Hybrid Human–AI Collaboration for Optimized Fuel Delivery Management

Iouri Semenov (), Marianna Jacyna, Izabela Auguściak and Mariusz Wasiak
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Iouri Semenov: University WSB Merito in Poznań, ul. Powstańców Wielkopolskich 5, 61-895 Poznań, Poland
Marianna Jacyna: Faculty of Transport, Warsaw University of Technology, 00-662 Warsaw, Poland
Izabela Auguściak: University WSB Merito in Poznań, ul. Powstańców Wielkopolskich 5, 61-895 Poznań, Poland
Mariusz Wasiak: Faculty of Transport, Warsaw University of Technology, 00-662 Warsaw, Poland

Energies, 2025, vol. 18, issue 19, 1-25

Abstract: This article deals with the analysis and exploration of the concept of integrating human knowledge (HK) and artificial intelligence (AI) in the management process. The authors point out that the implementation of advanced AI technologies into already functioning and often complex systems, such as enterprise resource planning (ERP), presents significant technical challenges and requires a well-thought-out integration strategy. The complexity arises from the need to align new solutions with existing processes, resources, and data. Using the example of a fuel distribution system, the authors present the concept of integrating human knowledge (HK) and artificial intelligence (AI) in the management process. The article presents a comprehensive analysis of the smart upgrade of fuel delivery management (FDM) architecture by incorporating an AI app to solve complex problems, such as predicting demand or traffic flows, as well as correctly detecting near-miss events. Technological convergence enables the mutual pursuit of improving the management process by developing soft skills and expanding knowledge managers. The authors’ findings show that an important factor for successful convergence is horizontal and vertical matching of the human knowledge and artificial intelligence cooperation for archive max positive synergy. Some recommendations could be useful for tank truck operators as a starting point to predict demand patterns, smart route planning, etc., where an AI app could be very successful.

Keywords: tank trucking company; fuel delivery management; human–AI app cooperation; horizontal and vertical adaptations; synergy effect (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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