AI Complaint Handling Policy: A Practical Template for Australian Teams
- Shiv Martin
- 3 hours ago
- 8 min read
A lot of complaints policy work in Australia is being done using policy guidance that was written before AI mattered. The NSW Government model policy, the ACNC template, the Victorian Ombudsman's model complaint handling policy. These are great documents to guide complaints management. Many organisations have adapted them well. None of them address AI.
What I have been hearing from complaints officers and dispute resolution teams over the past year is variations of the same question. Their existing policy is fine in principle but silent on practice: silent on AI-drafted submissions, silent on AI use disclosure, silent on verifying AI-generated case references, silent on what to do when a vulnerable complainant has used AI to articulate something they could not have written on their own. The policy was not written for the situation the team is now in. The teams are now in a situation where they are finding themselves increasingly buried in AI generated correspondence.
This page covers the practical updates a complaint handling policy needs to make sense in the AI era. I also provide a suggested template to my clients which I am happy to share with you on request. It is a practical, usable AI Complaint Handling Policy that public sector, Ombudsman, tribunal and regulatory teams can take, adapt and run as their own. It is not a fill-in-the-blanks document. It is a working policy you can use to update you existing policies this week.
The existing policy is fine in principle but silent on practice. The policy was not written for the situation the team is now in. That is, buried in AI generated correspondence.
What does a complaint handling policy need to say about AI?
A complaint handling policy that addresses AI does not need to be a separate document. In most cases, the better approach is to update the existing complaints policy with AI-specific provisions in the right places, rather than create a parallel AI policy that sits alongside. It is important not to treat a complaint or complainant differently for the only reason that they used AI. That is likely to cause risks for an organisation.
If you are considering updates to your complaints management policies, there are seven provisions worth thinking about. Not every organisation will need all seven, and not every organisation will need them at the same level of detail. The downloadable template below sets out workable wording for each, which your team can adopt as-is or adapt to your operating context.
The seven provisions are:
Scope and definitions: what the policy means by AI, and what kinds of AI use are covered.
AI use disclosure: whether and how complainants are asked to disclose AI assistance, and what the team does with that disclosure. Is it needed at all?
Verification of AI-generated material: how the team handles AI-drafted citations, references and quantitative claims.
Procedural fairness in AI-influenced matters: how AI use by one party affects the team's obligations to all parties.
Privacy and confidentiality of AI-influenced complaint information: how AI use changes (and does not change) the team's privacy obligations.
Staff use of AI in complaint handling: what the team's own staff are permitted, encouraged or restricted from using AI for.
Training and review: how the policy stays current as AI tools and stakeholder behaviour change.
The remainder of this article walks through each provision at a practical level. The downloadable template provides the actual policy wording.
How does a policy address AI use disclosure?
This is the question that comes up first in almost every policy conversation. Should we ask complainants to tell us if they have used AI to prepare their submission?
In most contexts, the answer is yes, but the framing matters. A disclosure question that reads "Have you used artificial intelligence to prepare any part of this complaint?" produces almost no useful information. Many people will not know how to answer it. They used ChatGPT to summarise their emails but typed the rest themselves, or they used Google Translate, which is also AI. Others will simply not answer at the level the question is asking about.
A more useful disclosure question is one that names specific assistance the team needs to know about. The template provides wording along the lines of "If any part of this complaint was prepared with significant assistance from a generative AI tool (for example, ChatGPT, Claude, Copilot, Gemini), please let us know which sections so we can review them with appropriate care." This wording does three things: it names common tools so the complainant knows what is being asked, it signals that disclosure is for accuracy support rather than punishment, and it gives the team something actionable in the response.
The point of disclosure is not to disadvantage complainants who used AI. It is to give the team useful context so they can verify specific material if needed. The policy provision should make that purpose explicit.
How does a policy address verification of AI-generated material?
The most documented AI risk in complaint handling is fabricated case citations. AI tools sometimes generate plausible-looking legal authorities, statutory references or precedent cases that do not exist. This is a well-known problem in the legal profession and it has appeared in Australian tribunal matters often enough to be a practical concern.
The policy provision worth having is not a ban on AI-generated material. It is a verification requirement: any factual or legal claim that the complaint or response relies on must be verifiable. If a citation cannot be located, the team is entitled to ask the party to provide the source or withdraw the claim.
The template provides wording for this provision that is general enough to apply across complaint types but specific enough that staff know what to do when a citation does not resolve. The key principle is that verification is the team's responsibility on its own decision-making, but it is the party's responsibility to provide material that can be verified.
How does a policy address procedural fairness in AI-influenced matters?
This is where the deeper conceptual work happens, and it is the section of the template that varies most across organisations.
