AI for Predictive Analytics in Retail: Enhancing Inventory Management and Customer Engagement

Artificial Intelligence (AI) is rapidly transforming various industries, and retail is no exception. Predictive analyticspowered by AI is becoming a game-changer in the retail sector, especially when it comes to inventory management and customerengagement. By leveraging machine learning algorithms and big data, retailers can predict customer demand, optimize stocklevels, reduce waste, and improve overall operational efficiency. This paper explores the role of AI-driven predictive analytics inretail, focusing on its impact on inventory management and customer engagement. It discusses the underlying technologies, suchas machine learning and natural language processing, and highlights real-world applications where AI is revolutionizing retailoperations. Additionally, the paper examines the challenges retailers face in implementing AI technologies and provides insightsinto the future potential of AI in shaping the retail landscape.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-03
DOI
https://doi.org/10.5281/zenodo.15334039
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

AI for Predictive Analytics in Retail: Enhancing Inventory Management and Customer Engagement

Zenodo (CERN European Organization for Nuclear Research)
Forecasting Techniques and Applications
article

AI for Predictive Analytics in Retail: Enhancing Inventory Management and Customer Engagement

article en

Abstract

Artificial Intelligence (AI) is rapidly transforming various industries, and retail is no exception. Predictive analyticspowered by AI is becoming a game-changer in the retail sector, especially when it comes to inventory management and customerengagement. By leveraging machine learning algorithms and big data, retailers can predict customer demand, optimize stocklevels, reduce waste, and improve overall operational efficiency. This paper explores the role of AI-driven predictive analytics inretail, focusing on its impact on inventory management and customer engagement. It discusses the underlying technologies, suchas machine learning and natural language processing, and highlights real-world applications where AI is revolutionizing retailoperations. Additionally, the paper examines the challenges retailers face in implementing AI technologies and provides insightsinto the future potential of AI in shaping the retail landscape.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 44%
Forecasting Techniques and Applications
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AI for Predictive Analytics in Retail: Enhancing Inventory Management and Customer Engagement · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS