Workers compensation

For a non-catastrophic injury, subsection 29(5) excludes compensation for any week within the 28 days beginning on the date of the injury, unless the relevant authority determines otherwise on the ground of financial hardship or the need to provide for adequate supervision of dependent children. Section 29A applies to catastrophic injury and has no 28-day exclusion and no weekly cap. An authorised person confirms which provision applies. From AI Can Map a Section 29 Household Services Claim. It Cannot Decide What Is Reasonable

No. Comcare's scheme guidance states that the rehabilitation authority's section 36 power does not extend to assessing an employee's need for household services. Relevant authorities have separate powers to arrange and pay for a needs assessment under section 70 for Comcare or section 108F for licensees. A rehabilitation assessment must be taken into consideration but cannot be the sole basis for the household services decision. From AI Can Map a Section 29 Household Services Claim. It Cannot Decide What Is Reasonable

No. Assessing whole person impairment against the approved Guide is a clinical judgement reserved for a suitably qualified medical practitioner, and the determination is a statutory decision for an authorised delegate. AI can organise the evidence, but it cannot decide the percentage or the entitlement and has no standing to. From AI and Permanent Impairment: Organise the Evidence, Keep the Judgement

AI can check transparent arithmetic using verified inputs, but it must not determine the reasonable amount or apply an unverified statutory maximum. The subsection 29(1) weekly maximum is indexed each 1 July and published by Comcare, and the amount also cannot be less than 50 per cent of what the employee pays for the services. The authorised claims manager confirms the current rate, the evidence and the final calculation. From AI Can Map a Section 29 Household Services Claim. It Cannot Decide What Is Reasonable

No. AI can triage a de-identified file to flag that an overlap may exist and build a chronology of the parallel claim, which is useful early screening. The offset or recovery amount is a calculation that turns on the exact heads of damage, the sections engaged and the amounts involved, and it is a determination the case manager makes. An AI-suggested figure should never be relied on as the number. From Preventing Double Payment Under the SRC Act: AI Can Flag the Overlap, Not Calculate the Offset

No. The control principle is that AI may organise information, but people must decide. Suitable duties need current medical evidence, knowledge of real work demands, consultation with the injured employee and review when circumstances change. Authorised people make the decision, and AI cannot replace that judgement. From AI Can Organise Recovery-at-Work Information, but People Must Decide

No. AI can build the analysis on a de-identified file: a chronology, the facts sorted against the subjective and objective limbs, an unable-versus- unwilling read, and a list of missing evidence. The reasonable-excuse finding is an exercise of delegated judgement on the specific facts, and any suspension, refusal or reinstatement that follows is the delegate's decision, recorded in their own reasons. From Reasonable Excuse Under the SRC Act: AI Can Structure the Analysis, Not Make the Finding

No. Section 5A is a chain of human judgements: characterising the condition, weighing employment contribution, classifying each action, and forming a view on whether conduct was reasonable and reasonably done. Those are evaluative calls a delegate is accountable for under the Act. A model that appears to decide them is worse than useless, because it produces a confident answer with no accountable reasoning behind it. From AI and the Reasonable Administrative Action Exclusion: Map the Actions, Keep the Judgement

No. Section 16(1) conditions compensation on the treatment being reasonable for the employee to obtain, and leaves the amount to what the authority determines is appropriate. In practice a properly delegated officer decides both. AI can assemble the picture: the category mapping, the evidence, the cost against the benefit and the gaps. The evaluative weighing and the determination itself stay with the human decision-maker, and a determination made without the delegation is invalid no matter how good the work-up was. From AI Can Build the Section 16 Picture, Not Make the Call

No. AI can prepare and organise the material and draft the referral, but the decision to require an examination under section 57 is a determination the relevant authority must make, and it must comply with the Guide. A model cannot weigh the necessity of the examination, the employee's personal circumstances or the choice of practitioner, and it cannot own a decision that carries a suspension consequence and a right of review. The delegate decides and signs, and a human reviews every AI output first. From Section 57 Examinations: AI Can Build the Referral, Not Make the Call

No. Comcare guidance is clear that medical professionals do not determine liability, and a model has even less standing to. AI can organise and compare conflicting opinions so the differences are visible, but the judgement about which opinion to prefer, and the liability determination under section 14 of the SRC Act, stays with the delegate, made on the balance of probabilities. From Two Doctors Disagree: AI Can Map the Conflict, Not Resolve It

No. The determination under the SRC Act is made by the case manager, and the reconsideration by the reconsideration officer. AI output supports those decisions; it does not make them. The human stays accountable for the regulated act, and that accountability must be documented in the workflow design, not just in policy. From AI Tools in Workers Compensation Claims: Where Value, Where Risk, Where Governance

No. Subsection 36(2) requires the assessment to be made by a legally qualified medical practitioner nominated by the rehabilitation authority, a suitably qualified person other than a medical practitioner nominated by the authority, or a panel of such people. AI can organise de-identified material for the workflow, but it is not the statutory assessor and cannot determine the employee's capability of undertaking a rehabilitation program. From AI Can Organise a Section 36 Rehabilitation Assessment. It Cannot Choose the Program

