An Empirical Investigation in Analyzing the Key Factors Influencing the Implementation of AI in Supply Chain Management for Enhancing Operational Efficiency

Abstract Purpose There is a growing need to implement artificial intelligence (AI) in different areas of business to enhance overall efficiency, reduce operational costs, and achieve sustainable growth. One domain that has gained more importance is logistics, supply chain management (SCM), and related areas. The basic purpose of the chapter is to understand the key factors that impact the implementation of AI in the SCM process. Design Methodology The article uses a mixed model approach, analyzing both primary and secondary data sources. The researcher used a quantitative methodology, and the primary data were collected using a structured questionnaire. Findings The overall findings state that key factors like technology consideration, return on investment (ROI) in AI, data security, and customer satisfaction influence the organization’s implementation of the stated technologies. Management needs to focus on these aspects before implementing the technologies. Originality/Value This chapter focuses more on the empirical understanding of the main factors that influence operational efficiency in the chosen domain. The existing literature focuses more on the factors in isolation. However, this analysis intends to use four key variables and how this impacts the organization’s implementation of the stated technology for operational efficiency.