AI for Information Tecchnology Operation (AIOps): A Review of IT Incident Risk Prediction

  • Salman Ahmed
  • , Muskaan Singh
  • , Brendan Doherty
  • , Effirul Ramlan
  • , Kathryn Harkin
  • , Damien Coyle

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

5 Citations (Scopus)

Abstract

The advancement of Artificial Intelligence has led to a surge in its application in Information Technology (IT) Operations, often termed Artificial Intelligence for IT Operations (AIOPS). One of the most challenging problems in AIOPS is IT Service Management (ITSM), which deals with incidents and anomalies of users, often referred to as tickets. These tickets are resolved by the IT firm support system, which plays a significant role in the company's user experiences, productivity, and profit. Recent advances have been made to automate the prediction of IT incidents and resolve them in a minimal time, utilizing AI models. In this paper, we take stock of the work in this domain and review the challenges. We also highlight the open topics that require further investigation for the advancement of the field.

Original languageEnglish
Title of host publication2022 9th International Conference on Soft Computing and Machine Intelligence, ISCMI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages253-257
Number of pages5
ISBN (Electronic)9798350320886
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event9th International Conference on Soft Computing and Machine Intelligence, ISCMI 2022 - Toronto, Canada
Duration: 26 Nov 202227 Nov 2022

Publication series

Name2022 9th International Conference on Soft Computing and Machine Intelligence, ISCMI 2022

Conference

Conference9th International Conference on Soft Computing and Machine Intelligence, ISCMI 2022
Country/TerritoryCanada
CityToronto
Period26/11/2227/11/22

Keywords

  • Artificial Intelligence for IT Operations (AIOPS)
  • Dataset Imbalance
  • Information Technology Infrastructure Library (ITIL)
  • IT Incidents
  • IT Service Management (ITSM)
  • Risk prediction

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