Published: 2026-02-01
The Impact of Artificial Intelligence and Big Data Integration on Decision-Making and Supply Chain Efficiency in Modern Logistics
DOI: 10.35870/ijmsit.v6i1.6344
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Abstract
This study examines the impact of the integration of Artificial Intelligence (AI) and Big Data on decision-making and operational efficiency in the logistics sector. AI accelerates data processing, while Big Data enables large-scale analysis to make more informed decisions. Both technologies can improve planning, distribution, and equipment monitoring, as well as enhance supply chain operability by reducing human error. The study included case studies of 50 logistics companies that have adopted AI and Big Data. Using this quantitative method, the research team developed survey questions based on the four parameters listed above and answered them by interviewing representatives from each company's management department. The results show that 70% of companies have implemented AI across various operational aspects. Sixty percent of companies are fully utilizing Big Data. AI improves demand forecast accuracy by 30% and reduces inventory waste by 25%. AI implementation saves 15-20% on delivery time in route management, while reducing operational costs. However, there are several drawbacks: it is expensive to build systems using all these technologies, there is a shortage of skilled labor, and companies struggle to integrate new systems with existing legacy systems. This study also shows that organizational readiness plays a critical role in leveraging the technical potential of these two technologies to improve supply chain operational efficiency.
Keywords
Artificial Intelligence ; Big Data ; Decision-Making ; Operational Efficiency ; Supply Chain ; Logistics
Article Information
This article has been peer-reviewed and published in the International Journal of Management Science and Information Technology. The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 6 No. 1 (2026)
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Section: Articles
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Published: %750 %e, %2026
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License: CC BY 4.0
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Copyright: © 2026 Authors
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DOI: 10.35870/ijmsit.v6i1.6344
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Jeni Karay
Faculty of Science and Technology, Information Systems Study Program, Universitas Ottow Geisler, Jayapura City, Papua Province, Indonesia
Reni Koibur
Faculty of Science and Technology, Information Systems Study Program, Universitas Ottow Geisler, Jayapura City, Papua Province, Indonesia
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