No. The SRC Act 1988 was written for delegated human decision makers, and decisions under sections 14, 16, 19 and 24 can only be made by an appropriately delegated person. AI can prepare a draft of any of these, but it cannot lawfully make the legal decision itself. From SRC Act and AI Assisted Determinations: A Practitioner Framework

No. Claimant material is sensitive health information and the matter ends in a statutory decision under the SRC Act. The safer pattern is to de-identify everything first, then use an LLM only to build an offline tool tested with synthetic rows, so real claimant data never reaches an external service. From Build a WC Evidence Chronology Tool Without Outsourcing Judgement

Yes, to prepare, never to conduct. AI can draft MI-informed openings, open questions, example reflections and follow-up messages so the human arrives rehearsed rather than improvising. The script is a rehearsal aid, not a teleprompter. Reflective listening cannot be pre-drafted, only rehearsed, and every draft needs human review first. From AI Can Draft Recovery Conversation Scripts, but the Listening Stays Human

Yes, for the reading task. AI structures long reports into diagnosis, history, treatment, prognosis, and recommendations, surfaces inconsistencies across reports, and reduces cognitive load on entry tasks. It is a navigation aid only. The first read is end to end, every time, and the summary never replaces the source report. From Treating Practitioner Reports and AI: Where the Workflow Helps and Where It Hurts

Yes. Claim files hold names, claim numbers, dates of birth and detailed medical and personal information. None of that should go into an AI tool. Replace identifiers with placeholders, and only ask the model to work on the de-identified structure of the opinions. The comparison AI produces is a working aid, and the delegate applies it back to the real file. From Two Doctors Disagree: AI Can Map the Conflict, Not Resolve It

Yes. Reconsideration is the gateway. ART review of a primary determination requires a reconsideration first. Going straight from a primary determination to the ART is procedurally not available. The reconsideration produces a reviewable decision, which is the artefact that triggers the next review tier. From ART Review Rights Under the SRC Act: A Practitioner's Map

Yes, always and first. Replace the name with [CLAIMANT_NAME], the claim number with [CLAIM_NUMBER] and date of birth with [DATE_OF_BIRTH], mask other identifying detail, and keep the re-identification key separate. Use only an approved tool for sensitive data, never a public consumer model where input may be retained. From AI and Permanent Impairment: Organise the Evidence, Keep the Judgement

Yes. The public profile of a tool is not the same as a documented privacy assessment, so the toolkit applies regardless of vendor. Even where a tool claims no data leaves your environment, de-identify unless inference location, logging, training use, and Privacy Impact Assessment questions are all confirmed. The cost of de-identifying is low; being wrong is high. From The De-Identification Toolkit for Case Managers Working With AI

No. Where an examination is carried out, the written assessment under subsection 36(8) states the employee's capability of undertaking a rehabilitation program and, where appropriate, the kind of program. A section 37 determination that the employee should undertake a program is made separately by the rehabilitation authority, which must have regard to the section 36(8) assessment and the other matters listed in subsection 37(3). From AI Can Organise a Section 36 Rehabilitation Assessment. It Cannot Choose the Program

Broadly, yes, for the same injury. Under the framework in sections 46, 48 and 50, once a person recovers damages from a third party for the injury, the relevant authority can recover the compensation it has paid and further compensation is affected, with a limited exception for damages recovered for non-economic loss under a section 45 election. The precise effect depends on the facts, so the guidance and the Act should be read directly. From Preventing Double Payment Under the SRC Act: AI Can Flag the Overlap, Not Calculate the Offset

Clause 3.7 records that the documents a decision-maker is required to give the Tribunal on commencement of a review may include reports that fall within the scope of the Practice Direction. Where a party wants to place particular reliance on such a report but it does not carry the information in clauses 3.1 to 3.5C, the party should consider whether additional information should be sought from the expert and given to the Tribunal. The practical effect is that a report written well before any review is later read against the standard. From The Medical Report Now Has to Declare Its AI

No. The Tribunal is not concerned with whether AI tools were used in drafting. It is concerned with whether the determination is supported by evidence, whether the delegate can articulate the reasoning, and whether procedural fairness was observed. Where the reasoning trail is intact, AI use is unproblematic and effectively invisible at review. From Reading the Reasoning Trail: A Case Note on AI Drafted Determinations

Set up a project space with a tight system prompt, a reference pack including the SRC Act 1988 and the review report, and a guardrail file. Then run four prompt patterns: triage the recommendations, compare them section by section, map operational impact, and scaffold a submission for legal to finish. From Leveraging AI to assist dissecting the SRC Act Review

AI can take de-identified medical reports and build a dated chronology tagged by author and body region, map each report to the approved Guide's structure, and flag gaps or inconsistencies. It can also draft a neutral file summary once a person has done the thinking. Every output is a checklist to verify, never a finding. From AI and Permanent Impairment: Organise the Evidence, Keep the Judgement

