Ahmad Y. A. Bani Ahmad, Firas Tayseer Ayasrah, Hamzeh Alhawamdeh, Mahmoud Allahham, Wasef Ibrahim Almajali, Irwanto Irwanto, Febri Prasetya, Aprilla Fortuna
This study aims to investigate the influence of AI-empowered optimizations on logistic processes centering around benchmark obfuscation. In a high-tech era, the application of AI to logistics has opened up several areas that can assist in better operational efficiency and competitiveness. This is the first study to explore how AI-powered tools like predictive analytics and automation interact with benchmarks in a complex system designed for optimization. This research uses a quantitative analysis with Smart PLS and collects data from the logistics sector. Our study offers helpful conclusions regarding the several determinants for successful AI-based optimization in logistics. The research results indicate that the AI technologies most commonly used today for data analysis, prediction power, and automation of processes are associated with better results in process benchmarking with impact directly on cost reduction using new ways to work. Nevertheless, logistical AI faces obstacles such as integrating it into existing systems and security concerns. The results provide theoretical contributions to the current literature and offer practical insights that could assist those logistics professionals seeking operational and strategic benefits across benchmarking with AI. © 2025 IEEE.
Middle East University, Faculty of Business, Department of Accounting and Finance, Amman, Jordan; Al Ain University, College of Education, Humanities and Science, Al Ain, United Arab Emirates; Jerash University, Business Faculty, Jerash, Jordan; Amman Arab University, Business Faculty, Amman, Jordan; Jakarta State University, Department of Chemistry Education, Jakarta, Indonesia; Universitas Negeri Padang, Faculty of Engineering, Department of Mechanical Engineering, Padang, Indonesia
