Thesis Abstract

Abstract
The integration of Artificial Intelligence (AI) in supply chain management has revolutionized the way businesses operate, particularly in the retail industry. This thesis explores the impact of AI on supply chain management practices within the retail sector, focusing on how AI technologies enhance efficiency, accuracy, and decision-making processes. The study investigates the adoption and implementation of AI tools such as machine learning, predictive analytics, and robotic process automation in supply chain operations to optimize inventory management, demand forecasting, logistics, and customer service. The research methodology employed a mixed-methods approach, combining qualitative interviews with industry experts and quantitative data analysis of AI adoption trends in retail supply chains. The findings reveal that AI technologies have significantly improved supply chain performance metrics, including cost reduction, inventory turnover, order fulfillment accuracy, and customer satisfaction levels. Additionally, AI-driven supply chain solutions have enabled retailers to adapt to dynamic market conditions, mitigate risks, and capitalize on emerging opportunities in the digital economy. Through a comprehensive review of the literature, this thesis identifies key success factors, challenges, and ethical considerations associated with AI implementation in supply chain management. The discussion of findings highlights the transformative potential of AI technologies in reshaping traditional supply chain practices and fostering innovation in the retail industry. The study concludes with recommendations for retail businesses to leverage AI capabilities strategically, invest in talent development, and establish robust governance frameworks to ensure the responsible and sustainable deployment of AI in supply chain operations. This research contributes to the growing body of knowledge on the implications of AI integration in supply chain management and offers valuable insights for practitioners, policymakers, and academics seeking to navigate the evolving landscape of AI-driven retail supply chains.

Thesis Overview

The research project titled "Analyzing the Impact of Artificial Intelligence on Supply Chain Management in the Retail Industry" aims to investigate the implications, challenges, and opportunities presented by the integration of artificial intelligence (AI) in supply chain management within the retail sector. This study recognizes the growing importance of AI technologies in revolutionizing traditional supply chain processes and seeks to provide an in-depth analysis of how AI adoption can enhance efficiency, reduce costs, and improve overall performance in retail supply chains. The research overview will focus on exploring the following key aspects: 1. **Introduction**: This section will provide an overview of the significance of AI in supply chain management and its relevance to the retail industry. It will highlight the rapid advancements in AI technologies and their potential to transform the way retail supply chains operate. 2. **Background of Study**: The background section will delve into the historical context of supply chain management in the retail sector and the evolution of AI technologies. It will provide a foundation for understanding the current landscape and the need for incorporating AI in supply chain operations. 3. **Problem Statement**: This part will identify the key challenges and issues faced by retail organizations in managing complex supply chains and highlight the gaps that AI can address. It will set the stage for the research by outlining the specific problems that the study aims to tackle. 4. **Objectives of Study**: The research objectives will outline the specific goals and aims of the study, including evaluating the impact of AI on supply chain efficiency, analyzing the benefits and drawbacks of AI adoption, and identifying best practices for integrating AI in retail supply chains. 5. **Limitation of Study**: This section will acknowledge the constraints and limitations of the research, such as time constraints, data availability, and potential biases. It will provide transparency about the scope and boundaries of the study. 6. **Scope of Study**: The scope section will define the boundaries of the research, including the geographical focus, industry sectors within the retail industry, and specific AI technologies considered. It will clarify the extent to which the study aims to explore the impact of AI on supply chain management. 7. **Significance of Study**: This part will highlight the potential contributions of the research to academia, industry practitioners, and policymakers. It will emphasize the importance of understanding the implications of AI in supply chain management for driving innovation and competitiveness in the retail sector. 8. **Structure of the Thesis**: The structure section will provide an overview of the organization of the thesis, outlining the chapters and sub-sections that will be covered in the research work. It will serve as a roadmap for the reader to navigate through the study. 9. **Definition of Terms**: This section will define key concepts, terms, and variables used in the research to ensure clarity and understanding. It will establish a common understanding of the terminology related to AI and supply chain management in the retail industry. By exploring these aspects, the research project will contribute to the existing body of knowledge on the impact of AI on supply chain management in the retail industry, offering insights, recommendations, and actionable strategies for organizations looking to leverage AI technologies to optimize their supply chain operations.