Artificial intelligence (AI) can help auditors examine more information and identify unusual transactions or patterns during the audit process. For finance leaders, that can mean better-informed questions and more productive conversations with auditors.
For most professionals, the benefits of AI are clear and practical: AI helps get work done faster. You may already be using AI to simplify the time-consuming tasks of gathering files and preparing data for financial statement audits.
But AI can do more than save time. By reducing manual data entry and supporting more targeted inquiries into financial records, AI can give auditors more time for analysis. Auditors serve as the “human in the loop,” reviewing the technology’s output, investigating exceptions and identifying areas that require closer attention.
A financial statement audit is designed to provide an independent opinion on whether financial statements are fairly presented.
As a finance leader, you may also value insights that help you better understand the issues identified in an audit. You may want to know whether the audit has identified patterns that could point to broader risks, along with opportunities to improve financial reporting processes. You might value the auditor’s perspective on evolving industry practices or suggestions related to specific pain points. But the limited time available for most audits can make it difficult to explore these areas.
By reducing manual work, AI can help auditors prepare more thoroughly for discussions with you and make better use of their time on-site. The routine back-and-forth during an audit can shift from filling gaps or searching for information to more focused conversations about risks and other areas that require your attention.
In other words, AI in financial statement audits is not just a technology story. It can create more room for human interaction and help auditors develop a deeper understanding of your business. Over time, that may change what you expect from an audit.
The traditional audit process is labor-intensive. Audit teams can spend considerable time getting data and files from clients, searching those files for specific information and entering the results into audit templates. That work must then be reviewed to verify that the data was entered correctly.
Technology that can read and transfer information from client files has existed for years, but earlier tools still required extensive manual searching and verification. AI can now make a first pass through client documents, extract specified information and populate the auditor’s templates. The auditor then reviews the results and investigates any exceptions.
Beyond reducing manual work, AI can also help auditors investigate specific questions.
Let’s say that an auditor wants to compare a client’s data with an external data set to look for unusual patterns or to examine revenue flows across client agreements, invoices and payment records. For companies with large, complex data sets, locating and reviewing all the relevant information manually would be very time-consuming.
With AI, auditors can create specific prompts to pull and organize data for a first-pass analysis. The auditor interprets the results and determines what, if anything, requires further investigation.
The technology driving AI is still developing, making it difficult to predict how its role in financial statement audits will evolve. Two areas to watch are fraud risk and auditing guidance.
AI’s ability to compare large amounts of data and trace transactions across multiple records may help auditors spot indicators of potential fraud. However, AI can also be used to create increasingly convincing false documents and transaction trails, adding new challenges to the evaluation of audit evidence.
Data analysis may help identify unusual patterns by comparing current transactions with historical or external data. Other defenses depend on people and processes. Finance leaders can help protect their companies by keeping employees informed about emerging schemes and regularly reviewing internal controls as threats evolve.
Auditors will also need to adapt how they evaluate and corroborate potentially false documentation. The approach will likely combine data analytics with hands-on review, external confirmations and interviews with key people at the company being audited.
Auditing standards and professional guidance on the use of AI in financial statement audits continue to develop, but the auditor’s fundamental responsibilities are already established. Existing standards and professional guidance make clear that auditors remain responsible for supervising and reviewing the work, evaluating audit evidence, exercising professional judgment and reaching audit conclusions.
For public company audits, the Public Company Accounting Oversight Board (PCAOB) standards address auditors’ responsibilities when using technology-assisted analysis. For private company and nonprofit audits, the American Institute of CPAs (AICPA) practice aid explains how existing auditing standards apply when auditors or the clients they audit use AI.
AI may affect the data auditors review, how they perform certain tasks and how they interact with you. Understanding how your auditor uses it can help you know what to expect, how your information will be protected and where human judgment remains essential. It can also clarify what level of communication to expect and when you can discuss concerns and priorities with the audit team. Consider asking these questions:
AI is changing how auditors gather information, analyze data and prepare questions, but professional judgment is still central to the process. Learn how our audit services experts combine technology with industry knowledge and human insight throughout the audit.
Want to smooth potential audit bumps? Get our financial statement audit checklist to learn document tips, what transactions to flag and more.
