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Revolutionizing Retail Operations through Generative AI: A Systematic Review

by Ananya Ghosh Chowdhury, Goutham Bandapati, Phanidhar Chilakapati
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 4
Year of Publication: 2025
Authors: Ananya Ghosh Chowdhury, Goutham Bandapati, Phanidhar Chilakapati
10.5120/ijca2025924834

Ananya Ghosh Chowdhury, Goutham Bandapati, Phanidhar Chilakapati . Revolutionizing Retail Operations through Generative AI: A Systematic Review. International Journal of Computer Applications. 187, 4 ( May 2025), 5-11. DOI=10.5120/ijca2025924834

@article{ 10.5120/ijca2025924834,
author = { Ananya Ghosh Chowdhury, Goutham Bandapati, Phanidhar Chilakapati },
title = { Revolutionizing Retail Operations through Generative AI: A Systematic Review },
journal = { International Journal of Computer Applications },
issue_date = { May 2025 },
volume = { 187 },
number = { 4 },
month = { May },
year = { 2025 },
issn = { 0975-8887 },
pages = { 5-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number4/revolutionizing-retail-operations-through-generative-ai-a-systematic-review/ },
doi = { 10.5120/ijca2025924834 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-05-17T02:45:52.922541+05:30
%A Ananya Ghosh Chowdhury
%A Goutham Bandapati
%A Phanidhar Chilakapati
%T Revolutionizing Retail Operations through Generative AI: A Systematic Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 4
%P 5-11
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This systematic review compares the transformative impact of generative artificial intelligence (GAI) on retail business operations between 2020-2024. From a close analysis of 14 studies across six continents, the study identifies prevalent patterns of implementation, technology designs, and operation impacts of GAI adoption in retail settings. The work shows high potential for GAI in augmenting demand forecasting (with accuracy gains of up to 23%), optimizing inventory management (with a 17% reduction in carrying costs), and customer experience personalization (with conversion gains of 35%). The review identifies the prevalence of big language models, transformer models, and multimodal designs as the prevailing technological approaches, with varying success across retail types. Despite challenges of data quality, legacy system integration, and ethics, successful implementations by retailers show these challenges overcome with planning and organizational readiness. Analysis confirms GAI to be revolutionizing the business models in retail in revolutionary ways, with both operation efficiency and new strategic potential. A conceptual framework is presented that links GAI competencies to retail operational needs, implementation drivers, and value creation drives, with implications for researchers and practitioners in this technology-revolutionizing space.

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Index Terms

Computer Science
Information Sciences

Keywords

Generative AI Retail Operations Demand Forecasting Inventory Optimization Customer Experience Supply Chain Management Large Language Models Machine Learning and Retail Digital Transformation

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