Towards Intelligent Auditing: Exploring the Future of Artificial Intelligence in Auditing

Abstract

Recent years have witnessed an increasingly broad application of artificial intelligence (AI) technologies such as speech recognition, computer vision, natural language processing, machine learning, algorithmic framework, cognitive computing, deep learning and neural networks in the field of auditing, producing a far-reaching impact on traditional audit work. However, the application of AI technologies in auditing practices is still in its infancy stage and further exploration and development are needed. Based on an in-depth investigation of AI-powered auditing practices, this paper proposes four innovative paths towards intelligent auditing in response to the key problems and challenges in practices, namely, audit procedure design, audit data processing, audit approach transformation and audit model exploration, with a view of achieving full coverage of intelligent auditing and making it standardized, normalized, popularized and practically effective. These innovations will effectively advance the improvement in auditing competencies and promote the high-quality development of audit work.