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Global Artificial intelligence for the IT operations platform Market is valued at approximately USD 7.1 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 17.7% over the forecast period 2022-2028. AIOps can be defined as the application of AI, and related technologies, such as machine learning and Natural Language Processing (NLP) to automate the traditional IT Ops activities and tasks. AIOps platform is used across different industries to automate several functions such as management of big data, Performance analysis, Anomaly detection, Event correlation and analysis as well as IT service management among others. The increasing cloud-based infrastructure in the IT sector and rising demand for AI-based Applications as well as strategic initiatives from leading market players are key factors accelerating the growth of the Market. For instance, according to Statista, the AI software market is estimated to reach a target of 126 billion USD by 2025. And as per sources, 37% of organizations have already implemented AI in some or other form. the need for employees for AI has also grown by over 270% in last the 4 years i.e., 2018-2022. Moreover, leading market players are coming up with new products to leverage the growing adoption of the AIOps Platform. For instance, in Dec 2021, Newbury, UK based Micro Focus launched its new Operations Bridge – SaaS AIOps platform. This new platform is intended for IT organizations. Also, increasing investment in AI from various industries and rising integration of IT operations with AI would create lucrative growth opportunities for the Market during the forecast period. However, rising concern over data security and privacy impedes the market growth throughout the forecast period of 2022-2028.
The key regions considered for the Global Artificial intelligence for IT operations platform Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America is the leading region in terms of market share, owing to the factors such as consumer application AI-based investing advice is becoming more popular to improve investment decisions and the presence of multiple AIOps platform vendors in North America. The Asia Pacific is expected to grow significantly during the forecast period, owing to the rapid acclimatization of AIOps platforms. Moreover, the large data volume presence has created a way to make the Asia Pacific region adopt AI-based solutions and services such as business/data analytics.
Major market players included in this report are:
AppDynamics
BMC Software, Inc.
Broadcom
HCL Technologies Limited
International Business Machines Corporation
Micro Focus
Moogsoft
ProphetStor Data Services, Inc.
Resolve Systems
Splunk Inc.
The objective of the study is to define the market sizes of different segments & countries in recent years and to forecast the values for the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with a detailed analysis of the competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Offering:
Service
Platform
By Application:
Application Performance Analysis
Infrastructure Management
Real-Time Analytics
Network & Security Management
Others
By Deployment Mode:
On-premises
Cloud
By Organization Size:
Large Enterprises
SMEs
By End Use Industry:
Healthcare & Life Sciences
BFSI
Retail & E-commerce
IT & Telecom
Energy & Utilities
Government & Public Sector
Media & Entertainment
Others
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World
Furthermore, years considered for the study are as follows:
Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028
Target Audience of the Global Artificial intelligence for IT operations platform Market in Market Study:
Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors
Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. Global Artificial intelligence for IT operations platform (AIOps) Market, by Region, 2020-2028 (USD Billion)
1.2.2. Global Artificial intelligence for IT operations platform (AIOps) Market, by Offering, 2020-2028 (USD Billion)
1.2.3. Global Artificial intelligence for IT operations platform (AIOps) Market, by Application, 2020-2028 (USD Billion)
1.2.4. Global Artificial intelligence for IT operations platform (AIOps) Market, by Deployment Mode, 2020-2028 (USD Billion)
1.2.5. Global Artificial intelligence for IT operations platform (AIOps) Market, by Organization Size, 2020-2028 (USD Billion)
1.2.6. Global Artificial intelligence for IT operations platform (AIOps) Market, by End Use Industry, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Artificial intelligence for IT operations platform (AIOps) Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Artificial intelligence for IT operations platform (AIOps) Market Dynamics
3.1. Artificial intelligence for IT operations platform (AIOps) Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Increasing cloud-based infrastructure in IT sector