Claim material is sensitive information. Strip names, claim numbers, dates of birth and any identifier before a single line goes near a model, and work in placeholders such as [CLAIMANT_NAME], [CLAIM_NUMBER] and [DATE_OF_BIRTH]. If you cannot de-identify it, it does not go in. This is the precondition for everything else. From AI and the Reasonable Administrative Action Exclusion: Map the Actions, Keep the Judgement

Reports carry identifiers in letterheads, signature blocks, practice details, and file references. Apply the five-category de-identification toolkit in full, using placeholders like TREATING_PRACTITIONER, PRACTICE, CLAIMANT_NAME, CLAIM_NUMBER, INJURY_DATE, and CONDITION consistently. Never paste a report into any tool that has not been approved by your scheme operator. From Treating Practitioner Reports and AI: Where the Workflow Helps and Where It Hurts

Never enter real names, claim numbers, dates of birth, employee IDs, provider names, exact dates or identifying injury details into a public or unapproved AI tool. Use fictional scenarios and [PLACEHOLDER] fields. Removing a name is not enough if the remaining facts can still identify the person. If context cannot be written without identifying detail, do not proceed. From AI Can Draft Recovery Conversation Scripts, but the Listening Stays Human

De-identify before the model ever sees the matter, treating it as a fixed step, not a judgement under time pressure. Use placeholders like [CLAIMANT_NAME], [CLAIM_NUMBER] and [DATE_OF_BIRTH], and neutral tags such as Treating Practitioner A. Raw fields never leave the local environment; a human maps placeholders back at review time. From Build a WC Evidence Chronology Tool Without Outsourcing Judgement

Build the library from fictional scenarios, de-identified chronologies and placeholder fields rather than real claim material. Tell each prompt what not to do, ban legal conclusions, and require source separation. The second, more important control is that a human reviews every output before it is saved, sent or relied on. From Prompt Libraries Make WC AI Safer Only When Human Review Comes First

Review whenever new medical evidence arrives, at agreed checkpoints, and when duties, symptoms or concerns change. Ask whether the plan is still supported by current evidence, whether duties remain safe and genuinely available, whether consultation raised concerns, and whether the reviewer recorded changes made to AI-assisted drafts. From AI Can Organise Recovery-at-Work Information, but People Must Decide

A neat timeline is not evidence until a human checks it against the source records. Add an export gate that blocks export until a reviewer confirms in a required note that the source records have been checked. The export must carry a disclaimer that the chronology is a preparation artefact, not a determination. From Build a WC Evidence Chronology Tool Without Outsourcing Judgement

It removes the sorting so you can spend your time on the weighing. Working from a de-identified file, AI can lay out what clinical question each opinion addressed, the history and evidence each relied on, where the opinions agree, where they diverge, and where the record is missing something. That structured comparison makes the real points of difference obvious, which is where the delegate's judgement is best spent. From Two Doctors Disagree: AI Can Map the Conflict, Not Resolve It

Comcare's scheme guidance points to the Clinical Framework for the Delivery of Health Services, published by WorkSafe Victoria, as the lens for the cost-versus-benefit weighing, and notes the Administrative Review Tribunal has supported its use as a relevant consideration in determining reasonableness. Its five principles cover measured effectiveness, a biopsychosocial approach, empowering the injured person, goals focused on function and return to work, and the best available research evidence. From AI Can Build the Section 16 Picture, Not Make the Call

Where AI assisted the original determination, the file note should record its role, the reconsideration reasons should engage with it, and the ART evidence pack should include the AI-assisted artefacts. The pattern that survives review is AI in the analysis, a human in the decision, documented in the reasoning trail. From ART Review Rights Under the SRC Act: A Practitioner's Map

Add a short file note paragraph recording that AI was used, that inputs were de-identified, and that the case manager reviewed and edited the draft. Silence is not defensible. A clear note signals discipline and is read positively at review, while the absence of such a note is read negatively. From Reading the Reasoning Trail: A Case Note on AI Drafted Determinations

De-identification is the default for every workflow where claim data leaves the scheme's controlled environment. Remove full names, claim numbers, specific addresses, employer identifiers, and diagnoses linked to identifiers. Use stable internal identifiers the case manager can re-attach afterwards. This is the single highest-leverage control across the entire claims workflow. From AI Tools in Workers Compensation Claims: Where Value, Where Risk, Where Governance

No prompt sent to any external AI tool may contain a claimant name, claim number, date of birth, exact address, treating practitioner name, or employer reference. Replace them with placeholders such as CLAIMANT_NAME, CLAIM_NUMBER, CONDITION and TREATING_PRACTITIONER. This is treated as a control, not a guideline, every single time. From SRC Act and AI Assisted Determinations: A Practitioner Framework

Make the determination on the evidence and record the divergence in the file note, capturing the model's prediction, your view, and the basis for the difference. The override is logged in an override register, keeping the reasoning trail intact and protecting every individual determination while also generating data that improves the model. From Predictive Analytics and Claims Triage: A Risk Analysis for Scheme Operators

Use a consistent convention: square brackets, capital letters, no spaces, so AI outputs return in a form you can find and replace at the end. Common placeholders include [CLAIM_NUMBER], [CLAIMANT_NAME], [CONDITION], [INJURY_DATE], and [TREATING_PRACTITIONER]. Build any additional placeholders on the same pattern so each is self-explanatory. From The De-Identification Toolkit for Case Managers Working With AI

