AI, Big Data and the Green Supply Chain: Innovation and Adoption Challenges

Abstract

The rise of digital technologies is profoundly transforming supply chain management, particularly from an ecological standpoint. Artificial Intelligence (AI) and Big Data have emerged as strategic levers to optimize the Green Supply Chain (GSC), enhancing flow forecasting, resource management, and carbon footprint reduction [1], [2]. This study is based on a structured review of the scientific literature, drawing on frameworks such as the Technology Acceptance Model (TAM) [3] and the ResourceBased View (RBV) [4], to analyze the impact of these technologies on green supply chains at the international level, as well as the barriers to their adoption in Morocco. While the adoption of AI and Big Data shows strong promise for enhancing logistics sustainability, its diffusion remains constrained by infrastructural gaps, limited technical capacity, and financial barriers, particularly in emerging economies. A comparison between global trends and the Moroccan context reveals a lag in adoption, despite the gradual emergence of initiatives in sectors such as agriculture and logistics. In light of these findings, several recommendations are proposed, including strengthening AI and data science training, encouraging technological investments, and improving access to digital infrastructure. This study thus underlines the urgency of accelerating the digital transition so that Morocco can fully harness technological innovations and enhance the sustainability and competitiveness of its supply chains.