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AI in Complaints and Disputes: The New Reality

  • Writer: Shiv Martin
    Shiv Martin
  • Mar 18
  • 6 min read

Updated: 2 days ago

If you work in complaints or dispute resolution, here’s what you need to know today about how AI is impacting your work

In this article

Across my Community of Practice discussions, one theme keeps resurfacing: navigating AI is quickly becoming one of the biggest operational and fairness challenges for complaints and dispute resolution teams. People are using AI to draft complaints and submissions, summarise evidence, translate narratives, and generate “legal research” (including citations) and institutions are responding with new guidance, practice directions, and governance frameworks to manage accuracy, privacy, and integrity risks. 


This paper does not seek to promote or prohibit the use of AI. Its purpose is to describe how AI is currently being used in complaints and dispute resolution contexts, to identify its strengths and limitations, and to outline the challenges these developments present for courts, tribunals, regulators, and oversight bodies.


Current uses of AI in complaints and dispute resolution systems


Use by complainants and parties

Parties commonly use commercially available AI tools to:

  • draft or refine complaints, submissions, and correspondence

  • structure narratives into timelines or issue lists

  • summarise long document sets or email chains

  • translate material or convert it into plain language

  • generate explanations of legal concepts, procedural steps, or potential remedies.


Use by institutions
AI in Complaints and Disputes: The New Reality

Institutions are also exploring or implementing AI-enabled tools, including:


  • automated intake and triage support

  • document classification and prioritisation

  • summarisation of large volumes of material

  • drafting assistance for routine correspondence or internal notes

  • website chat tools that provide general procedural information


While these uses vary significantly in sophistication and risk profile, they share a common objective: managing volume, improving consistency, and supporting timely resolution.



The challenges with Ai in complaints and dispute resolution


Too much information, not always the right information


AI can make submissions more structured and readable. It can also inflate volume: longer narratives, more annexures, more confident legal framing, and more repetition. That creates a predictable downstream cost. Not just reading time, but the hidden work of checking jurisdiction, separating relevant facts from AI-generated filler, verifying authorities and quotations, and correcting confident-but-wrong outputs.


What to do:

  • Name it early. Let stakeholders know AI-generated submissions can be polished but unreliable, and verification may be required.

  • Ask direct questions. Use specific prompts to extract the facts you actually need.

  • Design forms for clarity, not storytelling. Segment information into fields rather than inviting large slabs of free text.

  • Pick up the phone. Short early calls or case conferences clarify what matters faster than a paper trail.


Mismanaged expectations


AI tools create certainty in tone even when the underlying advice is conditional, incomplete, or wrong. Parties may believe a process is faster than it is, that outcomes are guaranteed, or that "the law clearly says" something it doesn't. The expectation gap increases repeat contact, escalation, and emotional load on staff.


What to do:


  • Invest in your first response. A short auto-response explaining your role, what you can and can't do, typical timeframes, and what a good complaint looks like prevents AI from becoming the default front door into your system.

  • Assume people use AI because they're stuck. If your guidance is hard to find or hard to understand, AI fills the gap. Fix the gap.

  • Treat your public information as a preventative control. AI platforms draw heavily on public content, so what you publish shapes what people read, repeat, and believe.


Practical guidance: green, amber, red

In my workshops I encourage complaints handlers to consider a traffic light system to explain AI use, rather than generic warnings or bans.


Green (generally safe): improving structure and readability, translating into plain language, creating timelines or issue lists, preparing questions for a call.


Amber (use with care): summarising long documents (check against originals), drafting complaint narratives (verify facts), suggesting next steps (check jurisdiction).


Red (high risk): generating facts or evidence, inventing legal authorities, rewriting witness evidence as if it were the person's own recollection, uploading sensitive or protected material to open tools.

Traffic Light guide for complaints and dispute resolution

If your team is grappling with AI-generated complaints, mismanaged expectations, or growing pressure on fairness and trust, I support complaints bodies, regulators, tribunals and Ombudsman offices through training, facilitation and system design advice. You can learn more about how I can support here: Ai in Complaints



A principles-based framework for AI-ready dispute resolution


Four principles hold up across complaints, conciliation, tribunals, and courts:


  1. Human dignity and voice. People need to feel heard by a real person, especially when stakes are high.

  2. Procedural fairness and explainability. Parties should understand what is happening, why, and how they can respond. AI influence on triage or outcomes must be transparent and contestable.

  3. Accuracy and evidence integrity. AI is useful for structure, not as a fact source. Verification must be built in.

  4. Privacy, confidentiality, and safety by design. Systems must reduce the risk of disclosure or unsafe handling of protected material.


What complaints and dispute resolution teams can do now


  1. Get human early. A short phone call or case conference prevents weeks of back-and-forth.


  2. Build AI literacy as a core practice skill. Train staff to recognise sudden shifts in writing style, over-structured legalistic framing that doesn't match the person's earlier communication, suspicious citations, and confident claims about what "the law clearly says".


  3. Guide stakeholders on safe use. Replace generic warnings with the green, amber, red framework.

    If people are using Ai to navigate your process... start here

Conclusion - As AI rises, it’s time to get more human


The more AI enters our dispute systems, the more we need to prove we are not machines. For decades, many members of the public have felt like they were communicating with computers: portals, scripted responses, standard letters, and processes that do not listen. Now AI risks deepening that experience unless we deliberately respond in a different direction.


For the past 20 years, I’ve been saying: pick up the phone. Now, more than ever, that message matters. Why? Because in an AI-shaped environment:

  1. the signal-to-noise ratio is lower (more words, less clarity),

  2. expectations are higher (more confidence, more certainty),

  3. misunderstandings spread faster (hallucinated law and misdirection),

  4. and trust becomes more fragile (people assume “it’s all automated”). 


As AI becomes more prevalent, the legitimacy of dispute resolution systems will depend not on technological sophistication, but on the clarity, care, and humanity with which those systems respond.


Curious about my training, speaking and policy supports in this area?


👉 Book a confidential conversation to discuss what an AI-ready, human-centred response could look like for your organisation.

My next live course in this area is this June! Sign up before June 30 to use this financial years budget! Find out more here.


Navigating Ai in complaints and dispute resolution banner

Shiv Martin is a nationally accredited mediator, practicing solicitor, conciliator, decision-maker, and certified vocational trainer.

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.





Shiv Martin Consulting offers a structured three-level professional development pathway for dispute resolution and regulatory teams.


3 levels of dispute resolution skills training

• Level 1 – Core Dispute Resolution Skills: For new starters or professionals working in complaints, case management or early resolution roles.

• Level 2 – Managing Challenging & High-Risk Interactions: For experienced conciliators, mediators, complaints managers and regulatory officers.

• Level 3 – Community of Practice for regulatory professionals: For experienced staff committed to reflective practice and continuous improvement.


All 3 levels can be offered in-house, simply email us to discuss your specific needs and we can tailor training to suit your team.


References for further reading



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Mar 19
Rated 5 out of 5 stars.

Great article Shiv. Hope you are well.

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