Artificial intelligence (AI) and machine learning driving efficiency and automation in supply chain Transportation

Rama krishna Vaddy

Abstract


The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies into the realm of supply chain transportation has become a pivotal catalyst for enhanced efficiency and automation. This paper delves into the transformative impact of AI and ML on various facets of supply chain transportation, elucidating how these technologies contribute to optimization, cost reduction, and agility in the logistics landscape. By harnessing the power of predictive analytics, route optimization algorithms, and real-time decision-making, AI and ML empower supply chain operators to make informed decisions swiftly, thereby streamlining processes and mitigating inefficiencies. The study explores case studies, industry applications, and emerging trends, shedding light on the evolving role of these technologies in revolutionizing transportation within the supply chain. Additionally, the paper addresses challenges, ethical considerations, and the need for harmonized regulatory frameworks to ensure responsible and sustainable implementation. As supply chain transportation continues to evolve in the era of digital transformation, this research provides a comprehensive overview of the current landscape and future trajectories shaped by the symbiotic relationship between AI, ML, and the logistics industry.


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