Modernizing Enterprise Service Desk and EUC Operations with AI-Powered Automation
DOI:
https://doi.org/10.15680/99n7a970Keywords:
AI-Powered IT Support, Enterprise Service Desk, End-User Computing (EUC), IT Service Management (ITSM), AIOps, Robotic Process Automation (RPA), Virtual Agents, Digital Employee Experience (DEX), Predictive IT Operations, Self-Healing Systems, Automation in IT Support, Intelligent Knowledge ManagementAbstract
Enterprise Service Desks and End-User Computing (EUC) operations play a critical role in ensuring business continuity, employee productivity, and digital experience. However, traditional IT support models are increasingly challenged by growing ticket volumes, hybrid work environments, complex device ecosystems, and rising user expectations for instant, always-available support. These challenges are driving organizations to modernize service desk and EUC operations through Artificial Intelligence (AI), automation, and data-driven service management practices.
This paper presents a comprehensive overview of how AI-powered automation is transforming enterprise service desks and EUC environments. It explores the evolution from reactive, ticket-driven support models to predictive, self-healing, and experience-centric IT operations. The article discusses key enabling technologies including conversational AI, virtual agents, AIOps, robotic process automation (RPA), intelligent knowledge management, and analytics-driven service optimization
The study also highlights architectural considerations, implementation strategies, governance models, and measurable business outcomes such as reduced mean time to resolution (MTTR), increased first-contact resolution (FCR), cost optimization, and improved employee digital experience (DEX). Challenges such as data quality, change management, ethical AI usage, and integration with legacy IT service management (ITSM) tools are examined alongside best practices for successful adoption
By providing a generalized, vendor-neutral perspective, this article aims to guide enterprises seeking to build a resilient, scalable, and AI-enabled support ecosystem capable of meeting the demands of modern digital workplaces
References
[1] M. Nayak and S. Rao, "Artificial Intelligence in IT Service Management: Opportunities and Challenges," IEEE Access, vol. 10, pp. 42111–42125, 2022.
[2] P. Leitner et al., "AIOps: Real-World Challenges and Research Directions," IEEE Software, vol. 39, no. 1, pp. 37– 44, 2022.
[3] Gartner, "Innovation Insight for AIOps Platforms," Gartner Research, 2022.
[4] Forrester, "The Total Economic Impact of AI-Powered IT Service Management," Forrester Research, 2022.
[5] S. Agarwal and T. Sharma, "Automation in IT Operations: A Machine Learning Approach," Journal of Cloud Computing, vol. 10, no. 1, 2021.
[6] A. Maroukian, "The Rise of Digital Employee Experience (DEX)," IEEE IT Professional, vol. 23, no. 5, pp. 72–78, 2021.
[7] R. Villamizar et al., "Improving IT Support Through Intelligent Automation," Future Generation Computer Systems, vol. 115, pp. 486–497, 2021.
[8] B. Furht and F. Villanustre, Big Data Technologies and Applications, Springer, 2021.
[9] J. Humble and D. Farley, Continuous Delivery and DevOps Automation, Addison-Wesley, 2020.
