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The rise of the "smart" supply chain: How AI and automation are revolutionizing logistics
1 College of Business, Auburn University, USA.
2 Business Administration, Obafemi Awolowo University, Nigeria.
3 Management Information Systems, University of Illinois, Springfield, USA.
4 Project Management, Northern Eastern University, Toronto, Canada.
5 Data Analytics, Harrisburg University of Science and Technology, USA.
6 Global Supply Chain Management. University of New Haven, West Haven, CT USA.
Review
International Journal of Science and Research Archive, 2024, 12(02), 790–798.
Article DOI: 10.30574/ijsra.2024.12.2.1304
Publication history:
Received on 08 June 2024; revised on 15 July 2024; accepted on 18 July 2024'
Abstract:
The logistics industry is experiencing transformational change driven by the rise of "smart" supply chains enabled by artificial intelligence (AI) and automation. This study examines the transformational impact of this technology, exploring how it increases productivity, reduces costs, and empowers better decision-making and inventory management throughout the supply chain. Focusing on transportation, warehousing, and demand forecasting, the paper provides a comprehensive view of the benefits and challenges associated with implementing AI and automation in logistics. Real-world examples and case studies illustrate the practical applications of these technologies and their potential to reshape the future of supply chain management.
AI algorithms are reshaping inventory management by leveraging big data for precise future predictions, helping companies streamline operations through automated replenishment and reduced stock levels. In transportation, AI optimizes routes considering traffic, weather, and delivery times, leading to fuel savings, faster deliveries, and lower costs. Warehousing benefits from AI with enhanced scheduling, automated processing, and robotic conveyors improving efficiency and accuracy. Furthermore, AI-driven demand forecasting integrates sales data, consumer trends, and social media insights to forecast demand accurately, enhancing production planning and customer service.
The adoption of "smart" supply chains faces several hurdles. Concerns over data privacy due to reliance on big data necessitate stringent data management practices and compliance with privacy laws. Technical barriers and high initial costs for AI implementation are particularly daunting for smaller businesses. Potential solutions, like partnering with AI providers or focusing on long-term benefits, offer strategies to overcome these challenges. Despite these obstacles, AI and automation hold immense potential to revolutionize logistics, offering companies competitive advantages, cost optimization, and superior customer service. As these technologies advance, the future of efficient and agile delivery looks promising.
Keywords:
AI in Supply Chain; Smart Logistics; Automation in Transportation; Inventory Management Optimization; AI-Driven Demand Forecasting; Data Privacy in Logistics
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
