USER SUPPORT SOLUTION IMPLEMENTATION FOR SAP ERP UTILIZING ARTIFICIAL INTELLIGENCE TO DRIVE AUTOMATED

Authors

  • Vedaprada Raghunath IT Director, IMR soft LLC, USA. Author

Keywords:

SAP, ERP, Service Manager, Information Technology (IT)

Abstract

Hundreds of millions of help desk requests are received each year by major corporations with complex IT systems, such as SAP ERP. You can submit these requests using Service Desk or Service Manager (SM) online or by calling in. A type of software for managing corporate processes, "enterprise resource planning" integrates several programs to automate HR, IT, and service operations. An intelligent method to assist SAP ERP users is suggested in this research study. Automated replies to customer support inquiries are now a reality, which not only improves responsiveness to end users but also speeds up the investigation and resolution of problems. In order to efficiently interpret questions, the system employs machine learning techniques to categorize text into multiple classes. In order to provide the optimal reaction, the system employs a customized framework to retrieve evidence. The framework's conversational AI features make it possible to build chatbots that facilitate simultaneous group collaboration.

References

Kersten, W., Blecker, T. and Ringle, C.M. (2019), “Artificial intelligence and digital transformation in supply chain management: Innovative approaches for supply chains”, Proceedings of Hamburg International Conference of Logistics. Hamburg.

Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A. and Galanos, V. (2019), “Artificial intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy”. International Journal of Information Management, doi: 10.1016/j.ijinfomgt.2019.08.002. In-press

Kiwibot (2020), available at: www.kiwibot.com/about-us (accessed 18 November 2020)

Vocke, C., Constantinescu, C. and Popescu, D. (2019), “Application potentials of artificial intelligence for the design of innovation processes”, Procedia CIRP, Vol. 84, pp. 810-813.

Lee, J., Davari, H., Singh, J. and Pandhare, V. (2018), “Industrial artificial intelligence for industry 4.0- based manufacturing systems”, Manufacturing Letters, Vol. 18, pp. 20-23.

Sundarakani, B., Rukshanda, K. and Jain, V.P. (2020), “Designing a hybrid cloud for a supply chain network of industry 4.0: a theoretical framework”, Benchmarking: An International Journal

Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P. and Fischl, M. (2021), “Artificial intelligence in supply chain management: a systematic literature review”, Journal of Business Research, Vol. 122, pp. 502-517

Feizabadi, J. (2020), “Machine learning demand forecasting and supply chain performance”, International Journal of Logistics Research and Applications, pp. 1-24, doi: 10.1080/ 13675567.2020.1803246.

Ramya Manikyam, J. Todd McDonald, William R. Mahoney, Todd R. Andel, and Samuel H. Russ. 2016.Comparing the effectiveness of commercial obfuscators against MATE attacks. In Proceedings of the 6th Workshop on Software Security, Protection, and Reverse Engineering (SSPREW’16)

R. Manikyam. 2019.Program protection using software based hardware abstraction.Ph.D. Dissertation.University of South Alabama.

GPB GRADXS, N RAO, Behaviour Based Credit Card Fraud Detection Design And Analysis By Using Deep Stacked Autoencoder Based Harris Grey Wolf (Hgw) Method, Scandinavian Journal of Information Systems 35 (1), 1-8.

R Pulimamidi, GP Buddha, Applications of Artificial Intelligence Based Technologies in The Healthcare Industry, Tuijin Jishu/Journal of Propulsion Technology 44 (3), 4513-4519.

R Pulimamidi, GP Buddha, AI-Enabled Health Systems: Transforming Personalized Medicine And Wellness, Tuijin Jishu/Journal of Propulsion Technology 44 (3), 4520-4526.

GP Buddha, SP Kumar, CMR Reddy, Electronic system for authorization and use of cross-linked resource instruments, US Patent App. 17/203,879.

Nadella, G. S. (2023). Validating the Overall Impact of IS on Educators in U.S. High Schools Using IS-Impact Model – A Quantitative PLS-SEM Approach, DAI-A 85/7(E), Dissertation Abstracts International, Ann Arbor, ISBN 9798381388480, 189, 2023.

Gonaygunta, Hari, Factors Influencing the Adoption of Machine Learning Algorithms to Detect Cyber Threats in the Banking Industry, DAI-A 85/7(E), Dissertation Abstracts International, Ann Arbor, United States, ISBN 9798381387865, 142, 2023.

Hari Gonaygunta (2023) Machine Learning Algorithms for Detection of Cyber Threats using Logistic Regression, 10.47893/ijssan.2023.1229.

Hari Gonaygunta, Pawankumar Sharma, (2021) Role of AI in product management automation and effectiveness, https://doi.org/10.2139/ssrn.4637857.

Sri Charan Yarlagadda, Role of Artificial Intelligence, Automation, and Machine Learning in Sustainable Plastics Packaging markets: Progress, Trends, and Directions, International Journal on Recent and Innovation Trends in Computing and Communication, Vol:11, Issue 9s, Pages: 818–828, 2023.

Sri Charan Yarlagadda, The Use of Artificial Intelligence and Machine Learning in Creating a Roadmap Towards a Circular Economy for Plastics, International Journal on Recent and Innovation Trends in Computing and Communication, Vol:11, Issue 9s, Pages: 829-836, 2023.

B. Nagaraj, A. Kalaivani, S. B. R, S. Akila, H. K. Sachdev, and S. K. N, “The Emerging Role of Artificial intelligence in STEM Higher Education: A Critical review,” International Research Journal of Multidisciplinary Technovation, pp. 1–19, Aug. 2023, doi: 10.54392/irjmt2351.

D. Sivabalaselvamani, K. Nanthini, Bharath Kumar Nagaraj, K. H. Gokul Kannan, K. Hariharan, M. Mallingeshwaran, Healthcare Monitoring and Analysis Using ThingSpeak IoT Platform: Capturing and Analyzing Sensor Data for Enhanced Patient Care, IGI Global eEditorial Discovery, Pages: 25, 2024. DOI: 10.4018/979-8-3693-1694-8.ch008.

Amol Kulkarni, Amazon Athena Serverless Architecture and Troubleshooting, International Journal of Computer Trends and Technology, Vol, 71, issue, 5, pages 57-61, 2023.

Amazon Redshift Performance Tuning and Optimization,International Journal of Computer Trends and Technology, vol, 71, issue, 2, pages, 40-44, 2023.

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Published

2024-05-23

How to Cite

Vedaprada Raghunath. (2024). USER SUPPORT SOLUTION IMPLEMENTATION FOR SAP ERP UTILIZING ARTIFICIAL INTELLIGENCE TO DRIVE AUTOMATED. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT (IJAIRD), 2(1), 123-134. https://iaeme-library.com/index.php/IJAIRD/article/view/IJAIRD_02_01_012