Recent Advancements in Auditing: Theory, Practice, and Innovation

This book explores the current developments in auditing, spanning theoretical foundations, practical applications, and the impact of digital transformation, particularly with regard to advancements in artificial intelligence and machine learning, including the development of large language models (LLMs) tailored to specific industries. These technologies have the potential to enhance the accuracy and efficiency of audits by providing deeper insights and automating complex tasks. Within this context, the book considers audit procedures, materiality, going concern assessments, and the integration of AI and IoT in audit processes. The book also addresses internal auditing challenges, pandemic-era adaptations, and auditor liabilities. The book serves as a vital resource for scholars, practitioners, and students seeking insight into the evolving auditing landscape.