A Unified Framework for ITSM, HRSD, and CSM
Keywords:
Generative AI, Large Language Models, ChatGPT, IT Service Management, HR Service Delivery, Customer Service Management, Enterprise Automation, Responsibility, Ethical AI, Data Responsibility, ITIL, Information Technology, Chatbot, LLM, Human Resource Service Delivery, Customer Service Management, Automation, Workflows, Work Management, Information Technology Infrastructure Library, Help Desk, Intelligent Virtual Assistant, Client Response, Enterprise Service Management, Chatbot Development, Digital Employee Experience.Abstract
Generative AI is increasingly used to orchestrate or augment enterprise operations across internal IT service management (ITSM), human resources service delivery (HRSD), and customer service management (CSM). A growing body of literature discusses the foundations of responsible generative AI; however, no comprehensive framework supports scalable deployments across multiple domains or connects generative AI to enterprise automation. A formalized approach to architecting responsible generative AI agents capable of automating ITSM, HRSD, and CSM workflows has yet to emerge. A unified framework integrating these three domains will support enterprise automation in a responsible manner.
Traditionally, ITSM, HRSD, and CSM automation applications are siloed, with reliance on uniform templates and a narrow focus on simple question–answer pairs. Responsible generative AI systems offer the ability to promote efficiency and effectiveness across a wider spectrum of operational tasks. The reference architecture, supporting guidelines, and domain-specific considerations outlined here serve as a blueprint for building or integrating responsible generative AI capabilities. With expansion beyond single-use agents into holistic, managed enterprise deployments featuring prebuilt connectivity, the full potential of generative AI can be realized.
References
1. Guerola-Navarro, V., Gil-Gomez, H., Oltra-Badenes, R., & Sendra-García, J. (2021). Customer relationship management and its impact on innovation: A literature review. Journal of Business Research, 129, 83–87.
2. Pereira, R., de Vasconcelos, J. B., Rocha, Á., & Bianchi, I. S. (2021). Business process management heuristics in IT service management: A case study for incident management. Computational and Mathematical Organization Theory, 27(3), 264–301.
3. Mattaparthi, R. (2021). Unified Data Lineage and Quality Governance Framework for Multi-Source Sensor Streams in Heavy-Duty Powertrain Manufacturing. Online Journal of Mechanical Engineering, 1(1), 1-15.
4. Serrano, J., Faustino, J., Adriano, D., Pereira, R., & Mira da Silva, M. (2021). An IT service management literature review: Challenges, benefits, opportunities and implementation practices. Information, 12(3), 111.
5. Trubetskaya, A., & Mullers, H. (2021). Transforming a global human resource service delivery operating model using Lean Six Sigma. Systems Research and Behavioral Science, 38(6), 712–728.
6. Yadav, M., & Vihari, N. S. (2021). Employee experience: Construct clarification, conceptualization and validation of a new scale. FIIB Business Review, 12(3), 328–342.
7. Widianto, A., & Subriadi, A. P. (2022). IT service management evaluation method based on content, context, and process approach: A literature review. Procedia Computer Science, 197, 410–419.
8. Žilinskienė, I., & Norkus, J. (2022). Improving IT service management in customer service business: A case study. Information & Media, 94, 53–70.
9. Loganathan, R. (2021). Integrated Risk and Compliance Frameworks for Global Data Center Operations: A Governance-Centric Approach. Universal Journal of Computer Sciences and Communications, 1(1), 1-26.
10. Malik, A., Budhwar, P., Mohan, H., & Srikanth, N. R. (2022). Employee experience—the missing link for engaging employees: Insights from an MNE's AI-based HR ecosystem. Human Resource Management, 62(1), 97–115.
11. Strohmeier, S. (2021). Digital human resource management: A conceptual clarification. German Journal of Human Resource Management, 35(3), 345–365.
12. Trullen, J., Bos-Nehles, A., & Valverde, M. (2021). From intended to actual and from actual to perceived HR practices: The missing links in HRM research. Human Resource Management Review, 31(3), 100771.
13. Jooss, S., Collings, D. G., & McMackin, J. (2021). The career implications of digital transformation and artificial intelligence for HR professionals. Human Resource Management Review, 31(3), 100794.
14. Pithadia, V., & Vashisth, A. (2022). Digitalization in human resource management. IITM Journal of Management and IT, 13(1), 56–63.
15. Peddi, R. K. (2021). Optimizing Case Management Workflows in Global Data Center Colocation Services. Universal Journal of Computer Sciences and Communications, 1(1), 1-21.
16. Anusiya, S. (2022). Digital human resource management. International Conference Faculty of Economics and Business, 1(1), 284–289.
17. Ni, J. (2022). Deep neural network model construction for digital human resource management with human-job matching. Computational Intelligence and Neuroscience, 2022, Article 1418020.
18. Margherita, A., Braccini, A. M., & Braccini, A. M. (2021). Digital transformation and human resource management: A systematic literature review. Management Decision, 59(9), 2270–2292.
19. Gahler, M., Klein, J. F., & Paul, M. (2022). Customer experience: Conceptualization, measurement, and application in omnichannel environments. Journal of Service Research, 26(2), 191–211.
20. Dalla Pozza, I. (2022). The role of proximity in omnichannel customer experience: A service logic perspective. Journal of Service Management, 33(5), 774–786.
21. De Keyser, A., Alkire, L., Verbeeck, K., & Christiaens, T. (2022). Living and working with service robots: A TCCM analysis and considerations for future research. Journal of Service Management, 33(2), 165–187.
22. Lim, W. M., Rasul, T., Kumar, S., & Ala, M. (2022). Past, present, and future of customer engagement. Journal of Business Research, 140, 439–458.
23. Stead, S., Odekerken-Schröder, G., & Mahr, D. (2021). Unraveling customer experiences in a new servicescape: An ethnographic schema elicitation technique (ESET). Journal of Service Management, 32(4), 612–641.
24. Jaakkola, E., & Terho, H. (2021). Service journey quality: Conceptualization, measurement and customer outcomes. Journal of Service Management, 32(6), 1–27.
25. Reddy, V. A. R. (2021). Challenges in Standardizing Member Eligibility Data Across Multi-Payer Healthcare Ecosystems. International Journal of Medical Toxicology and Legal Medicine, 24(3), 1-19.
26. Gupta, R., & Raman, S. (2022). After-sale service experiences and customer satisfaction: An empirical study from the Indian automobile industry. Research in Transportation Business & Management, 45, 100873.
27. Guerola-Navarro, V., Oltra-Badenes, R., Gil-Gomez, H., & Fernández-Avilés, G. (2021). Customer relationship management and its impact on organizational performance: A systematic review. Journal of Business Research, 129, 83–87.
28. Suoniemi, S., Terho, H., Zablah, A., Olkkonen, R., & Straub, D. W. (2021). The impact of firm-level and project-level IT capabilities on CRM system quality and organizational productivity. Journal of Business Research, 127, 108–122.
29. Pappas, I. O., Giannakos, M. N., & Sampson, D. G. (2021). Fuzzy-set qualitative comparative analysis of customer experience and digital service adoption. Information Systems Frontiers, 23, 1205–1221.
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Copyright (c) 2023 James Robertson (Author)
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