Artificial intelligence agents in ITSM incident management: a systematic review of their impact and performance
Keywords:
ITSM, incident management, artificial intelligence, intelligent agents, AIOpsAbstract
Incident management in Information Technology Service Management (ITSM) faces increasing challenges due to the growing volume and complexity of modern IT infrastructures. This systematic review aimed to analyze the impact and performance of artificial intelligence (AI) agents applied to incident management in ITSM. The review followed the PRISMA guidelines and included 15 studies published between 2021 and 2026. The findings indicate that AI-powered chatbots resolved up to 57% of user inquiries within one or two interaction turns, reduced resolution time by 74.17%, and achieved an intent classification accuracy of 82.5%. In addition, predictive monitoring agents outperformed human experts in early incident detection, while large language models enhanced the analysis of unstructured information and supported more effective incident diagnosis. Despite these advances, significant challenges remain, including the lack of standardized evaluation metrics, limited assessment of economic impact and user satisfaction, and the insufficient integration of AI agents into ITIL-based processes. Overall, AI agents significantly improve operational efficiency and represent a promising technology for advancing incident management within ITSM.
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Copyright (c) 2026 Ronaldo Carlos Robles Romero, Eduardo Joel Romero Vasquez, Alberto Carlos Mendoza de los Santos
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