Thesis Abstract

**Abstract
** The integration and utilization of Artificial Intelligence (AI) technologies in supply chain management have become increasingly prevalent in the retail industry. This thesis investigates the impact of AI on supply chain management processes and practices within the retail sector. The study explores how AI technologies such as machine learning, predictive analytics, and robotic process automation are transforming traditional supply chain operations, enhancing efficiency, and improving decision-making processes. Through a comprehensive review of literature, empirical data analysis, and case studies, this research aims to provide valuable insights into the benefits and challenges associated with incorporating AI in retail supply chain management. The research methodology involves a mixed-method approach, combining quantitative data analysis with qualitative case studies to examine the effects of AI adoption on key performance indicators, operational processes, and strategic decision-making in retail supply chains. The study will also investigate the factors influencing the successful implementation of AI technologies in supply chain management and identify best practices for leveraging AI to optimize supply chain operations in the retail industry. The findings of this research will contribute to the existing body of knowledge on the application of AI in supply chain management and offer practical recommendations for retail organizations looking to harness the potential of AI technologies to enhance their supply chain efficiency, responsiveness, and competitiveness. By shedding light on the opportunities and challenges of integrating AI into retail supply chain operations, this thesis aims to provide valuable insights for industry practitioners, researchers, and policymakers seeking to navigate the evolving landscape of AI-driven supply chain management in the retail sector.

Thesis Overview

The research project titled "Exploring the Impact of Artificial Intelligence on Supply Chain Management in the Retail Industry" aims to investigate the influence and implications of artificial intelligence (AI) on supply chain management within the retail sector. This study is motivated by the increasing adoption of AI technologies in various industries and the potential transformative effects it can have on traditional supply chain practices. The retail industry is constantly evolving, facing challenges such as demand fluctuations, inventory management, logistics optimization, and customer expectations. AI technologies offer opportunities to enhance decision-making processes, automate routine tasks, improve forecasting accuracy, and optimize supply chain operations. Understanding how AI can be effectively integrated into supply chain management practices is crucial for retail companies to stay competitive and meet the demands of modern consumers. This research will delve into the various applications of AI in supply chain management, including predictive analytics, machine learning, natural language processing, and robotic process automation. It will explore how these technologies can streamline processes, reduce costs, improve efficiency, and enhance overall supply chain performance in the context of the retail industry. Through a combination of literature review, case studies, and empirical analysis, this study seeks to identify the key benefits, challenges, and best practices associated with implementing AI in retail supply chains. The research will also investigate the impact of AI on supply chain visibility, collaboration, sustainability, and customer experience. By shedding light on the implications of AI in supply chain management for retail businesses, this project aims to provide valuable insights for industry practitioners, policymakers, and researchers. Ultimately, the findings of this study will contribute to the growing body of knowledge on the intersection of artificial intelligence and supply chain management in the retail sector, offering practical recommendations for leveraging AI technologies to drive innovation and competitive advantage.