The core question is whether AI use by one party affects the team's obligations to all parties. In most cases, the answer is that the underlying obligations do not change. Every party is still entitled to be heard, to know the case against them, and to have their material considered without bias. What changes is how those obligations are operationalised.
If one party arrives with an AI-drafted submission that runs to forty pages and the other party arrives with a handwritten letter, the team's job is not to police AI use. It is to ensure both parties have a fair opportunity to put their case. That may sometimes mean offering the second party more time, more clarification questions, or more support in articulating their position. The policy provision should make explicit that the team takes this responsibility seriously and how it does so in practice.
A separate article on this site covers procedural fairness in AI-assisted complaints in much more depth. The policy provision is the operational version of those principles. The article is the thinking behind them.
How does a policy address privacy and confidentiality of AI-influenced complaint information?
This is the question Privacy Officers ask. It does not always come up in the first conversation, but it comes up before anything is signed.
AI use by complainants raises two practical privacy questions. First, if a complainant has pasted complaint information into a public AI tool to draft their submission, that information may have been retained by the AI provider. The team cannot control what has already happened, but it can advise complainants about safer practices for any further submissions. Second, if staff use AI tools to assist with case work, the team needs clear guidance on what complaint information can and cannot be entered into those tools.
The policy provision worth having addresses both questions: it acknowledges that complainants make their own choices about AI use and the team does not police those choices, but it sets clear rules for what staff can put into AI tools when working on cases. The template wording covers both.
For organisations with statutory confidentiality obligations, Ombudsman offices and tribunals in particular, the staff-use provision should be tightened to reflect the relevant Act. The template includes a placeholder for organisation-specific statutory references because this is one of the few places in the document where one-size-fits-all wording would actively cause problems.
How does a policy address staff use of AI in complaint handling?
This is the provision that has changed the most in the last twelve months and is likely to keep changing. A year ago, most organisations were either banning staff AI use entirely or staying silent. Today, most are working out a middle ground.
The policy worth writing is one that recognises both ends of the spectrum. Staff use of AI for general productivity tasks (drafting correspondence, summarising long submissions, suggesting clarification questions) is increasingly common and, in most contexts, defensible. Staff use of AI to draft a substantive finding, recommendation or decision is a different question, and most organisations are not yet comfortable with that level of delegation.
My policy template provides a tiered structure: AI use for productivity tasks is permitted with team awareness, AI use to draft decision-making content is restricted, and the line between the two is explicit enough that staff can apply it day-to-day. The structure can be tightened or loosened depending on the organisation's appetite. What it should not be is silent.
How does a policy stay current as AI changes?
The honest answer is that any AI complaint handling policy written today will need revisiting within twelve months. The tools are changing, stakeholder behaviour is changing, and the legal and regulatory environment is changing.
The policy provision worth including is a review cycle: a named owner, a defined review date, and a trigger condition that brings the policy back to the table earlier if a significant development warrants it. The template provides wording for this with a default twelve-month cycle and a list of trigger conditions (significant case law, new statutory guidance, material change in AI tool capability, sustained pattern of new complaint behaviour).
The review provision is not a procedural afterthought. It is the provision that keeps the policy from going stale in the way that the existing pre-AI policies have.
A working AI complaint handling policy is not the destination. It is the operational scaffolding that lets the team handle the situation they are actually in, with the confidence that they are doing it consistently and defensibly.
The template we provide clients is a real, usable AI Complaint Handling Policy designed for Australian public sector, Ombudsman, tribunal and regulatory teams. It is not a fill-in-the-blanks document. It is the policy I would draft for an organisation in the first meeting, refined through actual policy advisory work with complaints teams across the country.
Let us know if you'd like a copy. You can Download the template, read it, adapt the statutory-specific provisions to your context, and adopt it. If the policy raises questions that need a deeper conversation, and most policy adoptions do, that is what the consulting work is for.
Email us to get a copy of the template at contact@shivmartin.com
A real, ready-to-adopt AI Complaint Handling Policy for Australian public sector, Ombudsman, tribunal and regulatory teams, covering the seven provisions above. Adapt the statutory-specific sections to your context and run it as your own.
Hi, I'm Shiv Martin. I'm a nationally accredited mediator, lawyer, conciliator, and conflict management specialist with over a decade of experience working across government, business, and community settings. I support teams to navigate complex and emotionally charged situations through mediation and conciliation, conflict skills training, facilitation, and practical advice on policies and processes. My approach is grounded in law, psychology, and real-world dispute resolution, with a strong focus on clarity, fairness, and workable outcomes.
If you'd like to talk about how I can help you or your organisation, you can get in touch here: 👉 Contact us
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