Tuzcuoğlu, Tolga2025-02-202025-02-2020232149-57502717-7629https://hdl.handle.net/20.500.12846/2028This research paper presents an approach for identifying and implementing machine learning use cases in finance and accounting in an agile setting. The study aims to address the gap in the literature, which predominantly covers the individual advantages of using machine learning in accounting and finance; however, it lacks a comprehensive view of the generation of use cases in this field. Furthermore, the study provides insights for organizations in creating machine learning-driven solutions, improving productivity, attaining operational excellence, generating cost savings, and fostering profitable growth. The proposed methodology includes a comprehensive step-by-step strategy comprising 18 distinct process phases categorized into five main clusters.eninfo:eu-repo/semantics/openAccessMachine Learning in Finance and AccountingDigital TransformationUse Case GenerationAgile ManagementCorporate FinanceArticle9289106