Naz Randeria, director of Reliance Auditing Services, said as these tools become more accessible and sophisticated in how they present information, they are also becoming more attractive to practitioners looking to create efficiencies and streamline operations.\u00a0<\/p>\n
\u201cI am not anti-AI. In fact, I think artificial intelligence will play an increasingly useful role in audit practices over time, particularly in improving efficiency, identifying patterns and assisting with preliminary analysis,\u201d Randeria said.<\/p>\n
\u201cHowever, in SMSF auditing we need to be careful not to confuse efficiency with evidence. Used appropriately, AI can become a valuable support tool. However, the concern lies in practitioners treating AI-generated output as inherently reliable simply because it is fast, appears polished or is marketed as suitable for audit use.\u201d<\/p>\n
Randeria said while AI is already used in auditing, the next challenge for the integration of the technology is around whether the output can be independently verified, and if it is grounded in objective and supportable evidence.<\/p>\n
\u201cIf an AI-generated valuation is used in an audit context, the auditor still needs to understand what sits behind it. What data was used? What assumptions were applied? Is the methodology sound? Can the result be tested against other market evidence? Can the conclusion be properly explained and defended if challenged?\u201d she said.<\/p>\n
\u201cThis remains the standard that matters, regardless of the technology used. I think this is where some practitioners may leave themselves exposed without realising it. AI tools are becoming easier to use, cheaper to access and more persuasive in the way they present conclusions. For busy firms and sole practitioners, there is a real risk that convenience starts to outpace caution.\u201d<\/p>\n
She continued that an AI-generated report can look comprehensive and still be built on weak, incomplete or untested inputs, which is why she believes it cannot be used as a substitute for professional judgement.<\/p>\n
\u201cAt most, it should be an aid to that judgement \u2014 and only where the practitioner has done the work to verify that the output is based on objective and supportable material,\u201d she said.<\/p>\n
\u201cEven using AI as a secondary check may not solve the problem. If one AI tool is being used to validate the output of another, the practitioner may simply be layering one opaque system over another. Unless the result can be traced back to reliable source material and independently assessed, that type of corroboration may offer more comfort than substance.<\/p>\n
Furthermore, Randeria said, there is a broader risk in using AI that is not often discussed \u2013 insurance exposure.<\/p>\n
\u201cFrom the advice I have obtained, AI use does not appear to be expressly excluded under existing cover. However, whether any particular claim would respond will still depend on the facts, the policy wording and the nature of the loss,\u201d she said,<\/p>\n
If the issue arises because an auditor relied on AI-generated material that should have been independently checked, that may raise a professional indemnity issue. If the issue involves client information being uploaded to a third-party platform, leading to a breach of confidentiality, privacy concerns or data leakage, the exposure may sit in the cyber space and, in some cases, overlap with PI.\u201d<\/p>\n
She said the distinction matters because many firms are focusing on what AI can do for productivity, without giving enough thought to what it may mean for liability.<\/p>\n
\u201cIf an AI platform is later found to be insecure, defective or unsuitable, or if staff use it in a way that exposes client information or weakens the quality of audit evidence, the consequences may extend well beyond methodology. They may affect claims, coverage and risk management obligations as well,\u201d she said.<\/p>\n
\u201cAI has the potential to enhance the audit profession, and I have no doubt it will soon play a role in day-to-day practice in some form. But in SMSF auditing, the threshold remains the same: evidence must be reliable, supportable and capable of withstanding scrutiny.\u201d<\/p>\n
She concluded that while technology can assist the audit process, it cannot replace the auditor\u2019s responsibility for the final conclusion.<\/p>\n
\u201cFor practitioners, the message is simple. Use AI thoughtfully. Understand the tool. Protect client data. Verify the output. And remember that when things go wrong, it is not the software that signs the audit file.\u201d<\/p>\n
\u00a0<\/p>\n
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