Thesis Abstract

Abstract
The rapid advancement of artificial intelligence (AI) technology has revolutionized various industries, including accounting and auditing. This thesis explores the impact of AI on financial statement auditing, aiming to assess the benefits, challenges, and implications of integrating AI technologies into traditional auditing practices. The study begins with an introduction to the research topic, providing background information on AI and its applications in accounting. The problem statement highlights the need for a comprehensive understanding of how AI is transforming financial statement auditing processes. The objectives of the study are to evaluate the effectiveness of AI tools in enhancing audit quality, efficiency, and accuracy, as well as to identify potential risks and limitations associated with AI implementation in auditing practices. The limitations and scope of the study are also discussed, along with the significance of the research in contributing to the existing body of knowledge in the field of accounting and auditing. Chapter two presents a detailed literature review on the impact of AI on financial statement auditing. The review covers ten key areas, including the evolution of AI in auditing, AI technologies commonly used in auditing processes, benefits of AI adoption in auditing, challenges and limitations of AI integration, regulatory considerations, ethical implications, and best practices for implementing AI in auditing practices. Chapter three outlines the research methodology employed in this study, detailing the research design, data collection methods, sampling techniques, and data analysis procedures. The chapter also discusses the research approach, data sources, and tools used to collect and analyze data related to the impact of AI on financial statement auditing. In chapter four, the findings of the study are presented and discussed in detail. The analysis includes an evaluation of the effectiveness of AI tools in improving audit quality, efficiency, and accuracy, as well as an exploration of the challenges and risks associated with AI implementation in auditing practices. The chapter also examines the implications of AI on audit procedures, professional standards, and regulatory requirements. Chapter five concludes the thesis by summarizing the key findings, implications, and recommendations derived from the study. The conclusion highlights the significance of AI in transforming financial statement auditing practices and suggests future research directions in exploring the evolving role of AI in the accounting profession. In conclusion, this thesis provides a comprehensive analysis of the impact of artificial intelligence on financial statement auditing, offering insights into the opportunities and challenges associated with AI integration in auditing practices. The findings of this study contribute to the growing body of knowledge on AI adoption in the accounting profession and provide valuable recommendations for auditors, accounting firms, and regulatory bodies seeking to leverage AI technologies for enhanced audit quality and efficiency.

Thesis Overview