Thesis Abstract

Abstract
The integration of artificial intelligence (AI) technologies into various industries has significantly transformed operational processes and decision-making capabilities. This thesis aims to explore the impact of AI on financial reporting within the accounting industry. The study investigates how AI technologies such as machine learning algorithms, natural language processing, and robotic process automation have influenced financial reporting practices, accuracy, efficiency, and decision-making processes in accounting firms and organizations. The thesis begins with an introduction that provides an overview of the research topic, followed by a background of the study highlighting the evolution of AI technologies in the accounting industry. The problem statement identifies the gaps and challenges in current financial reporting practices that necessitate the adoption of AI solutions. The objectives of the study focus on examining the benefits, challenges, and implications of AI implementation in financial reporting processes. Limitations and scope of the study outline the constraints and boundaries within which the research is conducted. The significance of the study emphasizes the potential contributions to academic knowledge, practical implications for accounting professionals, and the broader implications for the industry. The structure of the thesis provides a roadmap for the subsequent chapters, which include a detailed literature review, research methodology, discussion of findings, and conclusion. The literature review presents a comprehensive analysis of existing research on AI applications in financial reporting, covering topics such as automation, data analytics, fraud detection, and regulatory compliance. The review highlights the benefits and challenges associated with AI adoption in accounting practices and identifies gaps in current literature that this study aims to address. The research methodology section outlines the research design, data collection methods, sample selection, and data analysis techniques employed in this study. It discusses the rationale behind the chosen methodology and justifies why it is appropriate for investigating the research questions related to the impact of AI on financial reporting in the accounting industry. The discussion of findings chapter presents the results of the empirical analysis, including case studies, surveys, and interviews conducted with accounting professionals and AI experts. It explores the key findings, implications, and recommendations for accounting firms looking to integrate AI technologies into their financial reporting processes. In conclusion, this thesis summarizes the key findings, implications, and contributions to the field of accounting and AI research. It discusses the practical implications for accounting professionals, policy recommendations for regulators, and suggestions for future research directions in the evolving landscape of AI-enabled financial reporting. Overall, this study contributes to a deeper understanding of the impact of AI on financial reporting practices in the accounting industry and provides valuable insights for stakeholders navigating the digital transformation of the profession.

Thesis Overview