International Journal of Science, Engineering and TechnologyAuthors: Deepa K. Iyer
Abstract: Artificial Intelligence (AI) has increasingly transformed enterprise IT service management (ITSM) by enabling more intelligent, efficient, and proactive service desk operations. Traditional IT service desks often struggle with high ticket volumes, repetitive tasks, and delayed resolution times, which can negatively impact end-user satisfaction and operational efficiency. AI-driven ticketing systems leverage machine learning, natural language processing (NLP), and predictive analytics to automate ticket classification, prioritization, routing, and resolution. By integrating AI into IT service desks, organizations can optimize workflow efficiency, improve response accuracy, and reduce operational costs. Recent studies highlight the effectiveness of AI in identifying recurring incidents, suggesting proactive solutions, and enabling data-driven decision-making. Furthermore, AI-enabled self-service tools and chatbots empower end-users to resolve common issues independently, minimizing human intervention while maintaining high service quality. Despite these advantages, challenges such as data quality, model training, integration complexity, and staff resistance remain significant barriers to adoption. This review synthesizes recent research and case studies to evaluate the operational, strategic, and economic impacts of AI-driven ticketing systems. The findings suggest that while AI adoption significantly enhances IT service desk performance, careful implementation, continuous monitoring, and iterative improvement are essential for realizing its full potential. The review concludes by outlining future directions, including the integration of predictive and prescriptive AI models, autonomous IT service desk frameworks, and advanced knowledge management systems, which collectively promise to revolutionize ITSM efficiency.
DOI: https://doi.org/10.5281/zenodo.17797900
