Articles
| Open Access |
DOI: Optimizing IT Service Delivery with AI: Enhancing Efficiency Through Predictive Analytics and Intelligent Automation
Saif Ahmad , Department of Business Analytics, Wilmington University, USA MD Nadil khan , Department of Information Technology, Washington University of Science and Technology (wust), Vienna, VA 22182, USA Kirtibhai Desai , Department of Computer Science, Campbellsville University, KY 42718, USA Mohammad Majharul Islam , Department of Business Studies, Lincoln University, California, USA MD Mahbub Rabbani , Department of Information Technology, Washington University of Science and Technology (wust), Vienna, VA 22182, USA Esrat Zahan Snigdha , Department of Information Technology in Data Analysis, Washington University of Science and Technology (wust), Vienna, VA 22182, USAAbstract
At this time, the use of artificial intelligence (AI) for IT service delivery becomes a key modernization strategy that aims to move to a more efficient operation, decrease the cost of providing services, and increase its quality. The focus of this paper examines the AI driven predictive analytics and intelligent automation's ability to bring transformation into the IT service processes for the purpose of optimization. This research achieves this by conducting an extensive review on literature available about AI in the IT service industry and performing data driven analysis indicating key domains where AI can correctly anticipate and preempt IT service disruptions, allocate resources in an optimal manner and carry out routine tasks, helping increase overall efficiency substantially. To support the methodology, service metrics (incident response time, system downtime, etc.) are considered using their quantitative forms and analyzed using statistical tools to measure the impact of AI on these metrics. The findings show major improvements like predictive maintenance, automated issue resolution, and service personalization can be achieved with right implementations of AI technologies. This paper makes an addition to the body of literature, by conducting an in-depth investigation on the role of AI in changing IT service delivery, and presents practical insights to industry practitioners and regulators. The study proves that the adoption of modern AI technologies help the modern IT infrastructure remain competitive and develop as a drive to operational excellence.
Keywords
Predictive Analytics, Intelligent Automation, IT Service Delivery
References
Cheng, X., et al. (2023). AI for IT Operations in Cloud Platforms: Reviews, Opportunities and Challenges. arXiv preprint arXiv:2304.04661.
Ali, R. (2021). Cognitive Approaches to IT Service Desk Optimization. IEEE Transactions on Services Computing.
Levin, D., et al. (2020). AIOps Implementation in Cloud Storage Systems. SpringerLink.
Chakraborti, T., et al. (2020). From RPA to IPA: Advancing Automation. ResearchGate.
Wirtz, J., et al. (2018). Intelligent Automation in Service Management. Journal of Service Research.
Ganesan, S., et al. (2020). AI-Driven Sales Forecasting for IT Services. ScienceDirect.
Gadhiraju, R., et al. (2019). AI Optimization in Clinical Workflows. PubMed.
Avancha, S. (2021). Continuous Improvement in IT Service Delivery with AI. IEEE Xplore.
Uygun, S. (2020). Workforce Management Systems in Industry 4.0. Wiley Online Library.
Gundewar, S., et al. (2022). Predictive Analytics in Business Intelligence. JSTOR.
Wei, C., et al. (2023). Explainable AI in Crash Prediction. arXiv preprint arXiv:2302.11859.
Fosso, D. (2022). Strategic Benefits of AI Transformation Projects. SSRN.
Cheng, X., et al. (2023). AI for IT Operations in Cloud Platforms. arXiv.
Ali, R. (2021). Advanced Text Analytics in IT Service Management. IEEE Transactions.
Levin, D., et al. (2020). Analytics in Cloud IT Ecosystems. Springer.
Chakraborti, T., et al. (2020). Research Challenges in AI Automation. ResearchGate.
Jones, A., et al. (2023). Predictive Maintenance in IT Operations: A Data-Driven Approach. IEEE Transactions on Industrial Informatics.
Smith, R., et al. (2022). Enhancing Incident Management with AI-Powered Analytics. Journal of Information Technology Services.
Lee, K., et al. (2021). Dynamic Resource Allocation Using Predictive Models in Cloud Computing. SpringerLink.
Brown, T., et al. (2020). Customer-Centric IT Service Delivery: Leveraging Predictive Analytics. ScienceDirect.
Cheng, Q., et al. (2023). AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges. arXiv preprint arXiv:2304.04661.
Rajput, A. S., & Gupta, R. (2023). Hyperautomation in IT Industries. arXiv preprint arXiv:2305.11896.
Ali, A. R. (2021). Cognitive Computing to Optimize IT Services. arXiv preprint arXiv:2201.02737.
