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title: AIOps Platform Market Size to Grow at a CAGR of 32.2% from 2021 to 2028

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# AIOps Platform Market Size to Grow at a CAGR of 32.2% from 2021 to 2028
According to the study of The Insight Partners titled "***[AIOps Platform Market](https://)*** Forecast to 2028 – COVID-19 Impact and Global Analysis – by component, deployment, organization size, and Vertical," the AIOps platform market size is projected to reach US$ 19,933.5 million by 2028 from US$ 2,831.2 million in 2021. It is expected to rise at a CAGR of 32.2% from 2021 to 2028.

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The Artificial Intelligence for IT Operations (AIOps) platform mixes human intelligence with automated algorithms to give users complete visibility into IT system performance. The achievement of necessary speed and agility required for companies is a crucial driver pushing the adoption of AIOps in the IT environment. Furthermore, modern machine learning algorithms gather essential data collected in the background and provide actionable insights.

Increasing Global Data Driving AIOps Platform Market Growth
According to the annual DataSphere and StorageSphere study, published by International Data Corporation (IDC) in 2021, the quantity of data created, recorded, duplicated, and consumed worldwide increased from 1.2 trillion gigabytes to 59 trillion gigabytes between 2010 and 2020. It is projected to reach more than 180 zettabytes by 2025.

![](https://i.imgur.com/9NuHcWm.png)

**IBM; Splunk, Inc.; BMC Software, Inc; Broadcom Inc; and Moogsoft- Prominent Market Participants in AIOps Platform Market**


**Some of the companies competing in The AIOps Platform Market are** 
1.	IBM
2.	AppDynamics
3.	BMC Software, Inc
4.	Broadcom Inc
5.	Dynatrace LLC
6.	HCL Technologies Limited
7.	Micro Focus International plc
8.	Moogsoft
9.	Resolve Systems, LLC
10.	Splunk Inc.
11.	BigPanda

The AIOps platform employs intelligence and self-learning algorithms supported by machine learning to automate routine IT processes. It also analyses historical and behavioral data to detect and predict potential incidents. Furthermore, it uses big data analytics to analyze cognitive data and draws relevant information from data for complete processing. Real-time data correlation, multi-dimensional data normalization, severity-based issue prioritization, and established response plans to mitigate future disasters are all made possible by integrating IT operations with AI. This ability to generate meaningful insights from scratch data aids in the development of a flexible AIOps system.

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