I’m assuming that if you’re reading this post, you’re a member of your board’s audit committee (though if you’re here for fun - welcome! Maybe find a new hobby?). Within this role, you play a crucial part in overseeing the integrity of financial reporting and the effectiveness of internal controls. The emergence of AI technologies that can be leveraged in the revenue recognition processes presents a pressing issue that necessitates board review.

In a recent blog post that I wrote for my company, 273 Ventures, I explored how AI, particularly large language models like GPT-4, are potentially transforming the processes by which companies automate revenue recognition under ASC 606 and IFRS 15 standards. While it’s a fairly technical post (I was definitely wearing my CPA hat while writing that one), I think that there are some valuable points that are specifically relevant to audit committee members and I wanted to share them here:

Key Takeaways for Audit Committees

Enhanced Accuracy and Consistency

AI tools can systematically analyze contracts and related documents, potentially reducing human error and ensuring more consistent application of revenue recognition principles. This could lead to more reliable financial statements and fewer audit adjustments.

Internal Control Implications

The integration of AI in revenue recognition processes may require updates to internal control frameworks. Consider how these tools interact with existing controls and whether new controls are needed to address AI-specific risks.

Data Quality and Cybersecurity

AI systems rely heavily on data. Ensure that data feeding into these systems is complete, accurate, and secure (remember, garbage in = garbage out). This may involve discussions with IT and cybersecurity teams about data governance and protection measures.

Audit Efficiency

AI tools can potentially streamline the external audit process by providing more organized and accessible documentation. This could lead to more focused audits and potentially reduce audit fees over time (but remember, your auditors are also trying to figure out their new competitive advantage in this landscape).

Regulatory Compliance

As regulators begin to scrutinize the use of AI in financial reporting, stay informed about any new guidance or requirements. Consider how the use of AI aligns with regulatory expectations and industry best practices.

Transparency and Explainability

Ensure that the AI systems used for revenue recognition can provide clear explanations for decisions. This transparency is crucial for maintaining the audit trail and defending accounting treatments if questioned.

Skill Set Evolution

Assess whether the finance team and internal audit function have the necessary skills to effectively implement and oversee AI-driven revenue recognition processes. This may inform recommendations for training or hiring.

Strategic Considerations for Audit Committees

While this particular post focused on revenue recognition, it should give rise to questions about how your company is strategically thinking about AI and its impact on your company’s financial reporting processes and controls. Here are some key questions to get you started:

Conclusion

By examining these issues now, your audit committee can play a crucial role in guiding your company through the AI-driven transformation of your financial statement preparations, including revenue recognition processes.

Remember, while AI offers significant benefits in accuracy and efficiency, it also introduces new complexities that require careful oversight. Your role in ensuring the reliability and integrity of financial reporting is not lessened by the fact that models and algorithms are preparing the numbers - if anything, the human-in-the-loop element is even more important.