Name the four elements of the MI spirit, partnership, acceptance, compassion and evocation, and name OARS: open questions, affirmations, reflective listening and summaries. Impose constraints: no persuasion or pressure, no medical advice or recovery predictions, no commentary on liability or claim outcomes, plain Australian English. Unconstrained models default to upbeat salesmanship, the opposite of acceptance. From AI Can Draft Recovery Conversation Scripts, but the Listening Stays Human

AI should not infer attitude, motivation or credibility from an employee's language, or summarise concerns as resistance or non-compliance unless the evidence genuinely supports that and the decision-maker has considered context. Use AI to draft neutral prompts about whether duties are safe and sustainable, recognising section 37 considerations. From AI Can Organise Recovery-at-Work Information, but People Must Decide

Write a brief one-paragraph file note covering four things: the case manager calculated the figure manually, cross-checked it against an AI tool with de-identified inputs, the figures matched or any discrepancy was resolved, and the manual figure is authoritative. The note is not optional and is defensible at audit and review. From The Incapacity Cross-Check Workflow: AI as a Calculation Auditor

The case manager should redo the calculation independently, even where the AI got it right, so the figure is genuinely the case manager's. AI assisted maths accepted without the delegate being able to explain it creates calculation opacity. Use the AI result only as a cross-check, with the case manager's figure being authoritative. From Reading the Reasoning Trail: A Case Note on AI Drafted Determinations

No. Clause 1.11 says a failure to comply may have consequences for the weight the Tribunal gives to the expert's evidence. The note under it records that the Tribunal is not bound by the rules of evidence relating to opinion evidence, citing section 52 of the Administrative Review Tribunal Act 2024, and that the Tribunal will determine the weight given to any evidence before it. The report is not excluded. It can quietly carry less weight. From The Medical Report Now Has to Declare Its AI

Yes. Comcare's guidance on the amendments confirms that requests to undergo medical examinations under section 57 of the SRC Act are determinations that are reviewable and can be subject to review by the Administrative Review Tribunal, following changes that commenced on 14 June 2024. Because it is a determination for the purposes of section 60, notice of it must be given in writing under section 61 with the terms of the determination and the reasons for it, which raises the bar on how the referral is documented. From Section 57 Examinations: AI Can Build the Referral, Not Make the Call

The evidence is promising but thin. A 2017 Canadian trial of 728 claimants found the MI group transitioned to modified duties more often with roughly half the benefit recurrence. A 2021 mapping review found a large research gap, and the 2022 MI-NAV trial cut sickness absence by about seven days, a difference that was not statistically significant. From AI Can Draft Recovery Conversation Scripts, but the Listening Stays Human

No. The case manager owns the calculation and runs the maths fully and personally, because section 19 is a delegated decision. AI is well suited to finding discrepancies between two computed figures, so it audits the manual figure rather than producing it. The manual figure stays authoritative every time. From The Incapacity Cross-Check Workflow: AI as a Calculation Auditor

No. The AI drafts the scaffold only: a submission outline, points keyed to recommendation numbers, evidence inputs needed, and points requiring legal advice. Government relations and external legal counsel finish the submission. A regulator can usually tell when a position came from the model rather than the organisation. From Leveraging AI to assist dissecting the SRC Act Review

The five categories are direct claimant identifiers, indirect identifiers, treating practitioner identifiers, third-party identifiers, and free-text leakage. They are deliberately broader than the strict legal definition of personal information, because the goal is robustness rather than minimum compliance. Replace each with a standard bracketed placeholder before pasting anything. From The De-Identification Toolkit for Case Managers Working With AI

Summary drift can subtly distort the practitioner's view, case managers may start reading the summary instead of the report, and privacy creep can leave identifiers in metadata. Audit failure modes include confirmation summarisation, compression of disagreement between treating and IME views, and loss of clinical specificity. Going back to the source is the key control. From Treating Practitioner Reports and AI: Where the Workflow Helps and Where It Hurts

Six categories arise in practice: procedural fairness drift, training data bias, reasoning trail dilution, vendor opacity, calibration decay, and concentration of effect where one model touches every claim. Each is real even where the model is good, and several only become visible in aggregate or once something goes wrong. From Predictive Analytics and Claims Triage: A Risk Analysis for Scheme Operators

They stop a person being compensated twice for the same injury. Comcare guidance SRC344 groups them into three overlaps: damages recovered from a third party at common law under sections 46, 48 and 50, an overlapping state or territory workers compensation entitlement under section 118, and compensation under a state or territory scheme that is not workers compensation under section 119. Each has its own recovery mechanism. From Preventing Double Payment Under the SRC Act: AI Can Flag the Overlap, Not Calculate the Offset

Five steps. Calculate the section 19 figure manually. De-identify the inputs with placeholders. Prompt the AI to compute the figure step by step. Compare the manual and AI figures. Document both on file, recording that the manual figure is authoritative. It adds five to ten minutes. From The Incapacity Cross-Check Workflow: AI as a Calculation Auditor