Wirtz, J., et al. (2023). How Intelligent Automation and AI Will Reshape Future Services. Journal of Service Management, 34(1), 1–32.
Levin, A., Garion, S., Kolodner, E. K., Lorenz, D. H., Barabash, K., Kugler, M., & McShane, N. (2020). AIOps for a Cloud Object Storage Service. arXiv preprint arXiv:2005.03094.
Shanmugalingam, K., Chandrasekara, N., Hindle, C., Fernando, G., & Gunawardhana, C. (2019). Corporate IT-Support Help-Desk Process Hybrid-Automation Solution with Machine Learning Approach. arXiv preprint arXiv:1909.09018.
van der Aalst, W. M. P., Bichler, M., & Heinzl, A. (2018). Robotic Process Automation. Business & Information Systems Engineering, 60(4), 269–272.
Syed, R., Suriadi, S., Adams, M., Bandara, W., & Leemans, S. J. J. (2020). Robotic Process Automation: Contemporary Themes and Challenges. Computers in Industry, 115, 103162.
Aguirre, S., & Rodriguez, A. (2017). Automation in Business Processes through RPA. In Applied Computer Sciences in Engineering (pp. 65–71). Springer.
Agostinelli, S., Marrella, A., & Mecella, M. (2020). Towards Intelligent Robotic Process Automation for BPMers. In Business Process Management: Blockchain and Robotic Process Automation Forum (pp. 57–72). Springer.
Willcocks, L., Lacity, M., & Craig, A. (2017). Robotic Process Automation: Strategic Transformation Lever for Global Business Services? Journal of Information Technology Teaching Cases, 7(1), 17–28.
Leshob, A., Bourgouin, A., & Renard, L. (2018). Robotic Process Automation: A Technical Primer. In 2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) (pp. 140–145). IEEE.
Santos, F., Pereira, R., & Vasconcelos, J. B. (2019). Toward Robotic Process Automation Implementation: An End-to-End Perspective. Business Process Management Journal, 26(2), 405–420.
Chakraborti, T., Isahagian, V., Khalaf, R., Khazaeni, Y., & Muthusamy, V. (2020). From Robotic Process Automation to Intelligent Process Automation. In Business Process Management Workshops (pp. 215–228). Springer.
Enriquez, J. G., Jimenez-Ramirez, A., Dominguez-Mayo, F. J., & Garcia-Garcia, J. A. (2020). Robotic Process Automation: A Scientific and Industrial Systematic Mapping Study. IEEE Access, 8, 39113–39129.
Agostinelli, S., Marrella, A., & Mecella, M. (2019). Business Process Management Workshops. In Lecture Notes in Business Information Processing (Vol. 342, pp. 3–15). Springer.
Ratia, M., Myllärniemi, J., & Helander, N. (2018). Robotic Process Automation – Creating Value by Digitalizing Work in the Private Healthcare? In Proceedings of the 22nd International Academic Mindtrek Conference (pp. 222–227). ACM.
Vincent, N. E., Igou, A., & Burns, M. B. (2020). Preparing for the Robots: A Proposed Course in Robotic Process Automation. Journal of Emerging Technologies in Accounting, 17(1), 101–109.
Montero, J. C., Jimenez-Ramirez, A., & Enriquez, J. G. (2019). Robotic Process Automation: A Scientific and Industrial Systematic Mapping Study. In 2019 IEEE/ACM 14th International Workshop on Automation of Software Test (AST) (pp. 120–126). IEEE.
Kobayashi, T., Arai, K., Imai, T., Tanimoto, S., & Sato, H. (2019). A Study on the Introduction of Robotic Process Automation (RPA) to Test Management. In 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) (pp. 100–105). IEEE.
Herm, L. V., Janiesch, C., Helm, A., Imgrund, F., & Fuchs, K. (2020). Towards a Framework for the Systematic Evaluation of Robotic Process Automation Projects. In Business Process Management (pp. 446–462). Springer.
Wirtz, J., Patterson, P., Kunz, W., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave New World: Service Robots in the Frontline. Journal of Service Management, 29(5), 907–931.
Huang, M. H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172.
Gursoy, D., Chi, C. G., Lu, L., & Nunkoo, R. (2019). Consumers Acceptance of Artificially Intelligent (AI) Device Use in Service Delivery. International Journal of Information Management, 49, 157–169.
Article Statistics
Copyright License
Copyright (c) 2025 Saif Ahmad, MD Nadil khan, Kirtibhai Desai, Mohammad Majharul Islam, MD Mahbub Rabbani, Esrat Zahan Snigdha
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.