AI-based predictive analytics in international supply chain management of multinational corporations

Abstract

The purpose of this paper is to analyze the opportunities and limitations of artificial intelligenec-based predictive analytics in managing international supply chains of transnational corporations. The research methodology is based on a systemic analysis of academic literature and a generalization of machine learning applications by leading logistics and manufacturing companies operating in global markets. The results systematize the principal areas of predictive analytics application – demand forecasting, inventory management, and transportation planning – and identify factors that limit the effectiveness of such solutions in an international context, including data heterogeneity and the probabilistic nature of forecasts. The study concludes that sustainable benefits from predictive analytics require technological tools to be combined with continued qualified human oversight at all stages of the supply chain.