Review runs in three tiers. Tier 1 is internal reconsideration under section 62, carried out by an uninvolved officer. Tier 2 is a merits review by the Administrative Review Tribunal under section 64. Tier 3 is a Federal Court appeal on a question of law under section 44 of the ART Act. From ART Review Rights Under the SRC Act: A Practitioner's Map

Reconsideration of a primary determination should generally be requested within 30 days of the determination being notified. An ART application must generally be lodged within 60 days of the reviewable decision being received. A Federal Court appeal must be lodged within 28 days. Extensions are available only in limited circumstances. From ART Review Rights Under the SRC Act: A Practitioner's Map

Gate one is senior management reviewing the high-impact recommendation triage before further analysis runs. Gate two is external or in-house legal counsel reviewing the section-by-section statutory comparison before the transitional and submission patterns run. Skipping either gate is the most common failure mode. From Leveraging AI to assist dissecting the SRC Act Review

It cannot catch inputs that are wrong on file; it will compute the wrong answer correctly. It cannot resolve legal characterisation, such as whether a payment is part of normal weekly earnings. It cannot make the choice of which available figures to use. The case manager remains responsible for these. From The Incapacity Cross-Check Workflow: AI as a Calculation Auditor

The tool organises facts: it orders events by date, tags evidence types, references sources, flags gaps and drafts review questions. The delegate decides outcomes under the SRC Act, including liability under section 14, injury under section 5A, disease under section 5B, incapacity, impairment, treatment and rehabilitation. From Build a WC Evidence Chronology Tool Without Outsourcing Judgement

The ART conducts an independent merits review and can affirm the reviewable decision, vary it, set it aside and substitute its own decision, or set it aside and remit the matter to the determining authority with directions. There are some limits on substitution, notably for certain rehabilitation decisions. From ART Review Rights Under the SRC Act: A Practitioner's Map

Use only an approved tool and data pathway. De-identify before upload, using placeholders such as [CLAIMANT_NAME], [CLAIM_NUMBER], [CONDITION] and [DATE_OF_INJURY]. Removing a name alone is not enough if dates, providers, locations or unusual combinations of facts could still identify the person. From AI Can Organise a Section 36 Rehabilitation Assessment. It Cannot Choose the Program

Subsection 4(1) defines household services as services of a domestic nature, including cooking, house cleaning, laundry and gardening services, that are required for the proper running and maintenance of the employee's household. Whether a claimed task meets that definition depends on its nature and purpose, and the check belongs to the authorised decision-maker, not to a model. From AI Can Map a Section 29 Household Services Claim. It Cannot Decide What Is Reasonable

Do not enter real claimant names, claim numbers, employee IDs, provider names, exact dates, locations or medical details into unapproved AI tools. Use fictional examples and placeholder fields. Removing a name alone is not enough, because other facts can still identify the person. From AI Can Organise Recovery-at-Work Information, but People Must Decide

Four things, walked through in order: the legal test that applied (which SRC Act section and threshold), the evidence considered, the reasoning connecting that evidence to the test, and the conclusion that issued. AI drafting can support every step but cannot replace any of them. The delegate must reproduce the trail on demand. From Reading the Reasoning Trail: A Case Note on AI Drafted Determinations

It sorts incoming claims by likely complexity, expected duration, or risk of dispute, supporting faster triage, load balancing, earlier intervention on escalating claims, and cleaner management reporting. A handful of Australian schemes run production deployments and many more are piloting, so the technology is now business as usual in pockets. From Predictive Analytics and Claims Triage: A Risk Analysis for Scheme Operators

De-identification means more than removing a name. Claim numbers, employee IDs, provider names, exact dates, locations, unusual role details, injury facts, medical histories and combinations of facts can still identify a person. Use placeholder fields and fictional examples unless the tool, workflow and data handling have been formally approved. From Prompt Libraries Make WC AI Safer Only When Human Review Comes First

Comcare guidance is clear that being dissatisfied with the terms of a request does not amount to a reasonable excuse, and neither does a difficulty that arises only from the claimant's personal preference, such as choosing to relocate away from where the requirement can be met. Practical difficulties that are objectively reasonable, such as a remote location, an accessibility need or not receiving the request, are more likely to qualify. From Reasonable Excuse Under the SRC Act: AI Can Structure the Analysis, Not Make the Finding

Three things. The treatment must have been obtained in relation to the compensable injury, it must have been reasonable for the employee to obtain in the circumstances, and compensation is of such amount as the authority determines is appropriate to that treatment. Before any of that, the request must fall within the definition of medical treatment in section 4(1). Something outside that definition is not section 16 medical treatment at all. From AI Can Build the Section 16 Picture, Not Make the Call

Section 5A excludes compensation for an injury suffered as a result of reasonable administrative action taken in a reasonable manner in respect of the employee's employment. The analysis runs in order: first whether there is a disease under section 5B, then whether any employment causative factor was reasonable administrative action across four questions, then whether the injury was suffered as a result of that action. From AI and the Reasonable Administrative Action Exclusion: Map the Actions, Keep the Judgement

