Digital transformation of logistics: the role of artificial intelligence and Big Data in managing transport flows and optimizing loading and unloading operations - Minakova, Svitlana; Minakov , Vitaly; Minakova , Olena; Minakov , Oleksiy (FINANCIAL AND CREDIT SYSTEMS: PROSPECTS FOR DEVELOPMENT, 2025)
The digitalization of the economy covers all types of economic activity, among which logistics activities and the implementation of AI and Big Data tools are distinguished. Problem statement. Comprehensive approach to the study of the digital transformation of logistics (DTL) based on the use of AI and Big Data to manage transport flows (MTF) and optimize loading and unloading operations (OPUO). Unresolved aspects of the problem. Due to the dynamic development of the processes of DTL, a comprehensive approach based on the use of AI and Big Data to MTF and OPUO requires additional research. Purpose of the article. Research on the scientific foundations and practical recommendations for MTF and OPUO based on AI and Big Data. Presentation of the main material. It is noted that the driver of the spread of AI and Big Data tools in logistics is the WEF platform, which also considers the processes of DTL towards green logistics and decarbonization using AI and Big Data tools. The results of research conducted in 2025 among logistics companies in Europe and the USA showed that a quarter of respondents have already integrated AI and Big into their activities, half of them partially use AI and Big, and 57% plan to introduce these tools into their activities. A description of the main companies involved in the development and distribution of applied software solutions for logistics and logistics companies is provided. Conclusions. A list of the main obstacles (large initial investments, outdated data processing and storage technologies, lack of qualified labor, variability and instability of the regulatory field, costs of maintaining excess inventory in the warehouse) and opportunities (increasing the level of optimization and self-optimization of logistics processes, optimization of resource costs, autonomy of supply chains, real-time processing of large volumes of data and forecasting demand for products over time) in the development of AI and Big Data tools in MTF and OPUO has been formed.