The AIOps platform market size is expected to grow from US$ 2,831.2 million in 2021 to US$ 19,933.5 million by 2028


It is estimated to grow at a CAGR of 32. 2% from 2021 to 2028. The Artificial Intelligence for IT Operations (AIOps) platform mixes human intelligence with automated algorithms to give users complete visibility into IT system performance.

New York, June 20, 2022 (GLOBE NEWSWIRE) — announces the release of the report “AIOps Platform Market Forecast to 2028 – COVID-19 Impact and Global Analysis By Component, Deployment, Organization Size, and Vertical”

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.

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.

Factors such as the IT Data Exceeding Human Scale and AIOps assists enterprises in integrating diverse technologies and reducing the overhead time by automating various procedures thus, need for resource optimization are influencing the market growth.However, concerns regarding the adoption of modern solution over traditional methodology are restraining AIOps Platform market growth.

Moreover, integration of AIOps Platform with Observability Platforms are among other factors contributing toward the AIOps platform market growth.

Processes that formerly required human involvement have been automated by installing AIOps platform, allowing employees to focus on their core tasks.This results in the most efficient use of resources; resource optimization becomes more important when demand exceeds available resources.

AIOps assists enterprises in integrating diverse technologies and reducing the overhead time by automating various procedures.Corporate process automation removes manual quality assurance, execution procedures, and maximizes the use of resources.

According to a survey by Smartsheet, 69% of employees believe that automation decreases spare time, and out of which 59% believe if repetitive jobs were automated, they would have more than 6 spare hours each week.Organizations that operate in the global information technology market have offices in various parts of the globe.

As a result, onboarding employees, tracking employee performance, maintaining employee time and attendance gets complicated. AIOps platform and communication tools make it easier for distant teams and personnel to manage projects from a long distance. AIOps platform also aids in the automation and streamlining of HR activities. According to Wynhurst Group, a structured onboarding program helps firms retain 58% of their employees for at least 3 years. A good AIOps platform saves money and paves the way to improve business operations. As a result, automated business processes speed up and simplify activities, allowing employees to be more productive, motivated, and engaged at work. Hence, the factors mentioned above boost the growth of the AIOps platform market.

Impact of COVID-19 Pandemic on Europe AIOps Platform Market
Russia, the UK, France, Italy, Spain, and Germany were most affected by the COVID-19 outbreak.Due to severe economic challenges, businesses in the region have had to cease or significantly restrict their operations.

The region witnessed an economic recession in 2020 and 2021 due to business closures, travel prohibitions, and supply chain disruptions.However, Morning Consult surveyed 500 top decision-makers of the tech industry in the UK, France, Germany, Italy, and Spain.

Surprisingly 36% of respondents said the COVID-19 outbreak had expedited their companies’ AI adoption. Hence, COVID-19 had a positive impact on the Europe AIOps platform market share.

AIOps platform market analysis by component, the AIOps platform market is segmented into platform and services.In 2021, the platform segment led the market with a larger AIOps platform market share.

Based on deployment, the market is segmented into on-premises and cloud-based.In 2021, the cloud-based segment accounted for a larger market share.

Based on organization size, the market is segmented into small and medium enterprises and large enterprises.In 2021, the large enterprises segment accounted for a more prominent market share.

AIOps platform market analysis by vertical, the market is segmented into BFSI, IT & telecom, aerospace and defense, government, transportation, and others. In 2021, the BFSI segment accounted for the largest market share.

By geography, the AIOps Platform market is segmented into North America, Europe, Asia Pacific (APAC), the Middle East & Africa (MEA), and South America (SAM). In 2021, North America accounted for the largest share in the global market.

The size of the AIOps Platform market has been derived using both primary and secondary sources.To begin the research process, exhaustive secondary research has been conducted using internal and external sources to obtain qualitative and quantitative information related to the market.

The process also serves the purpose of obtaining an overview and forecast for the AIOps platform market with respect to all the segments.It also provides the overview and forecast for the market based on all the segmentation provided with respect to five major regions—North America, Europe, Asia Pacific, Middle East & Africa, and South America.

Primary interviews were conducted with industry participants to validate data and gain more analytical insights. Participants of this process are industry experts, such as VPs, business development managers, market intelligence managers, national sales managers, and external consultants, including valuation experts, research analysts, and key opinion leaders, specializing in the AIOps Platform market.

The key companies operating in the AIOps platform market are IBM; AppDynamics; BMC Software, Inc; Broadcom Inc; Dynatrace LLC; HCL Technologies Limited; Micro Focus; Moogsoft Inc.; Resolve Systems, LLC; BigPanda; and Splunk Inc.

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