The audit profession is changing faster than many businesses realise. Artificial intelligence, data analytics, cloud technology and automation are reshaping how audits are performed, how risks are identified and the type of value auditors can provide.
For businesses, understanding these developments is essential. Technology can improve efficiency and provide deeper insights, but it also introduces new ethical, governance and audit risks. Auditors need to ensure that technology supports professional judgement, rather than replacing it.
From Sampling to Smarter Analysis
For decades, audits have relied heavily on sampling. Auditors tested selected transactions and used the results to draw conclusions about the broader population. That approach was practical when records were largely manual, but today’s businesses generate far more data than traditional methods were designed to handle.
Technology now allows auditors to analyse entire datasets, making it easier to identify unusual transactions, trends and potential risks. Rather than relying solely on samples, auditors can gain a complete picture of an organisation’s financial activity.
Auditors still form an opinion on whether financial statements present a true and fair view. Technology does not change that objective; it provides new ways to gather evidence, identify risks and perform audit procedures more effectively.
The Technology Driving Change
Artificial intelligence can help auditors analyse large volumes of data quickly and identify unusual transactions, patterns and emerging risks that may require further investigation. For example, AI can assist in reviewing large journal entry populations, helping auditors identify unusual or high-risk manual journals and focus testing on areas that warrant further attention. This can improve the efficiency of fraud risk assessments and support auditors in meeting requirements under standards such as ASA 240 and ASA 315.
Other technologies driving change include:
- AI-powered document review tools can scan invoices, contracts, bank statements and other supporting documentation to extract and organise key information. By reducing the time spent manually reviewing documents, these tools allow auditors to focus on analysing evidence, investigating exceptions and applying professional judgement.
- Data analytics tools, which enable auditors to analyse entire populations of transactions rather than relying solely on sample testing. This helps identify trends, anomalies and potential risk areas that may otherwise go unnoticed.
How AI Changes Audit Risk
As more organisations adopt AI, auditors need to consider how these systems affect the audit risk profile, including changes to business processes, controls, data reliability and governance oversight.
AI can alter business processes, change the control environment and create new risks that require assessment. Auditors need to understand how AI is used within the organisation, how outputs are generated, what data the system relies on and whether appropriate governance and controls exist.
The reliability of audit evidence may also be affected where information is produced through AI-driven processes. In these circumstances, auditors may need to perform additional testing, involve specialists or place greater focus on the design and operation of relevant controls.
Strong governance is particularly important when AI is used in financial reporting or key business processes. If boards and management do not actively oversee AI systems, data quality, access controls and related risks, audit risk may increase significantly.
For businesses, the key message is that technology adoption should be matched with appropriate governance. Clear accountability, documented controls, data quality checks and regular oversight are important safeguards when AI or automation forms part of financial reporting or key business processes.
Technology and Ethics
The ethical principles that guide the profession do not change due to the use of AI. Under APES 110, accountants and auditors are required to maintain professional competence, objectivity, integrity, confidentiality and professional behaviour. These principles remain just as important when using AI as they are in any other aspect of professional work.
One risk that continues to attract attention is automation bias. This occurs when people place too much trust in technology-generated outputs without applying sufficient critical thinking. Auditors should approach AI-generated information in the same way they would any other source of evidence: carefully and critically.
AI, Governance and Professional Responsibility
The growing use of AI has attracted considerable attention from regulators and professional bodies.
ASIC has highlighted governance challenges associated with AI, including the risks that can arise when organisations adopt these technologies without appropriate oversight. Similarly, the APESB has reminded members that responsibility for professional judgement remains with the accountant or auditor, regardless of whether AI has been used to assist their work.
While AI can generate useful insights, it can also produce inaccurate or misleading information that appears convincing. There have already been examples of AI-generated content containing fabricated references and incorrect conclusions. As a result, auditors must continue to verify information and maintain professional scepticism.
Looking Ahead
AI is a powerful tool, but it is still only a tool. It can help auditors analyse information more efficiently and identify risks more effectively, but it cannot replace professional judgement, scepticism or experience.
Technology will continue to reshape the audit process, but audit quality will still depend on the auditor’s ability to apply sound judgement, challenge assumptions and draw meaningful conclusions from the evidence available.