Clause 3.5B requires an expert preparing a written report for a Tribunal proceeding to state whether the report includes content generated by using Generative AI. Clause 3.5C requires, where it does, that the expert clearly identify the AI content and the applications used to generate it, and certify that they have personally checked all of it, including research and other material cited in support, and are satisfied it is all accurate and reliable. Clause 3.5A defines Generative AI and names ChatGPT, Gemini, Microsoft Copilot, Perplexity, Claude, Grok and DeepSeek AI as examples. From The Medical Report Now Has to Declare Its AI

Comcare's material on the Guide states that relevant authorities must consider an employee's circumstances, rely as much as possible on relevant information from the injured employee's treating practitioner, and seek and take into account the employee's views about the selection of the person or people who will conduct the assessment or examination. Those are judgement calls about a specific person, which is exactly why they stay with the delegate and are documented in the decision record. From Section 57 Examinations: AI Can Build the Referral, Not Make the Call

Six controls: a written model description before deployment, ongoing calibration monitoring reviewed quarterly at minimum, an override register reviewed for patterns, bias monitoring across cohorts, reasoning trail integration in file notes, and a Privacy Impact Assessment covering training data, production flow, and output, reviewed annually. From Predictive Analytics and Claims Triage: A Risk Analysis for Scheme Operators

It is the ground a claimant relies on when they fail to comply with a requirement, such as attending an examination or undertaking a rehabilitation program. Comcare guidance SRC345 sets a combined test: the delegate weighs both the subjective grounds the claimant advances and whether those grounds are objectively reasonable. The excuse must show the person was unable to comply, not merely unwilling, and it requires more than a rational explanation. From Reasonable Excuse Under the SRC Act: AI Can Structure the Analysis, Not Make the Finding

Use four stages. Select an approved prompt from the library. Insert only de-identified placeholder facts or fictional scenario facts. Review the output against source documents, legislation, policy and tone requirements. Then record the AI assistance, reviewer, sources checked and changes made before the content is saved or sent. From Prompt Libraries Make WC AI Safer Only When Human Review Comes First

Under section 57 of the SRC Act, a delegate can require an employee to undergo an examination by a medical practitioner where additional medical information or specialist opinion is needed to make a decision. The resulting independent opinion often sits alongside the treating doctor's report, and the two can disagree. A decision to require a section 57 examination is itself a reviewable determination for the purposes of section 60. From Two Doctors Disagree: AI Can Map the Conflict, Not Resolve It

Open the source document, save a clearly marked working copy, run a five-category Find and Replace sweep for names, dates, locations, practitioner details, and third parties, then visually scan paragraph by paragraph for anything missed. Once clean, use the working copy in the approved tool while the original stays untouched in the source system. From The De-Identification Toolkit for Case Managers Working With AI

Administrative action is directed specifically at the employee and their employment relationship, such as a performance appraisal, counselling, suspension or disciplinary action under section 5A(2). Operational action, a direction about how and when to perform the work itself, is not reasonable administrative action, and any resulting injury is compensable. The distinction decides whether section 5A is even in play. From AI and the Reasonable Administrative Action Exclusion: Map the Actions, Keep the Judgement

Section 118 deals with an overlap between SRC Act compensation and state or territory workers compensation for the same injury, and Comcare may recover the amount it paid. Section 119 deals with an overlap between SRC Act compensation and a state or territory scheme that pays compensation other than workers compensation, such as a motor accident scheme, where Comcare is generally liable only for the excess. From Preventing Double Payment Under the SRC Act: AI Can Flag the Overlap, Not Calculate the Offset

Frame the question and identify the legal test. De-identify the input with placeholders. Generate a structured draft. Map the draft to the actual claim file line by line. Then issue the decision, applying the legal test and signing as the delegated decision maker. AI assists only at step three. From SRC Act and AI Assisted Determinations: A Practitioner Framework

Triage with the full report first, then generate a structured summary as a navigation aid. Cross-check the summary against the original and correct any drift. Use the summary as an aid, not a replacement, when deciding under section 16 or section 14, and capture medical opinion in the practitioner's own words from the source. From Treating Practitioner Reports and AI: Where the Workflow Helps and Where It Hurts

Section 57A of the SRC Act requires Comcare to prepare a Guide for Arranging Rehabilitation Assessments and Requiring Examinations. The object of the Guide is to support ethical, transparent and accountable decision making in relation to arranging a rehabilitation assessment of an employee under subsection 36(1), or requiring an employee to undergo an examination under subsection 36(3) or 57(1), including appropriate consideration of the employee's personal circumstances. It is a legislative instrument, compliance is mandatory, and it applies to section 36 and section 57 determinations made on or after 30 October 2024. From Section 57 Examinations: AI Can Build the Referral, Not Make the Call

Section 24 generally requires the permanent impairment to reach at least 10 per cent whole person impairment, with specific exceptions for matters such as hearing loss and loss of the use of fingers, toes, or the sense of taste or smell. The 10 per cent line is legal; whether the evidence reaches it is a clinical judgement. From AI and Permanent Impairment: Organise the Evidence, Keep the Judgement

