Thesis Abstract

Abstract
The integration of artificial intelligence (AI) in supply chain management has revolutionized operations in various industries, including the retail sector. This thesis explores the impact of AI on supply chain management within the retail industry, focusing on the opportunities and challenges it presents. The study investigates how AI technologies such as machine learning, predictive analytics, and robotic process automation are transforming traditional supply chain processes and enhancing efficiency, accuracy, and decision-making in retail operations. The research begins with a comprehensive review of the literature on AI applications in supply chain management, highlighting key concepts, theories, and previous studies in this area. Subsequently, the methodology chapter outlines the research design, data collection methods, and analysis techniques employed to investigate the impact of AI on supply chain management practices in retail. Findings from the study reveal that the adoption of AI technologies in supply chain management enables retailers to optimize inventory management, streamline logistics operations, and enhance demand forecasting accuracy. Moreover, AI-powered tools facilitate real-time data analysis, predictive modeling, and automated decision-making, leading to improved supply chain visibility, responsiveness, and customer service levels. The discussion chapter critically analyzes the implications of AI integration in supply chain management for retail businesses, addressing both the benefits and challenges associated with this technological advancement. Factors such as data privacy, cybersecurity, organizational readiness, and workforce skills are identified as critical considerations for successful AI implementation in supply chain operations. In conclusion, this thesis underscores the transformative potential of AI in revolutionizing supply chain management practices in the retail industry. By leveraging AI technologies effectively, retailers can gain a competitive edge, enhance operational efficiency, and meet evolving customer demands in an increasingly complex and dynamic marketplace. The study contributes to the existing body of knowledge on AI in supply chain management and provides insights for practitioners, policymakers, and researchers seeking to navigate the opportunities and challenges presented by AI integration in 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 of integrating artificial intelligence (AI) technologies in supply chain management within the retail sector. This comprehensive study is motivated by the increasing adoption of AI in various industries and the potential benefits it offers in optimizing supply chain operations in retail. The research will commence with a detailed introduction providing an overview of the significance of AI in supply chain management and its specific relevance to the retail industry. The background of the study will delve into the evolution of AI technologies and their application in different business functions, leading up to their integration into supply chain processes. The problem statement will clearly articulate the research gap in understanding how AI impacts supply chain management practices in retail, highlighting the need for further investigation in this area. The objectives of the study will be outlined to guide the research process, focusing on analyzing the benefits and challenges of AI implementation in retail supply chains, identifying best practices for integration, and assessing the overall impact on operational efficiency and performance. The limitations of the study will also be acknowledged to provide transparency regarding the scope and constraints of the research. The scope of the study will encompass a comprehensive analysis of AI technologies, including machine learning, predictive analytics, and automation, and their specific applications in inventory management, demand forecasting, logistics optimization, and customer service within the retail supply chain. The significance of the study lies in its potential to offer valuable insights to retail managers, supply chain professionals, and policymakers on leveraging AI to enhance competitiveness and sustainability in the dynamic retail landscape. The structure of the thesis will be organized into distinct chapters, including an introduction, literature review, research methodology, discussion of findings, and conclusion. Each chapter will be further divided into sub-sections to provide a clear and logical flow of the research work. Additionally, a comprehensive glossary of key terms and concepts related to AI and supply chain management will be included to ensure clarity and understanding throughout the thesis. In summary, this research project aims to contribute to the existing body of knowledge on the integration of AI in supply chain management within the retail industry. By examining the impact of AI technologies on key supply chain functions and performance metrics, this study seeks to provide actionable insights and recommendations for retailers seeking to harness the full potential of AI in optimizing their supply chain operations.