The Impact of Generative Artificial Intelligence on Knowledge Exchange in Supply Chains

Abstract

This study aims to understand and evaluate the impact of generative artificial intelligence (GenAI) on knowledge exchange processes in supply chains. In the era of digital transformation, tools such as ChatGPT, DALL·E, and other generative models enable the automation of knowledge creation and sharing, significantly transforming collaboration between organizations. The analysis focuses on key aspects such as supporting decision-making processes, optimizing real-time communication, and enhancing knowledge management in distributed structures. The research explores the benefits GenAI can bring to supply chains, including faster information sharing, more accurate forecasting, and automation of operational documentation. At the same time, it identifies potential challenges, such as data security risks, unpredictability of generated outcomes, and ethical considerations regarding the use of artificial intelligence in strategic knowledge management processes. The study includes a literature review and empirical research conducted among companies in sectors such as logistics, manufacturing, and retail. The results indicate that generative artificial intelligence not only supports knowledge exchange but also facilitates more dynamic and integrated models of collaboration. However, the research emphasizes the need to develop guidelines for implementing this technology that address organizational, technological, and regulatory aspects. In conclusion, the findings suggest that the responsible and strategic implementation of GenAI can significantly enhance efficiency and innovation in supply chains while highlighting the importance of investing in employee education and the development of knowledge management policies.