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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM49535

AI-Driven Inventory Optimization: Enhancing Supply Chain Efficiency

Stream/Area:

-

Subject:

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Paper ID:

IJSREM49535

Volume:

9 |

6 |

Jun 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem49535

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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AS

Aditya Singh

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Abstract

This paper explores the transformative role of Artificial Intelligence (AI) in inventory management, highlighting how AI-powered tools such as machine learning, predictive analytics, and automation optimize inventory levels, reduce holding costs, and improve forecasting accuracy. Drawing from case studies of Amazon, Mayo Clinic, and a focused analysis of Safe Shop India, the research evaluates AI’s real-world impact on operational efficiency and customer satisfaction. The findings advocate for the strategic implementation of AI in inventory systems to achieve agile, data-driven, and resilient supply chains.

KEYWORDS

Artificial Intelligence Inventory Management Supply Chain Optimization Forecasting Case Study

Cite This Article

Aditya Singh, "AI-Driven Inventory Optimization: Enhancing Supply Chain Efficiency," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 6, Jun 2025. https://doi.org/10.55041/ijsrem49535

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Publication Date

6/4/2025

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The authors declare no conflict of interest related to this research work.

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