AIOps Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Offering (Platform, Service), By Application (Infrastructure Management, Application Performance Analysis, Software Asset Management, Network & Security Management, Others), By Deployment (On-Premis

AIOps Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028 Segmented By Offering (Platform, Service), By Application (Infrastructure Management, Application Performance Analysis, Software Asset Management, Network & Security Management, Others), By Deployment (On-Premise, and Cloud), By Enterprise Size (Large Enterprises, Small and Medium-Sized Enterprises (SMEs)), By

Published Date: November - 2024 | Publisher: MIR | No of Pages: 320 | Industry: ICT | Format: Report available in PDF / Excel Format

View Details Buy Now 2890 Download Sample Ask for Discount Request Customization

The Global AIOps Market

Cloud computing technologies are being used by businesses of all kinds and sorts, including start-ups, multinational enterprises, government organizations, and non-profit organizations, to offer a variety of services. The capacity to use basic business tools, such as customer relationship management and process planning, has grown more crucial than ever. Building a smarter organization that makes educated decisions and maximises investments to support innovations has grown more and more dependent on connecting and analyzing data in real-time. The rise of the global AIOps market is being driven by the rising demand for cloud computing as businesses strive to use the newest tools and technologies to manage and optimize their cloud-based operations.

The AI Platform for IT Operations is referred to as AIOps (Artificial Intelligence Platform for IT Operations). It provides a comprehensive perspective of the functioning of IT systems by combining automated techniques and artificial intelligence. One of the key needs that AIOps systems address is the demand for quicker, accurate IT operations. As a result, more people are using AIOPs' products and services.The application of AI in IT operations has become viable thanks to recent technical advancements. The fact that many companies are using knowledge fusion, domain-enriched machine learning (ML), and natural language processing (NLP) approaches to offer improved AIOps platforms and services is one of the major factors driving the industry. The AIOps platform automates routine IT activities using intelligent, self-learning algorithms driven by ML.

Cloud-based infrastructure is being embraced quickly in the IT sector

In recent years, there has been a sharp rise in the popularity of cloud computing. Many businesses are drawn to cloud hosting services like those offered by Microsoft Azure, Amazon Web Services, Inc., and Alphabet Inc. because of its touted characteristics including pay-per-use, self-service, high reliability, and the flexibility to scale up or down based on consumption. These benefits of cloud computing result in much cheaper IT costs, greater service quality, and quicker time to market than traditional IT solutions. Through the provision of centralised visibility across all environments, provided by AIOps solutions, IT problems may be identified and fixed more quickly. For instance, IBM, a global technology firm based in the United States, announced IBM Cloud Pak for Watson AIOps, an AIOps platform for Multicloud Management, in July 2020.

Additionally, they lack access to real-time analytics. As a result, integrating AIOps gives users access to performance data from all environments and pulls information about any outages or slowdowns that may have occurred. It automatically notifies the IT staff of reported problems, does root cause analyses, and suggests remedies. These factors are driving the Global

Growthin Interest in AI-Based Applications

Layers of algorithms are used by artificial intelligence to analyze data, comprehend spoken language, and visually identify things. These algorithms are employed in the processing of data, computation, and robotic thinking. These algorithms must be improved in order to offer better and more effective solutions for a variety of end-use applications. Researchers in artificial intelligence are always attempting to improve various algorithms. Traditional algorithms have shortcomings in terms of efficiency and accuracy. Manufacturers and technology developers have turned their attention to creating standardised algorithms as a result.

Risk mitigation is becoming more important in IT organizations

Risk determines the disruptive technology and economic environments of today. Large businesses differentiate themselves with their capacity to minimize risk and maintain company continuity without sacrificing their core offerings, given the always changing market needs and the quick speed of innovation. For IT organizations, effective risk mitigation methods are vital. In order to identify unrealized risk and danger vectors, risk mitigation techniques evaluate an organization from top to bottom. Threats from both inside and outside the company are included that could interfere with business continuity. The type of danger will determine how the business wants to lessen the effects of the risk or lessen the effects of the occurrence. Thus, in order to reduce risks and increase the value of automation investments, IT organizations are entering the global AIOps market.

Lack of reliable and adaptable AI systems

When deployed as a component of a complete safety-critical system functioning in the physical IT environment, the lack of resilience and adaptability in novel AI algorithms has serious consequences. Poor quality data is largely to blame for the fragility of AI systems. Several issues with data quality include data sparsity, faulty labeling, irrelevant or corrupted data, failure to recognize unexpected patterns, and incorrect pattern learning. Low-quality data impede effective automation procedures because the main goal of any business's AI upgrade is to boost revenues and save costs. For instance, just 15% of firms have access to the necessary data as of 2020, despite the fact that 76% of organizations want to use their data to extract economic value. Therefore, the lack of AI systems poses a threat to the market’s growth.

Market Segmentation

The Global AIOps market is segmented into Offering, Application, Deployment, Enterprise Size, Vertical, Region and Competitive Landscape. Based on Offering, the market is segmented into Platform, Service

Market Players

Recent Developments

·

Attribute

Details

Base Year

2022

Historic Data

2018 â€“ 2021

Estimated Year

2023

Forecast Period

2024 – 2028

Quantitative Units

Revenue in USD Million and CAGR for 2018-2022 and 2023-2028

Report coverage

Revenue forecast, company share, growth factors, and trends

Segments covered

Offering

Application

Deployment

Enterprise Size

Vertical

 

Regional scope

North America; Asia-Pacific; Europe; South America; Middle East & Africa

Country scope

United States, Canada, Mexico, China, India, Japan, South Korea, Australia, Singapore, Malaysia, Germany, United Kingdom, France, Russia, Spain, Belgium, Italy, Brazil, Colombia, Argentina, Peru, Chile, Saudi Arabia, South Africa, UAE, Israel, Turkey

Key companies profiled

AppDynamics, BMC Software, Inc., HCL Technologies Limited, International Business Machines Corporation, Micro Focus, Moogsoft Inc., ProphetStor Data Services, Inc., Resolve Systems, Splunk Inc., VMware, Inc.

Customization scope

10% free report customization with purchase. Addition or alteration to country, regional & segment scope.

Pricing and purchase options

Avail customized purchase options to meet your exact research needs. Explore purchase options

Delivery Format

PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)

Related Reports

Table of Content

To get a detailed Table of content/ Table of Figures/ Methodology Please contact our sales person at ( chris@marketinsightsresearch.com )

List Tables Figures

To get a detailed Table of content/ Table of Figures/ Methodology Please contact our sales person at ( chris@marketinsightsresearch.com )

FAQ'S

For a single, multi and corporate client license, the report will be available in PDF format. Sample report would be given you in excel format. For more questions please contact:

sales@marketinsightsresearch.com

Within 24 to 48 hrs.

You can contact Sales team (sales@marketinsightsresearch.com) and they will direct you on email

You can order a report by selecting payment methods, which is bank wire or online payment through any Debit/Credit card, Razor pay or PayPal.

Discounts are available.

Hard Copy

Email