To explore current applications of Artificial Intelligence (AI) and Machine Learning (ML) in IT Service Management (ITSM).
To evaluate how AI/ML improves efficiency, accuracy, and user experience in ITSM processes such as incident management, change management, and service request handling.
To analyze the impact of AI-driven tools on decision-making, automation, and proactive problem resolution.
To identify limitations, implementation challenges, and skill gaps in AI/ML adoption within ITSM environments.
To propose a strategic roadmap for future integration of AI/ML in ITSM across maturity levels.
Conduct a literature review on AI/ML techniques relevant to ITSM (e.g., NLP for chatbots, anomaly detection, predictive analytics).
Study AI/ML-powered ITSM tools (e.g., ServiceNow’s Virtual Agent, BMC Helix, Freshservice Freddy AI) and their current capabilities.
Analyze real-world use cases in organizations where AI/ML has been implemented for service desk automation, incident prediction, and knowledge management.
Evaluate key performance metrics such as resolution time, ticket deflection rate, SLA compliance, and user satisfaction.
Identify challenges like data quality, model training, integration complexity, and human-AI collaboration issues.
(If feasible) Collect feedback through surveys or expert interviews on AI readiness and expectations within IT service teams.
Prepare a detailed report outlining present applications, effectiveness analysis, risk considerations, and a phased roadmap for AI/ML adoption in ITSM.
