Conceptual framework of Artificial Intelligence Integration within Supply Chain

Abstract

Effective Supply Chain Management (SCM) continues to be a major concern in the dynamic world of international trade. This paper offers a conceptual framework for investigating the effects of integrating artificial intelligence (AI) on SCM performance as a whole. The framework as the independent variable identifies AI integration, which includes subcomponents like machine learning, predictive analytics, and natural language processing. These AI components can enhance forecasting, inventory control, and logistics, improve operations, reduce risks, and take advantage of market trends. Nonetheless, the framework recognizes that effective AI integration requires organizational preparedness and strategic alignment. Organizational culture and data governance are two important factors. The approach further strengthens the link between AI and increased decision-making accuracy by introducing Decision Support Systems (DSS) with real-time analytics as a mediating variable. Through an analysis of several viewpoints and academic literature, this paper seeks to offer a thorough grasp of the benefits and difficulties associated with AI-driven supply chain modernization.  By guiding businesses through the intricacies of contemporary supply chains, this framework opens up new possibilities for development, innovation, and value generation.