3.1.1.2. Rising demand for AI-based Applications
3.1.1.3. Strategic initiatives from leading market players.
3.1.2. Market Challenges
3.1.2.1. Rising concern over data privacy and protection
3.1.3. Market Opportunities
3.1.3.1. Increasing investment towards AI from various industries
3.1.3.2. Rising integration of IT operation with AI.
Chapter 4. Global Artificial intelligence for IT operations platform (AIOps) Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Artificial intelligence for IT operations platform (AIOps) Market, by Offering
6.1. Market Snapshot
6.2. Global Artificial intelligence for IT operations platform (AIOps) Market by Offering, Performance – Potential Analysis
6.3. Global Artificial intelligence for IT operations platform (AIOps) Market Estimates & Forecasts by Offering 2018-2028 (USD Billion)
6.4. Artificial intelligence for IT operations platform (AIOps) Market, Sub Segment Analysis
6.4.1. Platform
6.4.2. Service
Chapter 7. Global Artificial intelligence for IT operations platform (AIOps) Market, by Application
7.1. Market Snapshot
7.2. Global Artificial intelligence for IT operations platform (AIOps) Market by Application, Performance – Potential Analysis
7.3. Global Artificial intelligence for IT operations platform (AIOps) Market Estimates & Forecasts by Application 2018-2028 (USD Billion)
7.4. Artificial intelligence for IT operations platform (AIOps) Market, Sub Segment Analysis
7.4.1. Application Performance Analysis
7.4.2. Infrastructure Management
7.4.3. Real-Time Analytics
7.4.4. Network & Security Management
7.4.5. Others
Chapter 8. Global Artificial intelligence for IT operations platform (AIOps) Market, by Deployment Mode
8.1. Market Snapshot
8.2. Global Artificial intelligence for IT operations platform (AIOps) Market by Deployment Mode, Performance – Potential Analysis
8.3. Global Artificial intelligence for IT operations platform (AIOps) Market Estimates & Forecasts by Deployment Mode 2018-2028 (USD Billion)
8.4. Artificial intelligence for IT operations platform (AIOps) Market, Sub Segment Analysis
8.4.1. On-premises
8.4.2. Cloud
Chapter 9. Global Artificial intelligence for IT operations platform (AIOps) Market, by Organization Size
9.1. Market Snapshot
9.2. Global Artificial intelligence for IT operations platform (AIOps) Market by Organization Size, Performance – Potential Analysis
9.3. Global Artificial intelligence for IT operations platform (AIOps) Market Estimates & Forecasts by Organization Size 2018-2028 (USD Billion)
9.4. Artificial intelligence for IT operations platform (AIOps) Market, Sub Segment Analysis
9.4.1. Large Enterprises
9.4.2. SMEs
Chapter 10. Global Artificial intelligence for IT operations platform (AIOps) Market, by End Use Industry
10.1. Market Snapshot
10.2. Global Artificial intelligence for IT operations platform (AIOps) Market by End Use Industry, Performance – Potential Analysis
10.3. Global Artificial intelligence for IT operations platform (AIOps) Market Estimates & Forecasts by End Use Industry 2018-2028 (USD Billion)
10.4. Artificial intelligence for IT operations platform (AIOps) Market, Sub Segment Analysis
10.4.1. Healthcare & Life Sciences
10.4.2. BFSI
10.4.3. Retail & E-commerce
10.4.4. IT & Telecom
10.4.5. Energy & Utilities
10.4.6. Government & Public Sector
10.4.7. Media & Entertainment
10.4.8. Others
Chapter 11. Global Artificial intelligence for IT operations platform (AIOps) Market, Regional Analysis
11.1. Artificial intelligence for IT operations platform (AIOps) Market, Regional Market Snapshot
11.2. North America Artificial intelligence for IT operations platform (AIOps) Market
11.2.1. U.S. Artificial intelligence for IT operations platform (AIOps) Market
11.2.1.1. Offering estimates & forecasts, 2018-2028
11.2.1.2. Application estimates & forecasts, 2018-2028
11.2.1.3. Deployment Mode estimates & forecasts, 2018-2028
11.2.1.4. Organization size estimates & forecasts, 2018-2028
11.2.1.5. End Use Industry estimates & forecasts, 2018-2028
11.2.2. Canada Artificial intelligence for IT operations platform (AIOps) Market
11.3. Europe Artificial intelligence for IT operations platform (AIOps) Market Snapshot
11.3.1. U.K. Artificial intelligence for IT operations platform (AIOps) Market
11.3.2. Germany Artificial intelligence for IT operations platform (AIOps) Market
11.3.3. France Artificial intelligence for IT operations platform (AIOps) Market
11.3.4. Spain Artificial intelligence for IT operations platform (AIOps) Market
11.3.5. Italy Artificial intelligence for IT operations platform (AIOps) Market
11.3.6. Rest of Europe Artificial intelligence for IT operations platform (AIOps) Market
11.4. Asia-Pacific Artificial intelligence for IT operations platform (AIOps) Market Snapshot
11.4.1. China Artificial intelligence for IT operations platform (AIOps) Market
11.4.2. India Artificial intelligence for IT operations platform (AIOps) Market
11.4.3. Japan Artificial intelligence for IT operations platform (AIOps) Market
11.4.4. Australia Artificial intelligence for IT operations platform (AIOps) Market
11.4.5. South Korea Artificial intelligence for IT operations platform (AIOps) Market
11.4.6. Rest of Asia Pacific Artificial intelligence for IT operations platform (AIOps) Market
11.5. Latin America Artificial intelligence for IT operations platform (AIOps) Market Snapshot
11.5.1. Brazil Artificial intelligence for IT operations platform (AIOps) Market
11.5.2. Mexico Artificial intelligence for IT operations platform (AIOps) Market
11.6. Rest of The World Artificial intelligence for IT operations platform (AIOps) Market
Chapter 12. Competitive Intelligence
12.1. Top Market Strategies
12.2. Company Profiles
12.2.1. AppDynamics
12.2.1.1. Key Information
12.2.1.2. Overview
12.2.1.3. Financial (Subject to Data Availability)
12.2.1.4. Product Summary
12.2.1.5. Recent Developments
12.2.2. BMC Software, Inc.
12.2.3. Broadcom
12.2.4. HCL Technologies Limited
12.2.5. International Business Machines Corporation
12.2.6. Micro Focus
12.2.7. Moogsoft
12.2.8. ProphetStor Data Services, Inc.
12.2.9. Resolve Systems
12.2.10. Splunk Inc
Chapter 13. Research Process
13.1. Research Process
13.1.1. Data Mining
13.1.2. Analysis
13.1.3. Market Estimation
13.1.4. Validation
13.1.5. Publishing
13.2. Research Attributes
13.3. Research Assumption
At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.
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