by task, pre-injury contribution, post-injury capacity, household composition, family contribution, disruption and cost. It cannot apply the word reasonable. This guide gives you the evidence map, the prompt and the human decision line.
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AI Can Organise a Section 36 Rehabilitation Assessment. It Cannot Choose the Program
AI can build a de-identified source register, chronology, evidence map and question list for a section 36 rehabilitation assessment under the SRC Act. It cannot conduct the statutory assessment, require an examination, select the assessor or choose the rehabilitation program. This guide maps where the machine stops and the people named by the Act take over.
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AI Can Build the Section 16 Picture, Not Make the Call
Section 16 of the SRC Act pays for medical treatment only where it was reasonable to obtain and the cost is appropriate. That is a judgement, not a fact. This guide gives you the prompts, the Monday workflow and the checklist so AI assembles the picture while a delegated officer makes the call.
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AI and the Reasonable Administrative Action Exclusion: Map the Actions, Keep the Judgement
A practical guide to where AI genuinely helps with a section 5A reasonable administrative action determination, and exactly where the work stops being organisation and becomes human judgement.
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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 and Permanent Impairment: Organise the Evidence, Keep the Judgement
A permanent impairment claim under section 24 lives or dies on the medical evidence. AI can assemble, de-identify and structure that evidence against the approved Guide, and surface the gaps. It cannot assess the impairment or make the determination. Here is the workflow.
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ChatGPT Just Got Better at Health. Mind the Boundary.
On 18 June OpenAI announced a substantial step up in ChatGPT's health intelligence, free to the 230 million people who already ask it health questions every week. Better answers do not move the boundary between information and a clinical decision. Here is what that means for Australian professionals this week.
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AI for Incident Analysis and Leading Indicators: A Human-in-the-Loop WHS Playbook
A practical, human-in-the-loop guide for Australian financial-services WHS teams. Use AI to surface leading indicators across de-identified incident data and to propose ICAM-style contributing factors, while keeping the notifiability decision firmly with a competent person.
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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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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 Week in Review, 8-14 June 2026: A Frontier Model Pulled by Government Order
The week a US directive forced Anthropic to suspend two new frontier models worldwide, plus six verified vendor moves and a repeatable method for turning AI news into Monday actions.
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Claude Model Routing for Regulated Work: Which Model to Use for GRC, WC and HR Tasks
Choosing a Claude model is a governance decision, not a speed decision. Route by capability tier, score the task, and keep accountable review with named people, with worked examples for GRC, workers compensation and HR.
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Build the Knowledge Spine That Stops Generic AI Output
Generic AI output is a context problem, not a prompt problem. Learn how a governed knowledge spine grounds your models in real organisational knowledge, with worked examples for GRC, workers compensation and HR.
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Build a WC Evidence Chronology Tool Without Outsourcing Judgement
A practical pattern for using an LLM to build an offline, de-identified workers compensation evidence chronology tool that organises facts while the delegate keeps every SRC Act decision.
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AI Can Draft Recovery Conversation Scripts, but the Listening Stays Human
A practical guide to using AI to draft motivational-interviewing-informed scripts, talking points and follow-up messages for recovery-at-work conversations. De-identification first, the MI frame in the prompt, and a human reviewer before any words reach an injured employee.
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Prompt Libraries Make WC AI Safer Only When Human Review Comes First
A practical SRC Act article on de-identification, placeholder prompt libraries, file-note drafting and human review controls for workers compensation communications.
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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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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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Treating Practitioner Reports and AI: Where the Workflow Helps and Where It Hurts
AI is a strong summariser of treating practitioner reports and a poor judge of medical evidence. The line between the two is the difference between speed and risk.
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The Incapacity Cross-Check Workflow: AI as a Calculation Auditor
Section 19 calculations are arithmetic-heavy and error-prone. AI shines as a second pair of eyes, not as the primary calculator. Here is the workflow.
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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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ART Review Rights Under the SRC Act: A Practitioner's Map
Review and appeal rights under the SRC Act 1988 changed in October 2024 when the AAT became the Administrative Review Tribunal. A practitioner's map of the three review tiers, the timeframes that apply, and the place AI evidence is taking in workers compensation matters before the ART.
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Custom Projects vs Raw Chats: When to Graduate Your AI Workflow
Raw chat is fine for ideation. For any workflow you run more than twice, Custom Projects pay back fast. Here is the rule for when to graduate.
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Privacy-Safe AI for Regulated Work: A Working Practitioner's Guide
Workers compensation, GRC, HR and clinical roles all sit on regulated data. Using AI well in those roles is not optional. Doing it safely is not optional either. This is the practitioner's guide.
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The De-Identification Toolkit for Case Managers Working With AI
A working toolkit for case managers who use AI inside live claim files. Five identifier categories, a placeholder convention, and a daily desk routine.
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RAG Explained for Non-Engineers: How AI Reads Your Documents
RAG is the architecture behind most enterprise AI tools you will meet in 2026. The acronym hides a simple idea. Here it is, explained in plain English with a working analogy.
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Choosing Claude, ChatGPT, Gemini or Copilot for Your Job
The four main AI tools have meaningfully different strengths in 2026. The right choice depends on your job, not on the marketing. Here is a working professional's decision guide.
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Reading the Reasoning Trail: A Case Note on AI Drafted Determinations
An illustrative case profile that mirrors live ART concerns: when an AI drafted determination cannot be unwound to its underlying reasoning, the determination itself is at risk.
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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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Your First AI Workflow Without a Single Line of Code
You do not need n8n, Zapier or a developer to get genuine productivity from AI workflows. Pick a task. Stitch three prompts together. Save the recipe. Repeat next week.
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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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Prompt Engineering Fundamentals: The 2026 Update for Working Professionals
The 2026 frontier models reward precision more than they did 18 months ago. This is the practical pattern set every working professional should be using now.
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Australian AI Safety Standard: 18-Month Review
Eighteen months in, Australia's voluntary AI Safety Standard has shifted from optional reading to procurement table stakes. Three things worked. Two did not. The next phase is moving towards mandatory.
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