These days, people use AI for everything. Emails. Shopping lists. Holiday plans. School assignments. Awkward text messages they do not want to write themselves (weird, I know!).

So, it is no surprise that some people think they should use AI for their superannuation TPD claim

The problem is, a TPD claim isn’t a shopping list, so by using AI for your claim, there is a real risk it will make your claim weaker, messier, and harder to prove. That is especially important where regulators are already warning that AI can produce false information, amplify consumer harm, and create privacy risks when sensitive personal information is entered into public tools.

What people mean when they say they are “using AI” for a TPD claim

Usually, they mean one of a few things.

They are asking AI to:

• draft their claim form
• summarise their medical history
• explain the policy definition
• prepare answers to insurer questions
• write submissions about why they meet the TPD test
• organise evidence or draft complaint letters.

On paper, that sounds efficient. In real life, it can go sideways very quickly.

A TPD claim is built on detail, not guesswork

A superannuation TPD claim usually turns on very specific things:

• the wording of the policy
• the employment history
• the medical evidence
• the person’s education, training and experience
• what work they were doing before they stopped
• what work, if any, they are realistically capable of doing now.

Put simply, but very accurately, that is not “plug in a prompt and get an answer” territory.

AI tools are built to generate plausible language. They are not built to know whether your insurer’s definition uses “unlikely ever” rather than “unable ever”, whether your fund has a particular waiting period, whether your treating specialist’s evidence matches your occupational history, or whether one careless sentence in a claim form will later be used against you.

Even our (a lawyer’s) own regulatory body emphasise that AI raises practical, ethical and accuracy issues for legal work. And courts have shown little sympathy for practitioners caught out using AI where it has hallucinated and given an incorrect case reference.

That matters because TPD claims are won and lost on the fine print and the facts.

AI is very good at sounding confident when it is wrong

This is one of the biggest problems. AI often gives answers that read smoothly and sound convincing. That is exactly what makes it dangerous in claim work.

It may:

• misstate the policy test
• invent legal principles
• oversimplify the evidence needed
• get the chronology wrong
• describe the claimant’s work history in a way that creates inconsistency
• make the claimant sound better than the medical records actually support.

There’s plenty of evidence available to confirm that AI adoption comes with risks including false information, bias, exploitation of consumer vulnerabilities, and erosion of trust.

That is bad enough in a general consumer setting.

In a TPD claim, it is worse. One wrong answer on a form, one overcooked description of symptoms, or one neat little AI summary that cuts out the wrong facts can give the insurer something to seize on later. And insurers do seize on inconsistencies.

Your TPD claim involves deeply personal information

Most TPD claims involve sensitive material, including:

• psychiatric history
• diagnoses
• medications
• income details
• employment records
• specialist reports
• family circumstances
• sometimes workers compensation or Centrelink information.

That is exactly the sort of information people should be careful about entering into public AI tools. It is deeply personal information that you do not floating around in a chatbot because it seemed handy at the time.

AI does not know what not to say

This is a big one. Almost always, in claim work, sometimes the issue is not just what needs to be said. It is what needs to be said carefully.

There is a difference between:

• a truthful answer and an overly broad answer
• a helpful summary and a harmful concession
• a clear explanation and a loaded phrase the insurer will later quote back at you.

AI is not good at judgment in that sense. It tends to complete the task it is asked to do, not weigh the strategic consequences the way an experienced practitioner does. That sentence is worth reading again!

A human adviser looking at a TPD claim might say:
“That is technically true, but do not phrase it that way.”
Or:
“That point is incomplete unless we tie it back to the treating psychiatrist’s records.”
Or:
“Leave that aside for now and answer the actual question being asked.”

AI usually does not do that well. It produces text. It does not carry the claim strategy.

AI can flatten the claimant’s story into mush

A good TPD claim is not just a pile of words.

It has to tell a coherent story about:

• what the person used to do
• what changed
• why they stopped
• what treatment they have had
• what their functional limits now are
• why they are unlikely to return to work suited to their education, training or experience.

AI tends to smooth everything out. It trims rough edges. It generalises. It makes things tidy.

But real claims are often won by the untidy details. The odd work duty that aggravated symptoms. The failed return to work attempt. The reason a claimant’s qualifications do not translate into realistic employment. The difference between sitting at a desk for 20 minutes and doing that reliably for a full workday. Those details matter. AI often blunts them.

Insurers and trustees are not grading your writing style

Some people use AI because they think it will make the claim sound more polished.

That is usually the wrong focus. A TPD claim does not succeed because it sounds fancy. It succeeds because the evidence lines up. In fact, overly polished AI-drafted material can sometimes make things worse. It can sound generic, legalistic, or oddly detached from the claimant’s actual voice. That can create a mismatch between the form, the medical records, and the lived reality of the claim. Put bluntly, trustees and insurers are not handing out marks for elegance. They are looking for consistency, credibility, and proof.

AI may miss what a lawyer or experienced claims adviser would spot

This is where people get caught. They think AI has “done the job” because it produced a document.

But producing a document is not the same as identifying the real issues, which an experienced human adviser may spot.

Things like:

• the wrong policy wording being applied
• an occupational versus activities of daily living issue
• a gap between the treating doctor’s records and the specialist report
• an adverse inference likely to be drawn from a surveillance reference
• the need for stronger vocational evidence
• the need to frame the claim around failed work capacity, not just diagnosis
• the importance of addressing inconsistent work attempts early rather than letting the insurer weaponise them later.

AI does not reliably do that. It can help generate words, but it does not reliably exercise forensic judgment. That’s another sentence worth reading again!

There is also a legal-practice reason to be cautious

Australian legal and court bodies have been moving carefully on generative AI, not treating it as a magic shortcut. The Law Council says AI raises ethical, regulatory and practical implications for legal practice, and most courts have focused on ensuring any use is responsible and does not compromise the administration of justice.

That should tell you something.

If courts and the legal profession are saying, in effect, “Slow down and use this carefully,” then using AI as a do-it-yourself engine for a high-stakes disability claim is not exactly a clever shortcut.

Can AI help at all?

Used very carefully, maybe.

For example, it might help a person:

• turn rough notes into a cleaner chronology
• generate a checklist of documents to gather
• simplify a dense letter into plain English
• suggest questions to ask their lawyer.

That is very different from asking AI to run the claim. Using AI as a filing cabinet or a first-pass organiser is one thing. Using it to decide how to present your medical case, answer insurer questions, or argue why you meet the TPD definition is another thing entirely.

The better approach

If you have a superannuation TPD claim, the better approach is usually:

• get proper advice early
• understand the exact policy wording
• make sure the medical evidence matches the work history
• answer insurer questions carefully and consistently
• avoid handing over sloppy, exaggerated, or half-baked material.

That is not old-fashioned. That is just sensible. Because once a bad answer goes into a claim form, or a weak AI-generated summary gets sent off, it can be very hard to unwind later.

In Summary

Using AI for your superannuation TPD claim is a bad idea because AI is good at producing words, but TPD claims are about evidence, judgment, strategy, and precision.

AI can get the law wrong; it can get the facts wrong. It can flatten important details and create inconsistencies. For a shopping list, no worries. For a TPD claim that may affect your financial future, it is a different story. As the legal saying goes…buyer beware!

There is, of course, more to this than can be covered here. As the usual legal disclaimer goes, this information is general in nature because legal advice always depends on your circumstances.

Contact

You can call us at (03) 9969 7077 or via email at info@leonardwelch.au.

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