AI Life Insurance Advice Risks: What Australians Need to Know
- 4 days ago
- 8 min read
Written by Christopher Hall, AdvDipFP | Authorised Representative, AFSL 526688 | March 2026
In March 2026, ASIC's Moneysmart Gen Z Financial Behaviours Report found that one in five Gen Z Australians are now using AI platforms to guide financial decisions. Commenting on those findings, Council of Australian Life Insurers CEO Christine Cupitt put the concern plainly: "Alarmingly, almost 20 per cent of people actually received life insurance advice from programs such as ChatGPT in the past quarter."
This is not a fringe behaviour. It is a mainstream one — and it carries specific risks that are worth understanding before an insurance application is submitted.
Why So Many Australians Are Turning to AI First
The instinct to start with generative AI makes complete sense given the current advice landscape. Australia has lost approximately 55% of its financial advisers since 2018, and those who remain have largely closed their books, increased minimum service fees, or doubled upfront consultation costs in response to demand that far outstrips supply. For many Australians, professional financial advice has become unaffordable — and particularly so for those who need it most. (See: Your Insurance Adviser Left the Industry: What Happens to Your Policy Now?)
ASIC's 2026 data captures this dynamic precisely. Among Gen Z Australians aged 18–28, 81% report barriers to becoming more confident in managing their finances. Thirty-one per cent say they do not know who to trust. Thirty-nine per cent feel overwhelmed by the volume of information available. With a sophisticated generative AI tool available at no cost and professional advice potentially out of reach, turning to ChatGPT to understand the lay of the land is a rational first move.
Financial services adds a further layer of complexity. The industry routinely uses common language in ways that carry highly specific meanings within a regulated context — terms that search engines and AI tools can handle inconsistently, particularly when drawing on sources from multiple jurisdictions.
At Arrow Equities, clients who arrive having already used generative AI to research their insurance are often among the most prepared. They understand the terminology, know what documentation is likely to be required, and arrive with focused questions. That foundation genuinely improves the efficiency of the initial consultation.
What AI Does Well in Life Insurance Research
Generative AI is genuinely useful for certain tasks in the insurance research process. Understanding policy terminology, identifying which types of cover exist in Australia, learning what information an adviser will typically request, and developing a list of questions to bring to a first consultation — these are areas where AI performs well.
As Christopher Hall at Arrow Equities puts it: "Generative AI can be like a search engine — really useful for understanding the question, but not the final answer."
ASIC's data reflects this pattern. Sixty-four per cent of Gen Z Australians report trusting AI platforms for financial information and guidance — yet 35% of that same cohort rank source credibility as by far the most important factor when choosing financial information. The tension between those two findings is significant. Trust in AI as a starting point coexists with a clear preference for credentialled expertise when the stakes are high.
Where AI Breaks Down in Life Insurance
In life insurance specifically, the consequences of inaccuracy are not recoverable with a follow-up prompt. As Cupitt noted when commenting on the ASIC findings: "This isn't just asking AI to draft an email or fix some grammar. This is real life. Without the right kind of advice from the right people, Australians are at greater risk of falling victim to scams and dodgy providers."
Christopher Hall's experience across 500+ Australian policy reviews identifies three specific failure modes.
The multi-layered circumstances problem
Generative AI handles single-variable questions reasonably well. When an individual provides a specific condition and asks a targeted question, the output can be useful. The problem emerges when personal circumstances layer: a medical history intersecting with occupation classification, intersecting with an existing superannuation structure, intersecting with family arrangements and long-term financial plans. At that point, AI systems produce outputs that are incomplete at best and materially inaccurate at worst — sometimes drawing from overseas regulatory frameworks that have no application in Australia whatsoever.
In life insurance underwriting, a single missed detail — one undisclosed condition, one misunderstood exclusion — can alter the outcome of an application or, more seriously, a claim. (See: Pre-Existing Conditions and Life Insurance: What You Need to Know)
The underwriter relationship
What generative AI cannot do is pick up the phone. An experienced life insurance adviser works directly with individual underwriters at each insurer — the person who will be signing off on whether an application is approved, what exclusions are applied, and precisely how those exclusions are worded. That conversation, conducted by someone who has navigated the process hundreds of times, produces materially different outcomes than submitting an application based on generalised AI guidance. (See: Medical Disclosure in Insurance Applications: Common Mistakes to Avoid)
The cross-country data problem
AI systems do not always clearly delineate between Australian and international insurance frameworks. Policy structures, regulatory requirements, tax treatment, and product types differ significantly between Australia, the United Kingdom, and the United States. Guidance partially calibrated to an overseas framework — even unintentionally — can send an individual down a path that is not applicable to their circumstances.
