Australian companies are racing to invest in artificial intelligence for financial auditing and reporting, but they're falling behind on the governance frameworks needed to manage those systems responsibly. A global survey of 1,800 business leaders, including 100 from Australia, reveals a critical gap: while 75% of Australian firms are piloting or adopting AI for financial reporting, only 48% have established formal policies and governance structures to oversee those systems. That's significantly lower than the 61% of companies globally that have set up such safeguards.

The disconnect matters because AI investment is accelerating rapidly. More than half of Australian respondents are dedicating 11% to 20% of their IT budgets to AI, compared to 44% globally. Within three years, 99% of companies worldwide say they will be piloting or actively using AI in financial reporting. Yet without clear governance frameworks in place, organizations risk deploying powerful AI systems without adequate oversight, controls, or accountability mechanisms.

What Are Companies Using AI for in Financial Auditing?

The appeal of AI in auditing is straightforward: it can detect anomalies, predict risks, and process vast amounts of financial data faster than human auditors alone. Globally, 73% of boards expect auditors to prioritize AI in anomaly and risk detection, while 53% want auditors to focus on predictive analysis. Generative AI, the technology behind tools like ChatGPT, is becoming central to these workflows. In Australia, 92% of respondents found generative AI to be important for external auditing.

The benefits are measurable. Companies report that AI significantly reduces costs, boosts employee productivity, and helps attract talent. The most commonly cited advantages include:

• Anomaly Detection: AI systems identify unusual patterns in financial data that might signal fraud or errors, flagged by 61% of respondents as a key benefit.
• Trend and Risk Prediction: AI can forecast financial trends and identify emerging risks before they become problems, valued by 60% of organizations.
• Evidence-Based Decision Making: AI-generated insights help leaders make more informed choices, cited by 58% of firms as a significant advantage.
• Real-Time Risk and Fraud Detection: Continuous monitoring provides immediate visibility into potential issues, important to 56% of respondents.
• Data Accuracy and Reliability: AI reduces human error in data entry and processing, noted by 51% of companies.

Why Is Governance Falling Behind Investment?

The governance gap suggests that Australian companies are moving faster on implementation than on establishing the rules and oversight mechanisms to manage AI responsibly. This creates real risks. When asked about concerns, organizations cited several critical issues: uncertain return on investment (49%), financial reporting and auditing data accuracy (46%), cybersecurity (45%), and regulatory compliance (44%).

The regulatory compliance concern is particularly telling. As governments worldwide develop AI governance frameworks, companies without formal internal policies may struggle to demonstrate compliance. Australia's lower governance adoption rate suggests many firms are reactive rather than proactive, building safeguards only after problems emerge or regulators demand them.

"As stewards of the capital markets, KPMG auditors understand the complex business, regulatory and technical challenges our clients face. They are in a unique position to make the most of AI and advanced technologies, transforming how we work together to deliver exceptional experiences and insights in a values-driven, human-centric and trustworthy way," said Elenie Panos Carey, Chief Technology Officer for Audit and Assurance at KPMG.

Elenie Panos Carey, Chief Technology Officer, Audit and Assurance at KPMG

How to Build AI Governance in Financial Auditing

Organizations looking to close the governance gap should consider a structured approach to managing AI systems responsibly:

• Develop a Company-Wide AI Strategy: Establish a clear vision and strategy for AI use across the organization, driven by the board. Currently, 67% of companies globally have such a strategy in place, but Australian firms should prioritize this foundational step before expanding AI deployment.
• Create Formal Policies and Governance Structures: Document how AI systems will be used, monitored, and audited. This includes defining roles, responsibilities, and escalation procedures for when AI systems produce unexpected or concerning results.
• Implement Responsible AI Frameworks: Use established methodologies to design, build, deploy, and use AI solutions in an ethical manner. This includes testing AI systems for bias, accuracy, and compliance with regulations before they're used in production.
• Establish Data Quality and Security Controls: Since AI systems are only as good as the data they process, implement controls to ensure data accuracy, consistency, and security throughout the AI pipeline.
• Monitor and Audit AI Performance Continuously: Don't treat AI deployment as a one-time event. Regularly assess whether AI systems are performing as expected and delivering promised benefits without introducing new risks.

The survey data reveals that 67% of companies globally already have a company-wide vision and strategy for AI, driven by the board. This suggests that governance is most effective when it starts at the top, with board-level commitment and oversight.

What Does This Mean for Australian Financial Services?

Australia's financial services sector is highly regulated, which makes the governance gap particularly concerning. Regulators expect organizations to understand and control the systems they deploy, especially in areas as sensitive as financial reporting and auditing. Companies that invest heavily in AI without establishing corresponding governance frameworks risk regulatory scrutiny, reputational damage, and operational failures.

The gap also reflects a broader challenge in AI governance globally. As organizations race to adopt AI for competitive advantage, the infrastructure to manage those systems responsibly often lags behind. Australia's 48% governance adoption rate suggests that many firms are still in the early stages of building that infrastructure, even as they scale AI use.

For auditors and financial leaders, the message is clear: AI is becoming essential to modern auditing, but deploying it without governance is like driving without brakes. The next phase of AI adoption in Australian finance will likely be defined not by who invests most in AI, but by who builds the most effective governance systems to manage it responsibly.