AI and Automation in SAP CRM Service: Chatbots, Intelligent Ticket Routing, and Predictive Service

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Published: 2026-02-12
DOI: https://doi.org/10.15662/IJRPETM.2026.0901010
Keywords:
SAP CRM, artificial intelligence, chatbots, intelligent routing, predictive service, automation

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Vinayak Kalabhavi
Denken Solution, USA

Abstract

The paper discusses the artificial intelligence (AI) and automation technologies of SAP Customer relationship management (CRM) service operations. This paper discusses intelligent chatbots, intelligent ticket routing, and predictive service analytics through a systematic secondary literature and review of existing published scholarly sources, industry reports, and case studies. It has already been proven that AI-based systems that are part of SAP CRM systems decrease the time of service response by as much as 60 percent, and increase the response rate of first contact by 20-30 percent. There are competitive advantages of AI strategies in organizations by providing better services to customers and making decisions based on data.


 


Theoretical contributions comprise an overall framework of integrating the AI technologies into the context of SAP CRM services and defining the essential success factors in the implementation. Practical contributions include practical lessons that can be used by practitioners who develop AI-driven automation of services, such as performance benchmarks and to strategies on implementation. The study combines the results to obtain theoretical knowledge and advice to integrate AI and SAP CRM service systems.

Article Details

Issue

Vol. 9 No. 1 (2026): International Journal of Research Publications in Engineering, Technology and Management

Section

Articles

How to Cite

AI and Automation in SAP CRM Service: Chatbots, Intelligent Ticket Routing, and Predictive Service. (2026). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 9(1), 86-93. https://doi.org/10.15662/IJRPETM.2026.0901010

References

1. Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology, and applications. Machine Learning with Applications, 2, 100006.

2. Aggarwal, C. C., & Zhai, C. (2012). Mining text data. Springer Science & Business Media.

3. Aksin, Z., Armony, M., & Mehrotra, V. (2007). The modern call center: A multi-disciplinary perspective. Production and Operations Management, 16(6), 665-688.

4. Araujo, T. (2018). Living up to the chatbot hype. Computers in Human Behavior, 85, 183-189.

5. Barocas, S., & Selbst, A. D. (2016). Big data's disparate impact. California Law Review, 104, 671-732.

6. Benbya, H., Pachidi, S., & Jarvenpaa, S. (2020). Artificial intelligence in organizations. Journal of the Association for Information Systems, 22(2), 281-303.

7. Brandtzaeg, P. B., & Følstad, A. (2017). Why people use chatbots. Internet Science, 10673, 377-392.

8. Buttle, F., & Maklan, S. (2019). Customer relationship management (4th ed.). Routledge.

9. Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics. MIS Quarterly, 36(4), 1165-1188.

10. Chui, M., Manyika, J., & Miremadi, M. (2018). What AI can and can't do for your business. McKinsey Quarterly, 1, 97-108.

11. Dale, R. (2016). The return of the chatbots. Natural Language Engineering, 22(5), 811-817.

12. Davenport, T. H., & Harris, J. G. (2007). Competing on analytics. Harvard Business Press.

13. Davenport, T. H., Harris, J., & Morison, R. (2010). Analytics at work. Harvard Business Press.

14. Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change marketing. Journal of the Academy of Marketing Science, 48(1), 24-42.

15. Domingos, P. (2012). A few useful things to know about machine learning. Communications of the ACM, 55(10), 78-87.

16. Følstad, A., & Brandtzaeg, P. B. (2017). Chatbots and the new world of HCI. Interactions, 24(4), 38-42.

17. Gans, N., Koole, G., & Mandelbaum, A. (2003). Telephone call centers: Tutorial and review. Manufacturing & Service Operations Management, 5(2), 79-141.

18. Gartner. (2021). Survey reveals 54% of organizations are piloting AI. Gartner Press Release.

19. Gnewuch, U., Morana, S., & Maedche, A. (2017). Towards designing cooperative conversational agents. ICIS Proceedings.

20. Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2020). The future of technology and marketing. Journal of the Academy of Marketing Science, 48(1), 1-8.

21. Guo, H., & Levy, M. (2018). Machine learning for call routing. Operations Research Letters, 46(3), 319-324.

22. Gupta, S., Hanssens, D., Hardie, B., et al. (2006). Modeling customer lifetime value. Journal of Service Research, 9(2), 139-155.

23. Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30-50.

24. Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for implementing INDUSTRIE 4.0. Final report.

25. Kumar, V., & Reinartz, W. (2018). Customer relationship management (3rd ed.). Springer.

26. Lee, J., Kao, H. A., & Yang, S. (2015). Service innovation and smart analytics for Industry 4.0. Procedia CIRP, 16, 3-8.

27. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience. Journal of Marketing, 80(6), 69-96.

28. Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Machines vs. humans. Marketing Science, 38(6), 937-947.

29. McKinsey & Company. (2021). The state of AI in 2021. McKinsey Global Survey.

30. Mohanty, R. P., Seth, D., & Mukadam, S. (2021). Quality dimensions of e-CRM. Total Quality Management, 32(11-12), 1337-1356.

31. Monk, E., & Wagner, B. (2013). Concepts in enterprise resource planning (4th ed.). Cengage Learning.

32. Neslin, S. A., Gupta, S., Kamakura, W., et al. (2006). Defection detection. Journal of Marketing Research, 43(2), 204-211.

33. O'Neil, C. (2016). Weapons of math destruction. Crown.

34. Pahl, C., & Jamshidi, P. (2016). Microservices: A systematic mapping study. Cloud Computing Conference, 137-146.

35. Payne, A., & Frow, P. (2005). A strategic framework for CRM. Journal of Marketing, 69(4), 167-176.

36. Pfeuffer, N., Benlian, A., Gimpel, H., & Hinz, O. (2019). Anthropomorphic information systems. Business & Information Systems Engineering, 61(4), 523-533.

37. Plattner, H., & Leukert, B. (2015). The in-memory revolution. Springer.

38. Provost, F., & Fawcett, T. (2013). Data science for business. O'Reilly Media.

39. Quarteroni, S., & Manandhar, S. (2009). Designing an interactive open-domain question answering system. Natural Language Engineering, 15(1), 73-95.

40. Russell, S., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.

41. SAP. (2021). Customer success story: Telecommunications provider. SAP Customer Case Study.

42. SAP. (2022). SAP Conversational AI documentation. SAP Help Portal.

43. Shmueli, G., & Koppius, O. R. (2011). Predictive analytics in information systems research. MIS Quarterly, 35(3), 553-572.

44. Teh, P. L., Ahmed, P. K., & D'Arcy, J. (2020). What drives intelligent routing adoption? International Journal of Information Management, 52, 102094.

45. Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence. Harvard Business Review, 96(4), 114-123.

46. Wirtz, J., Patterson, P. G., Kunz, W. H., et al. (2018). Brave new world: Service robots. Journal of Service Management, 29(5), 907-931.

47. Xu, Y., Shieh, C. H., van Esch, P., & Ling, I. L. (2017). AI customer service. Australasian Marketing Journal, 28(4), 187-199.