This work is dedicated to exploring the application of machine learning (ML) in transforming business processes within the digital economy. The study examines the potential of ML algorithms for automating management, forecasting key performance indicators (KPIs), and optimizing resource allocation. The article provides a detailed overview of theoretical foundations, the methodology for developing software solutions, and the results of experiments conducted on real-world data from logistics and e-commerce. Examples of using linear regression, random forest, gradient boosting, and neural networks are presented, demonstrating their effectiveness in enhancing productivity and reducing costs. The work emphasizes the strategic role of ML as a tool for achieving competitive advantages and suggests directions for further research in adapting these technologies to various industries.