An Overview of Optimized Inventory Management Models in Technology Companies: Historical Developments, Practical Applications, and AI-Driven Approaches

This article provides a comprehensive overview of improved inventory management models in technology companies and how AI methodologies such as machine learning, predictive analytics, and optimization algorithms are revolutionizing inventory management by enabling real-time decision making, accurate demand forecasting, and automated inventory replenishment by integrating historical context with state-of-the-art AI techniques. This article provides a thorough understanding of how technology companies can leverage advanced inventory management models to maintain a competitive edge and challenges associated with implementing AI- driven inventory systems. The findings offer valuable insights for both industry practitioners and academics, contributing to the development of more resilient and adaptive inventory management strategies within the rapidly evolving technology sector.

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Published
2024-12-20
DOI
https://doi.org/10.1109/acai63924.2024.10899588
Primary Topic
Digital Transformation in Industry
Type
article
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article

An Overview of Optimized Inventory Management Models in Technology Companies: Historical Developments, Practical Applications, and AI-Driven Approaches

Mohammed Mahde Mahmood Arnawtee, Murooj Fadhil Zaiter Zaiter
Digital Transformation in Industry
article

An Overview of Optimized Inventory Management Models in Technology Companies: Historical Developments, Practical Applications, and AI-Driven Approaches

Mohammed Mahde Mahmood Arnawtee, Murooj Fadhil Zaiter Zaiter
article en

Abstract

This article provides a comprehensive overview of improved inventory management models in technology companies and how AI methodologies such as machine learning, predictive analytics, and optimization algorithms are revolutionizing inventory management by enabling real-time decision making, accurate demand forecasting, and automated inventory replenishment by integrating historical context with state-of-the-art AI techniques. This article provides a thorough understanding of how technology companies can leverage advanced inventory management models to maintain a competitive edge and challenges associated with implementing AI- driven inventory systems. The findings offer valuable insights for both industry practitioners and academics, contributing to the development of more resilient and adaptive inventory management strategies within the rapidly evolving technology sector.

Ural Federal University (RU)
Industry, innovation and infrastructure
Openalex Percentile: Top 59%
Digital Transformation in Industry
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