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

Author

Listed:
  • Kamalendar Reddy Kotha
  • Sai Charan Tokachichu
  • Sudheer Chennuri

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.

Suggested Citation

  • Kamalendar Reddy Kotha & Sai Charan Tokachichu & Sudheer Chennuri, 2024. "AI and Machine Learning in Enhancing Scalability and Efficiency of Integrated E-commerce and ERP Systems," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(5), pages 254-264, October.
    • Handle: RePEc:jbh:ijsrcs:v10:y2024:i5:id:311
    DOI: 10.32628/CSEIT24105108
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24105108
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