Complex problem-solving in enterprises with machine learning solutions

Abstract

This paper explores the application of machine learning (ML) in solving complex problems within enterprises across various industries. By leveraging ML, businesses can enhance operational efficiency, customer experience, and risk management. The study reviews existing literature to develop a theoretical model that integrates ML applications into business processes. Key findings indicate that ML significantly improves quality control and predictive maintenance in manufacturing, leading to reduced costs and increased productivity. Additionally, ML-driven personalized marketing and customer support enhance customer satisfaction and loyalty. In financial management, ML enhances fraud detection and credit risk assessment, contributing to financial stability and security. The paper provides suggestions for effectively implementing ML strategies to optimize business performance and addresses the implications for future business operations in a rapidly evolving technological landscape.