The evolution of audits, best practices to prepare, and the role of AI in all of it.

The role of auditors is evolving. Traditionally, audits have been labor-intensive processes, relying on extensive sample testing, documentation reviews, and manual reconciliations. But with the rise of AI, the profession is on the brink of a transformation. To explore this shift, we spoke with Cees Man, Audit Partner at Grant Thornton Netherlands, and Eric Storms, Senior Manager Audit, to understand how AI is shaping the future of auditing, the challenges it presents, and what it means for finance leaders today.

The Evolution of Audit: From Sampling to Continuous Monitoring

One of the biggest challenges in audit is ensuring financial accuracy while balancing efficiency. Historically, auditors have relied on sample testing - selecting portions of transactions to verify, rather than analyzing an entire dataset. However, as AI-driven anomaly detection and automated reconciliation tools gain traction, the audit process is shifting.

"If companies have strong controls in place, we can rely on them more, which can reduce the amount of substantive testing required during the audit," says Man. "With AI, we will likely see a shift from sample testing to anomaly detection, which allows auditors to focus on areas of higher risk rather than spending time on routine checks."

Storms adds that AI-powered tools are already improving efficiency. "At Grant Thornton, we use tools like RobotX, DataSnipper, among other tools, for automated invoice matching, document verification, and cross referencing. These tools help auditors work more efficiently while improving accuracy."

The Foundation of a Strong Audit - Best Practices in Account Reconciliations and Controls

While AI is transforming audit processes, foundational best practices remain critical - especially when it comes to account reconciliations. A well-executed reconciliation process ensures that financial statements are accurate, reduces errors, and helps companies remain in control of their financial health.

"Account reconciliations are a crucial part of the closing process," says Storms. "Without them, companies risk relying on outdated or inaccurate financial numbers, which can lead to poor decision-making."

For companies that "get it right," the benefits are clear:

• Control and Reliability: Companies with well-structured reconciliation processes can confidently explain what’s in their financial system, making audits smoother and financial reporting more reliable.

• Compliance and Risk Reduction: "Companies that have management teams acknowledging the importance of compliance with legislation and financial requirements tend to have better internal controls," notes Man. This leads to a reduced need for extensive sampling in audits.

• Efficiency in Audit Preparation: When subledgers don’t align with general ledgers, it creates unnecessary complexity and follow ups with the external auditors. Ensuring timely reconciliations and proper documentation within finance processes prevents these issues.

For companies operating internationally, reconciliation challenges become even greater due to multiple time zones, currencies, and local regulatory requirements. Addressing these proactively with strong internal controls and automation can help mitigate risks.

AI’s Impact on Efficiency and Accuracy

AI is not just about automating tasks - it’s about redefining how audits are conducted. Traditionally, financial close and audit processes followed a rigid timeline, with accountants and auditors working in concentrated bursts around year-end. But AI is enabling a more continuous, real-time approach.

"In the past, auditing had a clear busy season," explains Man. "That’s changing. With AI, auditors can check in multiple times a week, making audits more iterative and reducing the last-minute crunch."

This shift is particularly relevant for companies operating across multiple jurisdictions. Different time zones, currencies, and local reporting requirements add complexity to reconciliations and financial close processes. AI-powered tools can streamline these operations by standardizing data and identifying discrepancies before they become material issues.

Regulatory Considerations: Are Auditors Ready?

While AI adoption in audit is growing, regulators have yet to fully catch up.

"Right now, accounting bodies are publishing guidelines on AI, but regulations lag behind adoption," Man notes. "There’s also the question of privacy - how do you deal with sensitive data when using AI-powered tools?"

This uncertainty means that while firms like Grant Thornton are embracing AI, the audit profession is still navigating uncharted territory. Companies implementing AI in their financial processes should be prepared for evolving compliance requirements in the years ahead.

A Future of Continuous Auditing?

One of the most exciting possibilities AI presents is the transition from periodic audits to real-time, continuous auditing. In a traditional audit cycle, financials are reviewed at set intervals, leaving room for financial inaccuracies to persist unnoticed for months. But AI’s ability to monitor financial transactions continuously could lead to a fundamental shift.

"We’re moving toward a world where audits happen in real time," says Storms. "Instead of waiting until the end of the year, AI can help us monitor financials continuously, reducing risk and improving oversight."

While continuous auditing isn’t widespread yet, companies that invest in AI-driven financial systems today will be better prepared for this future.

What Finance Leaders Should Do Now

For CFOs and controllers, AI in audit isn’t just about compliance, it’s about business resilience. Here’s what finance leaders should consider as AI reshapes auditing:

1. Invest in Strong Controls – AI tools can enhance efficiency, but auditors still need to rely on well-established internal controls. Companies with strong financial governance will benefit most from AI-driven audits.

2. Prepare for Regulatory Changes – AI in finance is still evolving, and regulations will follow. Stay informed on compliance updates to ensure your AI implementations align with future audit standards.

3. Embrace AI-Driven Anomaly Detection – Traditional sample testing has limitations. AI-powered anomaly detection tools can identify risks proactively, reducing the chances of financial misstatements.

4. Shift Toward Continuous Monitoring – While real-time auditing isn’t the norm yet, companies should start integrating AI tools that enable ongoing financial monitoring.

In conclusion…

The audit profession is on the brink of a transformation, driven by AI’s ability to improve efficiency, accuracy, and oversight. While challenges remain, particularly around regulation and data privacy, the trajectory is clear: AI will play a central role in the future of auditing.

At the same time, best practices like account reconciliations and strong internal controls remain as important as ever. AI may enhance the audit process, but it can’t replace the fundamental need for well-managed financial systems.

Companies that embrace both AI-driven efficiencies and strong reconciliation practices will not only streamline their audit processes but also gain a competitive edge in an era of real-time financial oversight. The question is no longer whether AI will impact auditing, but how quickly finance leaders will adapt.

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At Stacks, we’re committed to helping finance teams stay ahead of the curve with their audits. If you’re looking to integrate AI and boost controls into your financial workflows, we’d love to chat!