Three classes most often. Transposition errors, such as numbers in the wrong order or misplaced decimal points. Statutory interpretation errors, often involving section 8 normal weekly earnings interacting with allowances or prescribed amounts. Sequencing errors, where the order adjustments are applied matters for the legal correctness of the determination. From The Incapacity Cross-Check Workflow: AI as a Calculation Auditor

An unsafe prompt invites real claim information, asks AI to form a conclusion, and risks claimant-facing language without legal review. A safer prompt is narrower: it uses fictional information and placeholder fields, bans liability recommendations, separates evidence, gaps, assumptions and actions, and marks the output as draft-only for human review. From Prompt Libraries Make WC AI Safer Only When Human Review Comes First

Comcare guidance sets out notification duties. A claimant or dependant who decides to pursue a common law claim for damages against a third party must tell the relevant authority in writing as soon as practicable and within 7 days of becoming aware of the claim, and once damages are recovered must notify the authority in writing of the amount within 28 days. Recovering damages for the same injury affects the right to further SRC Act compensation. From Preventing Double Payment Under the SRC Act: AI Can Flag the Overlap, Not Calculate the Offset

Subsection 29(2) requires the decision-maker to have regard to five matters: the employee's pre-injury and post-injury contribution to household services, the people living in the household with their ages and needs, those members' contribution before the injury, what household or family members might reasonably be expected to provide for themselves and the employee after the injury, and the need to avoid substantial disruption to their employment or other activities. The subsection is expressed without limiting other matters, so other relevant circumstances may also be considered. From AI Can Map a Section 29 Household Services Claim. It Cannot Decide What Is Reasonable

Everything identifying: the claimant's name, claim number, date of birth and any detail that could identify them, replaced with placeholders such as [CLAIMANT_NAME], [CLAIM_NUMBER] and [CONDITION]. De-identification is mandatory before any claim material reaches a model, and the material goes only into a tool your organisation has approved for claims work. If no tool is approved, that approval comes first. From AI Can Build the Section 16 Picture, Not Make the Call

The reviewer verifies every extracted statement against its source, corrects dates and context, confirms de-identification, applies the current Act and Guide, preserves the employee-view and assessor-selection steps, and ensures only qualified and authorised people perform the assessment and determination functions. From AI Can Organise a Section 36 Rehabilitation Assessment. It Cannot Choose the Program

The whole person impairment assessment against the Guide, weighing conflicting examiner evidence, combining multiple impairments by the combined values method, section 27 non-economic loss assessment, and the section 24 determination all stay human. A model can flag divergence, but conclusions, percentages and the entitlement decision must be attributable to qualified people. From AI and Permanent Impairment: Organise the Evidence, Keep the Judgement

Enough for the report to answer clause 3.1 on its face: the questions or issues the examiner is asked to address, and a reference to the documents and materials provided. Comcare's guidance on engaging a legally qualified medical practitioner already says proper instructions, including the appropriate scope of the examination, reduce the risk of the examiner straying into areas irrelevant to the claim. Adding a request that the examiner address Generative AI use expressly costs a sentence and closes the gap before it opens. From The Medical Report Now Has to Declare Its AI

Never send unredacted claim data to an undocumented tool, treat an AI summary as a substitute for the source documents in a load-bearing decision, let an AI-drafted determination letter leave without case manager review, act on AI-flagged patterns without verifying them against sample claims, or run AI-influenced decisions with no file note record. From AI Tools in Workers Compensation Claims: Where Value, Where Risk, Where Governance

AI must not weigh competing medical evidence, apply the section 16 reasonableness test, perform causation analysis under section 14 and section 5B, or judge credibility on disputed history. These require human judgement with the rigour the SRC Act expects. Any AI output that opines on reasonableness or causation is out of scope. From Treating Practitioner Reports and AI: Where the Workflow Helps and Where It Hurts

A person goes and fills them. If the file holds no functional measure, no stated goal or no current treating practitioner review, the answer is a request back to the practitioner, not a model estimate. The work-up is valuable precisely because it names the gaps instead of papering over them. Asking the model to fill a gap converts missing evidence into invented evidence. From AI Can Build the Section 16 Picture, Not Make the Call

Gather combined evidence first: the current medical certificate, treating practitioner guidance, supervisor input on real and available duties, and employee feedback, plus review history. Only then use AI to draft a view of possible duties, restrictions, hazards, review questions and evidence gaps for human checking. From AI Can Organise Recovery-at-Work Information, but People Must Decide

Do not paste sensitive internal or Cabinet-in-confidence material into a shared endpoint without confirming data classification rules. Do not let AI draft the submission itself. Do not assume the model has read the report; enforce the citation rule. And do not run the workflow once and stop, since consultation is iterative. From Leveraging AI to assist dissecting the SRC Act Review

Capture the AI's role at the time of decision, not retrospectively. Record which tool was used, what data was sent to it, what the output was, and how the case manager engaged with it. Retrospective reconstruction of the AI's role is significantly harder than capture at the moment of decision. From AI Tools in Workers Compensation Claims: Where Value, Where Risk, Where Governance

