Paper Contents
Abstract
The incorporation of Artificial Intelligence (AI) into Information Technology Service Management (ITSM) represents a transformative strategy aimed at improving operational efficiency, enhancing scalability, and elevating the overall quality of service delivery. This study conducts a systematic review of AI-driven automation techniques applied in ITSM, focusing on tools such as IBM Watson AIOps, ServiceNows Virtual Agent, and BMC Helix. The study aims to identify the benefits, challenges, and future research directions associated with AI-driven ITSM. The methodology involves a comprehensive analysis of existing literature, case studies, and comparative assessments of AI-based ITSM tools. Key findings indicate that AI-driven solutions significantly improve incident prediction, service request automation, anomaly detection, and overall service reliability. However, challenges related to data quality, integration, ethical concerns, and scalability continue to hinder widespread adoption. The paper emphasizes the need for developing hybrid AI models, enhancing transparency through Explainable AI (XAI), and establishing standardized evaluation frameworks for AI-driven ITSM systems. The findings contribute to a deeper understanding of AI's transformative potential in ITSM and provide practical recommendations for organizations seeking to enhance their IT service delivery capabilities.
Copyright
Copyright © 2025 Arnika Kashinath Gunjal. This is an open access article distributed under the Creative Commons Attribution License.
