Perceived Challenges and Benefits of AI Implementation in Customer Relationship Management Systems

Abstract

This study explores the multifaceted implications of Artificial Intelligence (AI) implementation in Customer Relationship Management (CRM) systems. The research is broken down into distinct variables, each representing a unique aspect of the study. These variables include Assistance, Automation, Personalization, Customer Service Improvement, and Decision-making. Assistance refers to how AI can aid human workers by providing suggestions, automating repetitive tasks, or helping to sift through large amounts of data. Automation discusses the use of AI to perform tasks with minimal human intervention, thereby increasing efficiency. Personalization examines how AI can use data to tailor services or products to the individual needs and preferences of each customer. Customer Service Improvement refers to the use of AI to enhance customer service, for example, by improving response times, accuracy, or personalization. Lastly, Decision-making explores how AI can assist in decision-making by analyzing large amounts of data and providing insights or recommendations. The research employs a systematic and iterative coding process, identifying 'meaning units' from interview transcriptions and grouping these into 'sub-dimensions' based on shared meaning or context. This process has resulted in 33 distinct sub-dimensions that encapsulate the key themes or concepts emerging from the data. In essence, this paper serves as a comprehensive guide to understanding the key elements that have been explored in this study, providing a clear and concise summary of the findings related to each particular area. It is instrumental in providing a holistic view of the research, allowing readers to quickly grasp the breadth and depth of the study.