What question did this study set out to answer?

The aim focuses on improving inventory management efficiency and minimizing costs through AI-driven methods.

April 26, 2026Open Access

Repository Copy of: Artificial Intelligence-Driven Inventory Management: Optimizing Stock Levels and Reducing Costs Through Advanced Machine Learning Techniques

Key Points

The aim focuses on improving inventory management efficiency and minimizing costs through AI-driven methods.
Preservation of academic article in repository for accessibility
Evaluation of AI approaches in inventory management
Focus on machine learning techniques for optimizing stock levels
Identified cost-saving opportunities through advanced AI models
Showed improvements in stock level management efficiency
Demonstrated potential for reduced operational expenses

Abstract

This record is a repository-preserved copy of an article originally published in The European Journal of Research and Development by Orclever Science it is not the version of record, and Zenodo is not the publisher of this work. Version of Record (primary publication): https://doi.org/10.56038/ejrnd.v4i4.615 Publisher: Orclever Science & Research Group. Journal: The European Journal of Research and Development. For citation, please use the Crossref DOI and the journal citation above — not the Zenodo DOI.

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