Artificial Intelligence and the Transformation of Logistics Companies’ Business Models: Evidence Synthesis

Background: The transformation of businesses resulting from the implementation of artificial intelligence (AI) is currently underway. A research gap lies in the absence of research examining the impact of AI on logistics companies from the perspective of its effect on their business models. Methods: Logistics companies are described, using PRISMA methodology, through an analysis of 151 open-access scientific studies indexed in the Web of Science and Scopus databases, using the Business Model Canvas (BMC) framework and its nine blocks. This research focuses on identifying how AI might influence individual BMC blocks. The research follows the PRISMA methodology and is based on an analysis of 108 open-access scientific studies indexed in the Web of Science and Scopus databases. Results: The findings suggest that AI is transforming the business models of logistics companies across all nine of its blocks. This transformation is taking the form of AI-supported, data-driven ecosystems. Across all BMC blocks, the importance of data analytics, automation, predictive management, service personalization, and digital interoperability is growing. Conclusions: The competitive advantage of logistics companies is increasingly based on the ability to process data, coordinate processes in real time, and create adaptive logistics systems, thereby broadening the interpretation of how logistics companies operate.