Artificial Intelligence for IT Operations Platform Market (By Offering: Platform, Service; By Application: Infrastructure Management, Application Performance Analysis, Real-Time Analytics, Network & Security Management, Others; By Deployment: Cloud, On-premise; By Organization Size: SMEs, Large Enterprises; By Industry Vertical) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032
The global artificial intelligence for IT operations platform market size was estimated at USD 10.62 billion in 2022 and it is expected to hit around USD 55.32 billion by 2032, growing at a CAGR of 17.95% during the forecast period from 2023 to 2032.
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Artificial intelligence for IT operations is referred to as AIOps. It is a novel method of managing technology that makes use of machine learning and artificial intelligence to find issues before they arise, forecast when they will, and promptly fix them. Combining the best of human and machine intelligence to do regular activities while enabling IT employees to concentrate on more essential things, helps companies decrease downtime, enhance uptime, and raise productivity. Approximately 90% of CIOs in the Global 2000 will utilize AIOps solutions by 2026 to automate workload and remediation procedures, boost cost and performance metrics, and increase resilience and agility.
The market for artificial intelligence operations platforms is being pushed by reasons including the rising connection in IT operations, the growing need for image recognition systems, and increased data expansion. A possibility is presented by the procurement of cutting-edge technology by expanding big market corporations. Artificial intelligence for IT operations (AIOps) usage is also expanding as systems grow more complex as a result of rising data volume and device intelligence. The increased global use of cloud computing is also encouraging the automation of these processes. As more businesses move to the cloud, it is predicted that the need for artificial intelligence for IT operations (AIOps) solutions will rise.
Report Coverage | Details |
Market Size in 2023 | USD 12.52 Billion |
Market Size by 2032 | USD 55.32 Billion |
Growth Rate from 2023 to 2032 | CAGR of 17.95% |
Largest Market | North America |
Base Year | 2022 |
Forecast Period | 2023 To 2032 |
Segments Covered | By Offering, By Application, By Deployment, and By Organization Size |
Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Driver:
Increasing IT complexities and data volumes
With the rapid proliferation of technology and the adoption of cloud computing, virtualization, containerization, and distributed systems, IT infrastructures have become more complex and dynamic. AIOps platforms help organizations manage this complexity by providing real-time insights, automation, and predictive analytics to optimize IT operations. In addition, the explosion of data generated by various applications, devices, and systems has created a need for advanced analytics solutions. AIOps platforms are capable of ingesting and analyzing large volumes of data from diverse sources, enabling organizations to gain valuable insights and make data-driven decisions. Thus, this is expected to drive market growth over the forecast period.
Restraint:
Data privacy and security concerns
Platforms for IT operations rely heavily on accessing and analyzing vast amounts of data from various sources, including sensitive information. This raises concerns about data privacy, compliance with regulations (e.g., GDPR, CCPA), and the risk of potential data breaches. Organizations need to ensure robust data security measures and comply with data protection laws while leveraging AIOps platforms. Therefore, data privacy and security concerns are one of the major restraints that hamper the market growth over the forecasted period.
Opportunity:
Cloud migration and hybrid IT environments
The adoption of cloud computing and the proliferation of hybrid IT environments create complex IT infrastructures. AIOps platforms offer the ability to manage and monitor such diverse environments effectively, providing real-time insights and proactive incident management. The growth in cloud adoption presents a significant opportunity for AIOps vendors to cater to the unique needs of cloud-native and hybrid environments. Thus, this is expected to offer a lucrative opportunity for market growth during the projected period.
Based on the offering, the global artificial intelligence for IT operations platform market is segmented into platform and service. The platform segment is expected to grow at a substantial rate over the forecast period. AIOps manufacturers provide corporate organizations with dependable, adaptable, and cutting-edge platform experiences to give them a competitive edge in the marketplace. Its corporate advantages, including improved integrated agility, decision-making, effective data processing, and quicker digital transformation, should be credited for this significant market share.
Based on the application, the global artificial intelligence for IT operations platform market is segmented into infrastructure management, application performance analysis, real-time analytics, network & security management and others. The real-time analytics segment is expected to dominate the market over the forecast period. The integration of real-time analytics in AIOps platforms is expected to continue driving their adoption across various industries. As organizations seek to optimize their IT operations and deliver seamless digital experiences, the demand for AIOps platforms with real-time analytics capabilities is likely to grow.
Moreover, advancements in AI and ML technologies will further enhance real-time analytics in AIOps platforms, providing more accurate insights and predictive capabilities. Vendors are expected to focus on developing scalable and real-time data processing solutions to cater to the increasing demand for real-time analytics in AIOps platforms. Thereby, driving market growth.
Based on the deployment mode, the global artificial intelligence for IT operations platform market is segmented into cloud and on-premise. The cloud segment is expected to grow at the fastest rate over the forecast period due to the variables including the growing use of cloud computing by businesses, considerable expenditures in cloud infrastructure services, and a strong need for automating labor processes at low cost.
