What AI does (and doesn’t do) in our Melbourne team’s audit process

AI is changing how audits are delivered, but the story is not just about tools. At PKF Melbourne, our focus is on building the capability of our people to use AI responsibly, critically and effectively.

What AI does (and doesn’t do) in our Melbourne team’s audit process

There’s no question that AI is changing the way work gets done across professional services. At our PKF Melbourne office, we’re embracing that shift with a very clear position: AI doesn’t perform the audit for us. It helps our auditors ask better questions, analyse information more effectively and spend more time on the areas where experience and judgement matter most.

We’re passionate about innovation and continually investing in tools, training and habits that improve how we work. We are building AI capability within our audit team rather than simply deploying another piece of software. The quality of our audits is still driven by the experience of our people. Our partners and senior management remain deeply involved, constantly reviewing workflows and processes to ensure we’re delivering at, and above, the standard our clients expect.

AI is not a shortcut for our teams. It’s an enabler that allows our auditors to focus more time and attention on client context, risk, challenge and judgement. Tom Burton, Senior Manager in our Melbourne Audit team provides insight into how his team are using AI in the audit process.

Planning and risk assessment

At the earliest stage of the audit, AI helps us bring together large volumes of information quickly; prior year files, financial reports, and relevant industry data.

This allows our teams to identify key risk areas earlier and more efficiently, bringing more contextual information into the discussion. It can also highlight unusual trends, movements, and ratios that warrant further investigation.

The outcome is not a decision; but a better-informed starting point for our auditors, who apply judgement to determine what matters, why is matters and how it should influence the audit response.

Data analysis and scoping

Audit increasingly involves working with large datasets. AI supports our teams by analysing general ledgers and transaction listings to identify anomalies, outliers, and patterns that may not be immediately visible.

It also assists in shaping how we scope testing, helping to identify appropriate samples or populations.

Those outputs are inputs into judgement, not decisions in their own right. Our Melbourne auditors interpret those outputs, challenge the results, and determine the right approach to testing.

Documentation and workpapers

One of the most practical uses of AI is in reducing time spent on repetitive documentation tasks.

AI can help draft workpapers, summaries, and initial narratives, allowing our teams to spend less time writing and more time thinking critically about the work itself.

Every document is still reviewed, refined, and signed off by our audit team. This rigorous processing ensures it reflects our professional standards and the reality of the engagement.

Testing support

AI can also assist in interpreting supporting documentation such as contracts and agreements.

By summarising key terms and highlighting potential accounting or audit implications, it provides a starting point for analysis.

Our auditors then apply technical knowledge and scepticism to assess whether those interpretations align with the broader context of the business and the applicable standards.

Financial reporting and technical analysis

When it comes to financial reporting, AI can support the technical side of the audit; assisting with analysing accounting standards, reviewing disclosures, and checking completeness.

It can also compare draft financial statements against prior periods and relevant requirements.

But assessing whether disclosures are appropriate, and whether positions taken are reasonable, remains a matter of professional judgement.

Completion and review

At the final stage of the audit, AI can support the preparation of closing reports and communications.

This helps streamline delivery, but it does not replace the review and oversight processes that underpin audit quality.

The role of judgement

Across every stage of the audit, AI plays a supporting role. It enables efficiency, consistency, and broader analysis; but its greatest value is in augmenting auditor capability rather than replacing professional judgement.

The quality of an audit ultimately depends on:

• The experience of the audit team
• Their understanding of the client and industry
• Their ability to challenge, interpret, and reach a conclusion

Technology cannot replicate the expertise, experience, diversity and wisdom that sits within our teams, nor the professional scepticism required to challenge, interpret and conclude.

At PKF Melbourne, our approach is to use AI where it enhances quality, insight and efficiency, while ensuring the outcome is always shaped by the people behind it.