A Survey of Emerging Technologies in Cloud Enterprise Resource Planning: The Oracle Fusion Cloud ERP Ecosystem
Keywords:
Agentic AI, Artificial Intelligence, Blockchain, Cybersecurity, Data science, Edge computing, Enterprise resource planningAbstract
Enterprise Resource Planning (ERP) systems have evolved from monolithic, on-premises transaction engines into cloud-native, intelligent platforms that fuse artificial intelligence, distributed ledgers, the Internet of Things (IoT), and elastic edge-to-cloud infrastructure. Oracle Fusion Cloud ERP has emerged as a leading exemplar of this transformation, embedding machine learning, generative and agentic artificial intelligence, and pervasive analytics directly within core financial and operational workflows. This article presents a structured survey of the emerging technologies reshaping the Oracle ERP ecosystem and situates them within the broader research landscape of intelligent enterprise systems. The survey traces the architectural evolution from Oracle E-Business Suite to Fusion Cloud ERP; examines the cloud and edge computing foundations provided by Oracle Cloud Infrastructure and the Oracle Autonomous Database; analyzes embedded, generative, and agentic AI capabilities, including the AI Agent Studio and a suite of finance-oriented agents; and reviews the integration of IoT and sensor networks, blockchain-based track-and-trace, data science and soft-computing techniques, and cybersecurity mechanisms. Recurring design patterns and open research challenges are synthesized across trust, explainability, data governance, latency-sensitive edge processing, and the security of autonomous enterprise agents. The result is a technology map intended to serve both practitioners planning cloud ERP modernization and researchers seeking an application-grounded view of one of the most consequential domains for AI, IoT, blockchain, and secure distributed computing.
References
A. Reyna, C. Martín, J. Chen, E. Soler, and M. Díaz, “On Blockchain and Its Integration with IoT. Challenges and Opportunities,” Future Generation Computer Systems, vol. 88, pp. 173–190, Nov. 2018.
M. A. Abd Elmonem, E. S. Nasr, and M. H. Geith, “Benefits and Challenges of Cloud ERP Systems – a Systematic Literature Review,” Future Computing and Informatics Journal, vol. 1, no. 1–2, pp. 1–9, Dec. 2016.
E. Hofmann and M. Rüsch, “Industry 4.0 And the Current Status as Well as Future Prospects on Logistics,” Computers in Industry, vol. 89, pp. 23–34, Aug. 2017.
S. Singh, Y.-S. Jeong, and J. H. Park, “A Survey on Cloud Computing Security: Issues, Threats, and Solutions,” Journal of Network and Computer Applications, vol. 75, pp. 200–222, Nov. 2016.
M. Al-Mashari, A. Al-Mudimigh, and M. Zairi, “Enterprise Resource Planning: A Taxonomy of Critical Factors,” European Journal of Operational Research, vol. 146, no. 2, pp. 352–364, Apr. 2003.
K. Sallam, M. Mohamed, and A. W. Mohamed, “Internet of Things (IoT) in Supply Chain Management: Challenges, Opportunities, and Best Practices,” Sustainable Machine Intelligence Journal, vol. 2, no. 2, Mar. 2023.
S. Katuu, “Enterprise Resource Planning: Past, Present, and Future,” New Review of Information Networking, vol. 25, no. 1, pp. 37–46, 2020.
A. Elragal and M. Haddara, “The Future of ERP Systems: Look Backward Before Moving Forward,” Procedia Technology, vol. 5, pp. 21–30, 2012.
A. K. Kalusivalingam, A. Sharma, and N. Patel, “Optimizing E-Commerce Revenue: Leveraging Reinforcement Learning and Neural Networks for AI-Powered Dynamic Pricing,” International Journal of AI and ML. 2022.
L. Da Xu, W. He, and S. Li, “Internet of Things in Industries: A Survey,” IEEE Transactions on Industrial Informatics, vol. 10, no. 4, pp. 2233–2243, Nov. 2014.
L. Atzori, A. Iera, and G. Morabito, “The Internet of Things: A Survey,” Computer Networks, vol. 54, no. 15, pp. 2787–2805, Oct. 2010.
Z. Zheng, S. Xie, H. N. Dai, X. Chen, and H. Wang, “Blockchain Challenges and Opportunities: A Survey,” International Journal of Web and Grid Services, vol. 14, no. 4, pp. 352–375, Oct. 2018.
M. Satyanarayanan, “The Emergence of Edge Computing,” Computer, vol. 50, no. 1, pp. 30–39, Jan. 2017.
M. Attaran, “Digital Technology Enablers and Their Implications for Supply Chain Management,” Supply Chain Forum: An International Journal, vol. 21, no. 3, pp. 158–172, Apr. 2020.
W. Shi, J. Cao, Q. Zhang, Y. Li, and L. Xu, “Edge Computing: Vision and Challenges,” IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637–646, Oct. 2016.
I. H. Sarker, “Machine Learning: Algorithms, Real-World Applications and Research Directions,” SN Computer Science, vol. 2, no. 3, pp. 1–21, Mar. 2021.
Y. Duan, J. S. Edwards, and Y. K. Dwivedi, “Artificial Intelligence for Decision Making in the Era of Big Data – Evolution, Challenges and Research Agenda,” International Journal of Information Management, vol. 48, no. 1, pp. 63–71, Oct. 2019.
Y. K. Dwivedi, “So What If ChatGPT Wrote It?’ Multidisciplinary Perspectives on Opportunities, Challenges and Implications of Generative Conversational AI for Research, Practice and Policy, International Journal of Information Management, vol. 71, no. 0268–4012, p. 102642, Aug. 2023.