Most scheme operators use a four-line standard: the AI tool and version used, the specific purpose the AI served, confirmation that inputs were de-identified, and a statement that the case manager reviewed and edited the output so the issued text reflects their own reasoning. Four lines, defensible at audit. From SRC Act and AI Assisted Determinations: A Practitioner Framework

Three conditions justify pausing the model: calibration drift exceeding tolerance so predictions are no longer reliably informative, a systematic bias finding that is not promptly addressable, and vendor changes to the underlying behaviour that the operator has not yet assessed. A paused model can be switched back on once issues are resolved. From Predictive Analytics and Claims Triage: A Risk Analysis for Scheme Operators

Avoid AI drafting for significant degree disease claims under section 5B, credibility-driven determinations, and determinations involving the interaction of multiple Act provisions such as sections 14, 16, 19 and 24 together. In these, review cost outweighs drafting savings. AI is still useful for narrower sub-tasks like summarisation. From SRC Act and AI Assisted Determinations: A Practitioner Framework

The Guide for Arranging Rehabilitation Assessments and Requiring Examinations 2024 requires the rehabilitation authority to first consider whether existing information is sufficient. If it is insufficient or inconsistent, further information or clarification should be sought from the employee's treating practitioner, and the authority should rely on the treating practitioner as much as possible before involving an independent assessor. The authorised person applies the Guide to the circumstances and records the decision. From AI Can Organise a Section 36 Rehabilitation Assessment. It Cannot Choose the Program

Re-identify only at the final write step, never as an intermediate one. All review and editing happens with placeholders intact, which keeps any discussion privacy safe. When ready to write the final text, run a controlled find and replace from placeholders back to real values inside your case management system, not in the AI tool. From The De-Identification Toolkit for Case Managers Working With AI

AI operates across five production workflows in Australian schemes: intake and initial triage, decision support on liability, communications drafting, document analysis and case file review, and quality assurance with pattern detection. Each carries genuine value alongside specific risks, so each needs its own governance baseline rather than a single blanket control. From AI Tools in Workers Compensation Claims: Where Value, Where Risk, Where Governance

SRC345 applies the same concept across sections 36(4), 37(7), 57(2), 58 and 118. Suspension for failing a section 36 rehabilitation examination, a section 37 program or a section 57 medical examination is made under sections 36(4), 37(7) or 57(2) and is a determination. A reasonable-excuse assessment on a refusal to deal with a claim under section 58, or a suspension under section 118, is not a determination. From Reasonable Excuse Under the SRC Act: AI Can Structure the Analysis, Not Make the Finding

Three provisions generate most difficult calls. Section 36 covers assessing an employee's capability of undertaking a rehabilitation program. Section 37 covers providing rehabilitation programs and considers the employee's attitude. Section 40 places a duty on the employer to take all reasonable steps to provide suitable employment. Conversations about what counts as suitable are where trust is most easily lost. From AI Can Draft Recovery Conversation Scripts, but the Listening Stays Human

Block terms that imply a determination the delegate has not made: accepted, rejected, liable, unreasonable and non-compliant. They suggest decisions reserved under sections 14 and 5A. Use neutral alternatives instead, such as event recorded pending review, gap or question flagged for delegate, and management action flagged for s5A review. From Build a WC Evidence Chronology Tool Without Outsourcing Judgement

AI can format notes but must not become the source of truth. A reviewer must verify that every factual statement is traceable to a source document, that SRC Act references and review rights are accurate, and that no legal or medical conclusion has been invented. These are requirements AI cannot be left to approximate. From Prompt Libraries Make WC AI Safer Only When Human Review Comes First

Because the review pathway differs. A suspension under sections 36(4), 37(7) or 57(2) is a determination that can be reconsidered and then reviewed by the Administrative Review Tribunal, so the reasons must withstand that scrutiny. A decision under sections 58 or 118 is not a determination and is not reconsidered, but it can be challenged by judicial review, so procedural fairness and a clear written record still matter. From Reasonable Excuse Under the SRC Act: AI Can Structure the Analysis, Not Make the Finding

The review produced 124 recommendations, not legislation. Submissions, consultation forums and stakeholder input happen on the recommendation set, not the bill. An employer who waits for the bill is six to twelve months too late, so forming a coherent organisational position during consultation is the priority. From Leveraging AI to assist dissecting the SRC Act Review

AI tools tend to write with assertive, confident prose that reads well at the desk but can read as overstatement at review. Over-confident wording that asserts more than the evidence supports is a long-standing review risk. Every confident assertion must be earned by evidence on file, or the paragraph should be rewritten. From Reading the Reasoning Trail: A Case Note on AI Drafted Determinations

The reasonableness test is not prescriptive. There may be more than one reasonable way to take an action, and the question is whether what was done was reasonable in the circumstances. That is a contextual, evidence-weighing judgement that depends on what the employer knew at the time and on the particular employee. A determination has to survive reconsideration and Administrative Review Tribunal review on the strength of the human reasoning. From AI and the Reasonable Administrative Action Exclusion: Map the Actions, Keep the Judgement