Internal Audit Applications of AI: It Doesn't Have to Be Complicated to Be Effective - The Protiviti View

For many internal auditors, artificial intelligence (AI) may seem like a daunting topic to tackle -- but that shouldn't stop them from considering how they can apply it to their work. Tools and techniques exist that can provide auditors with powerful, straightforward techniques to enhance their work. With an increased focus and urgency around the use of data to support internal audit activities, the time for next-generation pursuits, such as use of AI, is now. Following up on a previous blog post discussing the basics of AI for auditors, here we offer our thoughts on how internal audit organizations can get started with AI methods, such as machine learning (ML), to increase efficiency and coverage, better assign resources to areas that matter most, deliver more insight and even help identify leading indicators of risk. We also offer a specific example of ML applied to internal audit. Machine Learning Doesn't Have to Be Complex ML is an application of AI in which the system itself is designed with the ability to learn and improve from experience.