Enhancing Supply Chain Efficiency through Machine Learning and AI Integration

Vivek Prasanna Prabu

doi:10.5281/zenodo.15155314

Enhancing Supply Chain Efficiency through Machine Learning and AI Integration

Author(s)	Vivek Prasanna Prabu
Country	United States
Abstract	In today’s hyper-connected global economy, supply chains must be agile, resilient, and responsive to a multitude of challenges, from demand fluctuations and geopolitical disruptions to sustainability mandates and evolving customer expectations. Traditional supply chain models, often linear and reactive, struggle to meet these demands. The integration of artificial intelligence (AI) and machine learning (ML) offers transformative potential by enabling real-time data processing, predictive analytics, and autonomous decision-making. AI and ML algorithms can optimize logistics, forecast demand, manage risks, and streamline procurement with unprecedented speed and accuracy. This technological advancement facilitates end-to-end visibility, reduces operational costs, and enhances service levels. Moreover, ML can uncover hidden patterns in large datasets, enabling dynamic inventory planning, route optimization, supplier risk assessment, and maintenance scheduling. Organizations like DHL, Maersk, Amazon, and IBM are already leveraging AI/ML to build intelligent, adaptive supply chain ecosystems that learn from disruptions and evolve continuously. Despite these benefits, challenges remain in data integration, system interoperability, model explainability, and workforce readiness. Successful implementation requires a strategic roadmap, cross-functional collaboration, and a robust data governance framework. Ethical considerations must also be addressed, including transparency, fairness, and sustainability. This white paper explores the foundational technologies, practical applications, implementation frameworks, and business impacts of AI/ML integration in supply chain management. Drawing on industry case studies and expert insights, it provides a comprehensive guide for organizations aiming to future-proof their supply chains through intelligent automation and analytics.
Field	Engineering
Published In	Volume 15, Issue 1, January-June 2024
Published On	2024-02-07
Cite This	Enhancing Supply Chain Efficiency through Machine Learning and AI Integration - Vivek Prasanna Prabu - IJAIDR Volume 15, Issue 1, January-June 2024. DOI 10.5281/zenodo.15155314
DOI	https://doi.org/10.5281/zenodo.15155314
Short DOI	https://doi.org/g9cs8n

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Enhancing Supply Chain Efficiency through Machine Learning and AI Integration

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