Thesis Abstract

Abstract
Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize various industries, including supply chain management in the retail sector. This thesis explores the impact of AI on supply chain management practices within the retail industry, aiming to provide insights into how AI technologies can enhance efficiency, accuracy, and decision-making processes in the supply chain. The research begins with an introduction to the significance of AI in supply chain management and the specific focus on the retail industry. A comprehensive review of the existing literature on AI applications in supply chain management is conducted to identify trends, challenges, and opportunities. The literature review highlights the benefits of AI technologies such as machine learning, data analytics, and automation in optimizing various aspects of supply chain operations, including demand forecasting, inventory management, logistics, and customer service. The methodology section outlines the research design, data collection methods, and analytical techniques employed in this study. A mixed-methods approach is utilized, combining qualitative interviews with supply chain managers and quantitative data analysis of AI adoption trends in the retail industry. The research methodology aims to provide a holistic understanding of how AI is currently being utilized in supply chain management within the retail sector. The findings of this study reveal the significant impact of AI on supply chain management practices in the retail industry. AI technologies have been shown to improve supply chain visibility, reduce lead times, optimize inventory levels, and enhance overall operational efficiency. However, challenges such as data security, integration complexity, and workforce readiness remain barriers to widespread AI adoption in the retail supply chain. The discussion section critically examines the implications of the research findings and offers recommendations for retail organizations looking to leverage AI in their supply chain operations. Strategies for overcoming implementation barriers, fostering organizational readiness, and maximizing the benefits of AI technologies are discussed in detail. In conclusion, this thesis contributes to the growing body of literature on AI applications in supply chain management, specifically within the retail industry. The findings underscore the transformative potential of AI technologies in enhancing supply chain performance and competitiveness. By embracing AI-driven innovations, retail organizations can streamline their operations, improve customer satisfaction, and adapt to the dynamic market landscape. Keywords Artificial Intelligence, Supply Chain Management, Retail Industry, Machine Learning, Data Analytics, Automation, Optimization, Decision-making.

Thesis Overview

The research project titled "The Impact of Artificial Intelligence on Supply Chain Management in the Retail Industry" aims to explore and analyze how the integration of artificial intelligence (AI) technologies influences supply chain management practices within the retail sector. With the rapid advancements in AI technologies, businesses are increasingly adopting AI-driven solutions to enhance efficiency, reduce costs, and improve decision-making processes across various functions. In the retail industry, where supply chain management plays a crucial role in ensuring seamless operations and customer satisfaction, the adoption of AI has the potential to revolutionize traditional practices. The research will delve into the current landscape of supply chain management in the retail industry, highlighting the key challenges and opportunities faced by businesses in managing complex supply chains. By examining the role of AI in addressing these challenges, the study aims to provide insights into how AI technologies can optimize supply chain operations, enhance forecasting accuracy, streamline inventory management, and improve overall supply chain performance. Through a comprehensive literature review, the research will explore existing studies, frameworks, and best practices related to AI applications in supply chain management, with a focus on the retail industry. By identifying the key trends, benefits, and challenges associated with AI adoption in supply chain management, the study aims to build a solid theoretical foundation for the research. The research methodology will involve a combination of quantitative and qualitative approaches, including surveys, interviews, case studies, and data analysis techniques. By collecting data from retail businesses that have implemented AI in their supply chain operations, the study aims to evaluate the impact of AI on key performance indicators such as cost reduction, lead time optimization, inventory turnover, and customer satisfaction. The findings of the research will be presented and discussed in detail, highlighting the specific ways in which AI technologies have influenced supply chain management practices in the retail industry. By analyzing the implications of AI adoption on business processes, decision-making, and overall performance, the study aims to provide valuable insights for retail managers, practitioners, and policymakers seeking to leverage AI for supply chain optimization. In conclusion, the research project on "The Impact of Artificial Intelligence on Supply Chain Management in the Retail Industry" seeks to contribute to the existing body of knowledge on AI applications in supply chain management and provide practical recommendations for retailers looking to harness the power of AI to drive innovation and competitiveness in their supply chain operations.