Optimizing IT Service Delivery with AI: Enhancing Efficiency Through Predictive Analytics and Intelligent Automation - Saif Ahmad; MD Nadil khan; Kirtibhai Desai; Mohammad Majharul Islam; MD Mahbub Rabbani; Esrat Zahan Snigdha (The American Journal of Engineering and Technology, 2025)
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.