Thesis Abstract

Abstract
The rapid advancement of technology has significantly transformed various aspects of the business world, including financial statement auditing in publicly listed companies. This thesis explores the impact of artificial intelligence (AI) on financial statement auditing practices and procedures in the context of publicly listed companies. The study aims to investigate how the integration of AI technologies influences the efficiency, effectiveness, and accuracy of auditing processes, as well as the implications for auditors and stakeholders in the auditing profession. The research methodology employed a mixed-methods approach, combining qualitative and quantitative data collection techniques. A comprehensive literature review was conducted to examine existing studies, theories, and frameworks related to AI in auditing, providing a theoretical foundation for the study. The empirical research involved surveys and interviews with auditors, financial professionals, and AI experts to gather insights and perspectives on the use of AI in financial statement auditing. The findings of the study reveal that the integration of AI technologies in financial statement auditing has the potential to enhance audit quality, reduce errors, and improve decision-making processes. AI tools such as machine learning algorithms, data analytics, and robotic process automation offer opportunities to automate routine tasks, identify anomalies, and extract valuable insights from large datasets. However, challenges related to data privacy, cybersecurity, and ethical considerations must be addressed to ensure the responsible and ethical use of AI in auditing practices. The implications of the study underscore the importance of continuous professional development for auditors to acquire the necessary skills and knowledge to leverage AI technologies effectively. Training programs, certification courses, and collaboration with technology experts are essential to prepare auditors for the digital transformation of the auditing profession. Moreover, regulatory bodies and standard-setting organizations play a crucial role in establishing guidelines, standards, and best practices for the implementation of AI in auditing. In conclusion, this thesis contributes to the existing body of knowledge on the impact of AI on financial statement auditing in publicly listed companies. The study highlights the opportunities and challenges associated with the adoption of AI technologies in auditing practices, emphasizing the need for auditors to embrace innovation, adapt to technological changes, and uphold professional standards in the digital age. By embracing AI, auditors can enhance their audit processes, deliver value-added services to clients, and maintain the trust and confidence of stakeholders in the financial reporting ecosystem.

Thesis Overview