Driving the circular economy: How artificial intelligence could empower transportation and logistics companies to lead the transition

Purpose Artificial Intelligence (AI) has great potential to contribute to the operational, environmental, and social performance of supply chains. The purpose of this study is to examine the implications of AI adoption and implementation for the supply chains of logistics-intensive companies, with the aim of stimulating discussion on the future of transportation and logistics. Design/methodology/approach A systematic review of the literature, following the PRISMA protocol, was conducted to identify AI applications in supply chains. A distinction was made between logistics-intensive companies for which transportation and logistics are a supporting function, and transportation and logistics companies for which this is their main business model. We extrapolated from the existing literature to identify opportunities for digital transformation for transportation and logistics companies. Findings Of the 244 studies retained for analysis, the majority were review studies or focused on developing Machine Learning algorithms and models. The few articles documenting AI applications in supply chains focused on digitalization, neglecting opportunities for digital transformation. The study argues that the adoption of AI has the potential to negatively impact the current business model of transportation and logistics companies by (1) reducing the need for transportation and warehousing activities, and (2) increasing competition from other logistics-intensive companies that use AI to develop the capabilities to insource their transportation, warehousing, and other logistic activities. Originality The study illustrates how AI could create opportunities for digital transformation in transportation and logistics companies, enabling them to become orchestrators of the circular transition, and proposes a corresponding agenda for future research.