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Abstract
This study explores the transformative role of Artificial Intelligence in financial auditing and assurance services, focusing on how AI and machine learning technologies are reshaping traditional audit processes. With increasing demands for accuracy, efficiency, and reduced human error, AI-driven tools have the potential to significantly enhance audit quality and risk assessment capabilities. Using a mixed-methods approach, this research combines quantitative data analysis from financial audits incorporating AI technologies with qualitative insights gathered through semi-structured interviews with industry professionals. The quantitative phase evaluates the impact of AI on audit efficiency and error reduction, while the qualitative phase offers perspectives on the challenges and opportunities AI presents in the auditing landscape. The study aims to provide a comprehensive understanding of how AI can improve audit practices, drive better decision-making, and address evolving risks in the financial sector. This research offers critical insights for auditors, regulators, and firms seeking to integrate AI into auditing processes to enhance both compliance and innovation.
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