AI-Augmented Service Operations Enhancing Customer Satisfaction and Business Performance

Abstract

This research explores the role of Artificial Intelligence (AI) in enhancing service operations across organizations. The study identifies key advantages of AI adoption, such as improved customer experience through personalized troubleshooting and quicker problem resolution, increased operational efficiency, and reduced costs via "Shift Left" approaches. These strategies democratize expert-level troubleshooting, making them accessible to a wider range of employees and end-users, thereby reducing expenses related to customer calls, field visits, and spare parts. The study also emphasizes the critical nature of real-time data analytics in proactive management. To optimize AI deployment, the research recommends a methodical approach involving initial business needs assessment across various departments and a comprehensive review of existing data practices. The study outlines essential steps for the selection and integration of AI tools, focusing on immediate business requirements. Employee training programs are advocated for, to ensure effective utilization of AI tools, which become more accurate with continuous use. A performance monitoring system is also recommended for ongoing evaluation and necessary strategic adjustments. This research also discusses various AI tools available for service operations, including Natural Language Processing for large-scale data analysis, Self-Service tools for instantaneous user support, Intelligent Troubleshooting for quick problem identification and resolution, and Prescriptive Analytics for efficiency and cost improvement. This study serves as a comprehensive guide for organizations looking to substantially improve the effectiveness and efficiency of their service operations through the strategic implementation of AI.