Economic Aspects of Introducing Artificial Intelligence Solutions in Logistics and Port Sectors: The Data Entry Case

Abstract

The development and implementation of digital solutions are new in contemporary businesses in logistics. As a next step, the potential of advanced solutions that make use of an AI or ML algorithm and which leverage on data is highly promoted. Yet, the implementation on a large scale of these types of solutions is happening at a slow pace. Recent studies show that a considerable amount of data in the maritime supply chain (MarSC) is still transferred through traditional communication channels (e.g., via e-mails or attached xls, pdf, csv, xml, etc. documents). Human intervention is thus needed to fetch this information and type it over in internal ERP systems. This type of practice opens the scene for extra labor, misinterpretation, or faults. This research puts forward the port users’ perspective on the implementation of AI and ML-based applications for the automatic handling of data. To achieve this goal, a structured survey is launched. The survey results show that, while AI and ML technologies have a high potential to take over repetitive and fault-sensitive tasks, human operators are still needed to maintain customer relations or carry out other planning-related tasks. This initial inquiry shows that, although there are operational costs that are avoided by AI-based technologies, the logistics sector shows low willingness to pay or join development tracks for this type of solutions.