Three Situations Arrow Equities Sees Regularly
The complex medical history
Individuals with pre-existing conditions represent the group most likely to receive harmful guidance from generative AI. The typical pattern: AI identifies the relevant conditions, confirms they are disclosable, and suggests proceeding with an application. What it does not assess is whether a pre-assessment process is warranted first. Depending on the circumstances discussed with an adviser, there are tools available to a licenced and experienced adviser — such as gathering detailed medical history information and working through a pre-assessment with an insurer — to better understand the options available and how those might shape the advice process. This is one of the avenues an experienced adviser can explore that generative AI simply cannot access. (See: When to Seek Professional Insurance Advice: The Review Process)
The online policy with inferior terms
Some individuals, directed by AI or comparison platforms toward minimal-underwriting online policies, proceed without understanding the full picture. These policies frequently carry higher premiums than a fully underwritten policy arranged directly with an insurer through an adviser. They may also carry inferior terms — and in cases reviewed by Arrow Equities, clients have been found to have missed tax deductions that, had their policies been structured differently from the outset, they may have been in a position to claim. The individual ends up paying more out of pocket while simultaneously missing potential structuring advantages. (See: Insurance Through Super or Personal Payment | 5 Ways to Reduce Life Insurance Premiums Without Cancelling Cover)
The outdated question list
A pattern that appears with some regularity: an adult child, concerned about a parent's insurance situation, generates a list of questions using ChatGPT and presents them ahead of an adviser consultation. The questions are often technically reasonable — but calibrated for a different life stage, a different level of debt, and cost-of-living assumptions that predate the current environment. The yardsticks generative AI draws on for coverage calculations have not always kept pace with current Australian mortgage levels, superannuation balances, or the premium environment following the 2021 APRA reforms.
The Insurance Industry Is Also Watching AI Closely
Questions around AI and insurance are not confined to the retail consumer experience. In August 2025, the CSIRO and the Insurance Council of Australia published a joint report, AI for Better Insurance, examining how AI is being adopted across the Australian insurance sector — from automated claims processing and fraud detection through to underwriting and risk assessment. The report noted that 57% of AI use cases across Australian financial services had been implemented or were under development within the preceding two years, with 61% of licensees planning further AI expansion.
The report's central emphasis, however, was on governance, human oversight, and the risks of over-reliance at critical decision points. Australia's own CSIRO identified bias, hallucination, privacy risks, and the erosion of human expertise as live concerns requiring active management — observations that align closely with what advisers are observing at the retail level. The technology is moving faster than the regulatory frameworks designed to govern it.
Where AI Research Ends and Professional Advice Begins
For those who have already used ChatGPT or a similar tool to research life insurance, that research represents a reasonable foundation — not a completed process. The terminology is clearer, the general landscape is understood, and the right questions are forming. What remains is a conversation with a licenced adviser who can assess the actual circumstances: the medical history, the occupation, the existing superannuation structure, and the broader family situation.
At Arrow Equities, that initial conversation is focused on understanding individual circumstances and whether meaningful assistance is possible — it is the first step in the process, not the delivery of advice itself. In many cases there is little or no out-of-pocket cost to the client. A full outline of how the review process works from that initial conversation through to a formal Statement of Advice is set out here: (See: How a Professional Life Insurance Review Works)
As CALI CEO Christine Cupitt said when responding to ASIC's March 2026 findings: "Australians want and need advice that is simple, accessible and affordable. They shouldn't have to turn to AI to get it."
A consultation with Christopher Hall can be booked directly here: Book a consultation
Frequently Asked Questions
Can generative AI provide life insurance advice in Australia? AI tools can provide general information about life insurance concepts, terminology, and available policy types in Australia. They are not licensed to provide personal financial advice under Australian law and cannot assess individual circumstances in the way a licenced adviser is required to do.
What are the main risks of using AI to research life insurance? The primary risks include inaccuracy when personal circumstances are complex, cross-country data contamination, outdated benchmarks, and the absence of any underwriter relationship. In life insurance, an error in the research phase can produce exclusions, loadings, or claim complications that are difficult to reverse.
How is a life insurance adviser different from an AI tool? A licenced adviser holds an Australian Financial Services Licence, is bound by a duty to act in the client's best interests, and has direct working relationships with individual underwriters at each insurer. An adviser can negotiate exclusion wording, conduct pre-assessments, and structure policies for tax efficiency — none of which are available through an AI platform.
Does researching life insurance through AI affect an application? The research process itself does not affect an application. However, acting on inaccurate AI-generated guidance — for example, submitting an application without appropriate pre-assessment for a complex medical history — can affect underwriting outcomes.
How does a professional life insurance review work? A professional review involves an initial consultation to understand individual circumstances, a comparison across available insurers including TAL, AIA, ClearView, Zurich, MetLife, OnePath, NEOS, PPS, and Encompass, and where appropriate the preparation of a formal Statement of Advice — provided at no cost through Arrow Equities. (See: How a Professional Life Insurance Review Works)
Educational Disclaimer: This content is for educational purposes only and does not constitute financial advice. Past performance is no guarantee of future results.
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