Optimizing and Enhancing IT Operation Operating Models Through Artificial Intelligence

Artificial Intelligence for IT Operations (AIOps) signifies a radical change in managing and controlling complex IT frameworks. Operating together with artificial intelligence and machine learning technologies, AIOps platforms improve incident management, predictive modeling, root cause analysis, and the entire operation processes [1]–[4]. Addressing these existing problems becomes highly important as the enhancement of IT infrastructures continues to escalate due to the increasing adoption of hybrid and multi-cloud technologies [5]. Most importantly, AIOps helps organizations realize their goals, such as detecting abnormal behavior in a system in realtime, eliminating or automating repetitive processes, estimating the probability of system breakdown, and making the best use of available resources to enhance service delivery while minimizing operational expenses [6] [7]. AIOps also assists organizations in managing probable problems in the best possible manner to maintain both effectiveness and flexibility. This paper discusses the primary purposes of AIOps, how it is set to change the practice of IT operations, the problems encountered when applying this system, and the tactical approaches needed to accomplish this plan effectively. Using practical examples and looking into the horizon, we stress the significance of AIOps application for the development of the IT ecosystem across various sectors in the near future [8].