Thesis Abstract

Abstract
This thesis investigates the implementation of Artificial Intelligence (AI) in supply chain management within the context of the retail industry. The research aims to explore how AI technologies can enhance supply chain efficiency, accuracy, and decision-making processes in retail operations. The study focuses on a case study approach to analyze the application of AI in a real-world retail setting, providing insights into the challenges, benefits, and implications of AI adoption in supply chain management. The introductory chapter sets the foundation for the research by presenting the background, problem statement, objectives, limitations, scope, significance of the study, and defining key terms related to AI and supply chain management. The subsequent literature review chapter critically evaluates existing studies and theories on AI in supply chain management, highlighting key themes such as AI technologies, supply chain optimization, predictive analytics, and automation. The research methodology chapter outlines the approach taken to investigate the implementation of AI in supply chain management in the retail industry. The methodology includes research design, data collection methods, sample selection, data analysis techniques, and ethical considerations. Through interviews, surveys, and data analysis, the study gathers empirical evidence to support the findings and discussions presented in the subsequent chapters. The findings chapter presents the results of the case study analysis, discussing the practical applications of AI technologies in improving supply chain processes, inventory management, demand forecasting, and customer service in a retail environment. The chapter also addresses the challenges faced during the implementation of AI, such as data quality issues, integration complexities, and organizational resistance to change. The discussion chapter critically examines the implications of the findings, offering insights into the potential benefits of AI adoption in supply chain management and the strategies for overcoming implementation barriers. The chapter also reflects on the theoretical and practical contributions of the research, identifying areas for further study and development in the field of AI-enabled supply chain management. In conclusion, this thesis summarizes the key findings, implications, and recommendations derived from the study on the implementation of AI in supply chain management in the retail industry. The research contributes to the growing body of knowledge on AI technologies in supply chain operations, offering practical insights for retailers and supply chain professionals seeking to leverage AI for competitive advantage and operational excellence.

Thesis Overview

Research Overview: The project titled "Implementation of Artificial Intelligence in Supply Chain Management: A Case Study in the Retail Industry" aims to investigate the practical applications and impact of artificial intelligence (AI) in enhancing supply chain management within the retail sector. With the rapid advancements in AI technology, there is a growing interest in leveraging these tools to optimize supply chain processes, improve efficiency, and drive competitive advantage. The retail industry is known for its complex and dynamic supply chain networks, characterized by numerous stakeholders, diverse product ranges, and fluctuating consumer demands. Traditional supply chain management practices often struggle to adapt quickly to these challenges, leading to inefficiencies, delays, and increased costs. By introducing AI technologies into supply chain operations, retailers can potentially revolutionize their processes, enabling real-time decision-making, predictive analytics, and automation of routine tasks. This research project will focus on a case study approach, examining how a specific retail company has implemented AI solutions to enhance its supply chain management practices. By conducting in-depth interviews, surveys, and data analysis within the chosen organization, the study aims to uncover the key drivers, challenges, and outcomes of integrating AI in the supply chain. Key areas of investigation will include the identification of AI tools and technologies utilized, the impact on inventory management, demand forecasting, logistics optimization, and customer service, as well as the organizational changes required to support AI implementation. Additionally, the study will explore the potential risks and limitations associated with AI adoption in supply chain management and provide recommendations for successful integration based on the case study findings. Overall, this research project seeks to contribute valuable insights into the practical implications of implementing AI in supply chain management within the retail industry. By understanding the opportunities and challenges associated with AI adoption, organizations can better position themselves to harness the full potential of AI technologies to drive innovation, efficiency, and competitiveness in their supply chain operations.