The future of an ITIL compliant technology - AI integration for enhancing incident management and problem management for company XYZ - global service operations a technology foresight through scenario building - Roxas, Maria Luisa Cruz; Imbang, Glen (Quezon City University of the Philippines Diliman, 2025)
In this modern digital age, IT services are crucial for business continuity and user satisfaction. As organizations increasingly depend on technology, the quantity and diversity of incident management and problem management has increased significantly. The ITIL (Information Technology Infrastructure Library) framework has long been utilized for effective IT Service Management (ITSM). It gives the best ways to oversee IT services. Company XYZ's global service operations are becoming more complicated and having the same problems in all regions.
This project intends to systematically include AI capabilities into the ITIL framework, highlighting incident management and problem management, while making use of technical foresight to foresee future trends and assure the continuing versatility of service operations. Artificial Intelligence (AI) and technology foresight are two vital developments that contribute to this progress. AI may identify, classify and fix incidents and problems on its own through machine learning. Technology foresight, on the other hand, can consistently anticipate trends, risks, and opportunities. This will be a crucial guide for ITSM strategy in the future. End users need help that is quick, efficient, and dependable. With these customer-focused goals, AI-powered virtual assistants, autonomous problem solving, and self-service apps could deliver a high-quality user experience while also making support jobs much simpler.
Integrating AI and technology foresight into the ITIL framework, specifically in both incident and problem management, enables organizations to transition from reactive measures to proactive strategies, providing improved, streamlined, and strategic IT support. Its absence could contribute to a critical gap that would affect continuous service improvement and long-term IT resilience. Recently conducted studies on AI-driven ITSM suggest that these solutions can automate repetitive tasks, improve service quality, and decrease mean time to resolution (MTTR) by analyzing past incidents, behavioral trends, and configuration data.
In partial fulfillment of the requirements of the Master of Technology Management Program
Thesis
Keywords: ITIL (Information technology management standard) .; Artificial intelligence -- Industrial applications; Machine learning -- Decision making