AI and Machine Learning in Enhancing Scalability and Efficiency of Integrated E-commerce and ERP Systems

This article explores the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing the integration of E-commerce platforms with Enterprise Resource Planning (ERP) systems. As E-commerce experiences explosive growth and ERP systems become increasingly complex, businesses face significant challenges in maintaining scalability and efficiency. We examine how AI and ML can optimize various aspects of these integrated systems, from intelligent automation and predictive analytics to anomaly detection and decision support. Through case studies and analysis of current trends, we demonstrate the tangible benefits of AI/ML implementation, including reduced costs, improved accuracy, and enhanced customer experiences. The article also addresses key challenges such as data quality, scalability, ethical considerations, and the skills gap. Finally, we explore future research directions in explainable AI, edge computing, blockchain integration, and natural language processing, highlighting their potential impacts on the E-commerce and ERP landscape.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2024-10-06
DOI
https://doi.org/10.32628/cseit24105108
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.06
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article

AI and Machine Learning in Enhancing Scalability and Efficiency of Integrated E-commerce and ERP Systems

Sai Charan Tokachichu, Kamalendar Reddy Kotha, Sudheer Chennuri
2 citations
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Big Data and Business Intelligence
1.06
article

AI and Machine Learning in Enhancing Scalability and Efficiency of Integrated E-commerce and ERP Systems

Sai Charan Tokachichu, Kamalendar Reddy Kotha, Sudheer Chennuri
article en
2 citations

Abstract

This article explores the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing the integration of E-commerce platforms with Enterprise Resource Planning (ERP) systems. As E-commerce experiences explosive growth and ERP systems become increasingly complex, businesses face significant challenges in maintaining scalability and efficiency. We examine how AI and ML can optimize various aspects of these integrated systems, from intelligent automation and predictive analytics to anomaly detection and decision support. Through case studies and analysis of current trends, we demonstrate the tangible benefits of AI/ML implementation, including reduced costs, improved accuracy, and enhanced customer experiences. The article also addresses key challenges such as data quality, scalability, ethical considerations, and the skills gap. Finally, we explore future research directions in explainable AI, edge computing, blockchain integration, and natural language processing, highlighting their potential impacts on the E-commerce and ERP landscape.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 10(5)
Dexcom (United States) (US), Texas A&M University – Corpus Christi (US)
Openalex Percentile: Top 17%
Big Data and Business Intelligence
1.06
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AI and Machine Learning in Enhancing Scalability and Efficiency of Integrated E-commerce and ERP Systems — Sai Charan Tokachichu, Kamalendar Reddy Kotha, et al. · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2024) | TGRS Research Map | TGRS