Leveraging AI-Driven Predictive Analytics in Modern ERP Systems

Authors

  • Ravi Sankar Korapati University of Madras, Chennai, India Author

DOI:

https://doi.org/10.32628/CSEIT251112193

Keywords:

Artificial Intelligence, Enterprise Resource Planning, Machine Learning, Predictive Analytics, Real-time Integration

Abstract

This comprehensive article explores the transformative impact of AI-driven predictive analytics in modern Enterprise Resource Planning (ERP) systems. The article examines how the integration of artificial intelligence and machine learning capabilities has revolutionized organizational decision-making processes, operational efficiency, and strategic planning. The article investigates key application areas including financial forecasting, inventory optimization, and customer behavior analysis, while also addressing technical implementation considerations and system architecture requirements. The article demonstrates how AI-enhanced ERP systems have enabled organizations to achieve significant improvements in operational performance, risk management, and market competitiveness through advanced data processing and predictive modeling capabilities.

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References

Hari Krishna Reddy Rikkula, "The Future of ERP Integrations: A Look at Emerging Technologies," International Research Journal of Engineering and Technology (IRJET), Volume: 11 Issue: 07, July 2024. Available: https://www.researchgate.net/profile/Harikrishna-Rikkula/publication/382444998_The_Future_of_ERP_Integrations_A_Look_at_Emerging_Technologies/links/669dc4c7cb7fbf12a465578e/The-Future-of-ERP-Integrations-A-Look-at-Emerging-Technologies.pdf

Hemanth Kumar Gollangi, et al., "The Impact of AI and ML on ERP Systems and Supply Chain Management," Nanotechnology Perceptions 20(S9), 2024. Available: https://www.researchgate.net/publication/384081137_The_Impact_of_AI_and_ML_on_ERP_Systems_and_Supply_Chain_Management

Mohammad Amini, et al., "Erp Systems Architecture For The Modern Age: A Review Of The State Of The Art Technologies," Journal Of Applied Intelligent Systems & Information Sciences Vol. 1, Issue 2, Pp. 70-90, August 2020. Available: https://www.researchgate.net/publication/343450571_ERP_SYSTEMS_ARCHITECTURE_FOR_THE_MODERN_AGE_A_REVIEW_OF_THE_STATE_OF_THE_ART_TECHNOLOGIES

Karen J.Colley, et al., "The Integration of Machine Learning in Enterprise Systems," Journal of Information Technology Management, vol. 35, no. 1, pp. 112-129, 2024. Available: https://www.researchgate.net/publication/383212461_The_Integration_of_Machine_Learning_in_Enterprise_Systems

G. Mothilal Nehru, et al., "Risk Modelling and Prediction of Financial Management Using FTL-CSGRU Approach," IEEE International Conference on Electronics, Computing, Communication and Control Technology (ICECCC), 2024. Available: https://ieeexplore.ieee.org/document/10593965

Somanchi Hari Krishna, et al., "Competitive Edge Using Big Data Analytics to Improve Customer Relationship Management," IEEE International Conference on Communication, Computer Sciences and Engineering (IC3SE), 2024. Available: https://ieeexplore.ieee.org/document/10593152

Noussair Fikri, et al., "An adaptive and real-time based architecture for financial data integration," Journal of Big Data, vol. 6, no. 1, pp. 1-23, 2019. Available: https://link.springer.com/article/10.1186/s40537-019-0260-x

Luis Barberá, et al., "Advanced model for maintenance management in a continuous improvement cycle: Integration into the business strategy," International Journal of Systems Assurance Engineering and Management 3(1):47-63, 2012. Available: https://www.researchgate.net/publication/257798557_Advanced_model_for_maintenance_management_in_a_continuous_improvement_cycle_Integration_into_the_business_strategy

Sanjay Vijay Mhaskey, "Integration of Artificial Intelligence (AI) in Enterprise Resource Planning (ERP) Systems: Opportunities, Challenges, and Implications," International Journal of Computer Engineering in Research Trends 11(12), 2024. Available: https://www.researchgate.net/publication/387667312_Integration_of_Artificial_Intelligence_AI_in_Enterprise_Resource_Planning_ERP_Systems_Opportunities_Challenges_and_Implications

Indu John, et al., "Predictive and Prescriptive Analytics for Performance Optimization: Framework and a Case Study on a Large-Scale Enterprise System," 18th IEEE International Conference On Machine Learning And Applications (ICMLA), 2019. Available: https://ieeexplore.ieee.org/document/8999314

Amejuma Emmanuel Ebule, "Leveraging Artificial Intelligence in Business Intelligence Systems for Predictive Analytics," International Journal of Scientific Research and Management (IJSRM) , 2025. Available: https://i-jsrm.net/index.php/ijsrm/article/view/v13i01.ec02/43

Olubunmi Adeolu Adenekan, et al., "Enhancing manufacturing productivity: A review of AI-Driven supply chain management optimization and ERP systems integration," International Journal of Management & Entrepreneurship Research, Volume 6, Issue 5, May 2024. Available: https://www.fepbl.com/index.php/ijmer/article/view/1126

Khadijat Oyindamola Alabi, “Predictive Analytics in HR: Leveraging AI for Data-Driven Decision Making,” International Journal of Research in Engineering, Science and Management Volume 7, Issue 4, April 2024. Available: https://www.researchgate.net/publication/380297920_Predictive_Analytics_in_HR_Leveraging_AI_for_Data-Driven_Decision_Making

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Published

03-02-2025

Issue

Section

Research Articles

How to Cite

Leveraging AI-Driven Predictive Analytics in Modern ERP Systems. (2025). International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 11(1), 1639-1651. https://doi.org/10.32628/CSEIT251112193