Thesis Abstract

Abstract
The integration of artificial intelligence (AI) technologies into supply chain management processes has revolutionized operations within the retail industry. This thesis explores the significant impact of AI on supply chain management in the retail sector, focusing on how these technologies enhance efficiency, accuracy, and adaptability in meeting consumer demands. The study delves into the key areas of AI application, such as demand forecasting, inventory management, logistics optimization, and customer experience personalization. By analyzing current research, case studies, and industry practices, the thesis aims to provide a comprehensive understanding of the benefits and challenges associated with AI adoption in retail supply chains. Furthermore, the research methodology involves a mixed-methods approach, combining quantitative data analysis and qualitative case studies to explore the practical implications of AI implementation. The findings reveal that AI technologies have the potential to streamline supply chain processes, reduce operational costs, and improve decision-making capabilities for retail organizations. However, challenges related to data integration, organizational readiness, and workforce reskilling must be addressed to fully leverage the benefits of AI in supply chain management. The conclusion summarizes the key findings and recommendations for retail industry stakeholders to effectively harness the transformative power of AI in optimizing supply chain operations and enhancing overall business performance.

Thesis Overview