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Auditing and assurance practices have evolved significantly with the integration of artificial intelligence (AI), machine learning, and data analytics. These technologies enhance audit efficiency, accuracy, and risk identification by enabling the analysis of large and complex data sets. While some challenges remain, particularly around governance and oversight, their effective implementation can strengthen audit quality and support more informed professional judgement. Intelligent Strategies for Audit Precision, Transparency, and Risk Forecasting critically examines how auditing and assurance practices are being transformed by emerging technologies. Its central impact lies in bridging the gap between theory and practices, providing frameworks that integrate traditional audit rigor with next-generation technologies. Covering topics such as blockchain-enabled cybercrime, audit precision, and machine learning, this book is an excellent scholarly resource for graduate and doctoral students, researchers, auditors, IT professionals, and more.

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