As cloud platforms may provide easy accessibility, huge data storage, flexibility, hassle-free deployment, and other benefits, they are among the key drivers impacting the market's expansion. Cloud-based AI solutions, which are more common than on-premise models, do not require additional hardware installation or infrastructure upkeep and reduce organizational upfront expenses. Additionally, choices for price flexibility, such as monthly or yearly subscriptions, have had a significant impact on the market development of cost-effective AI platforms throughout the period. Therefore, propelling the segment growth during the forecast period.
Based on the organization size, the global artificial intelligence for IT operations platform market is segmented into SMEs and large enterprises. The large enterprise segment accounted for the largest revenue share and is expected to continue the same pattern over the forecast period. Large enterprises often have sprawling and diverse IT infrastructures, including multiple data centers, cloud environments, and hybrid setups. AIOps platforms were deployed to manage these complex infrastructures efficiently. Large enterprises deal with a significant volume of IT incidents daily. AIOps' predictive and proactive capabilities were leveraged to detect and resolve incidents before they impacted business operations. Automated incident correlation and root cause analysis facilitated faster resolution, minimizing the impact on end-users and reducing downtime. Thereby, driving the segment growth over the forecast period.
The BFSI segment is expected to dominate the market over the forecast period. The IT Operations in the financial services industry frequently use AIOPs, a potent methodology. Whenever used diligently, wisely, and carefully by enterprises, it has the potential to be beneficial. Finance AIOps include anything from chatbot assistance to task automation and incident detection. Security challenges and data breaches are common in the banking sector. AIOps platforms and tools may prevent these problems and raise customer satisfaction levels by improving the standard of financial services provided. Thus, these advantages are expected to propel the segment expansion over the forecast period.
The Asia Pacific is expected to grow at the highest CAGR over the forecast period. Growing R&D efforts for artificial intelligence products, the quick development of AI-based applications, a major move towards digitalization, and Industry 4.0 trends will all contribute to the market's expansion in the area. Additionally, higher expenditures in cloud-based infrastructures, a focus on AI-based skill development initiatives on the part of the government, as well as the adoption of AI-based workloads across a variety of industries, may all contribute to the market growth of AI platforms. Moerover, the massive use of data science, computer vision, and natural language processing technology in various industries promotes the market’s growth. All these factors collectively boost the growth of the market in Asia Pacific.
North America is expected to capture a significant market share over the forecast period. Consumer apps for AI-based investing advices are gaining steam in the US to help investors make better investment choices. This is supported by the region's abundance of AIOps platform manufacturers. AIOps platforms are being created by several companies, including IT giants and start-ups. AIOps platform adoption in the area is also significantly influenced by substantial R&D spending and ongoing digital transformation in advanced countries. AIOps solutions that offer full-stack observability, actionable analytics, and intelligent automation are used by multiple firms in North Americs to enhance the digital experience in addition to providing LEDs and a variety of other technology-related products. Thus, driving the market growth in the region.
Segments Covered in the Report:
By Offering
By Application
By Deployment
By Organization Size
By Geography
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Artificial Intelligence for IT Operations Platform Market
5.1. COVID-19 Landscape: Artificial Intelligence for IT Operations Platform Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Artificial Intelligence for IT Operations Platform Market, By Offering
8.1. Artificial Intelligence for IT Operations Platform Market, by Offering, 2023-2032
8.1.1. Platform
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Service
8.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Artificial Intelligence for IT Operations Platform Market, By Application
9.1. Artificial Intelligence for IT Operations Platform Market, by Application, 2023-2032
9.1.1. Infrastructure Management
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Application Performance Analysis
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Real-Time Analytics
9.1.3.1. Market Revenue and Forecast (2020-2032)
9.1.4. Network & Security Management
9.1.4.1. Market Revenue and Forecast (2020-2032)
9.1.5. Others
9.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Artificial Intelligence for IT Operations Platform Market, By Deployment
10.1. Artificial Intelligence for IT Operations Platform Market, by Deployment, 2023-2032
10.1.1. Cloud
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. On-premise
10.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Artificial Intelligence for IT Operations Platform Market, By Organization Size
11.1. Artificial Intelligence for IT Operations Platform Market, by Organization Size, 2023-2032
11.1.1. SMEs
11.1.1.1. Market Revenue and Forecast (2020-2032)
11.1.2. Large Enterprises
11.1.2.1. Market Revenue and Forecast (2020-2032)
11.1.3. By Industry Vertical
11.1.3.1. Market Revenue and Forecast (2020-2032)
11.1.4. BFSI
11.1.4.1. Market Revenue and Forecast (2020-2032)
11.1.5. Healthcare & Life Sciences
11.1.5.1. Market Revenue and Forecast (2020-2032)
11.1.6. Retail & E-commerce
11.1.6.1. Market Revenue and Forecast (2020-2032)
11.1.7. IT & Telecom
11.1.7.1. Market Revenue and Forecast (2020-2032)
11.1.8. Energy & Utilities
11.1.8.1. Market Revenue and Forecast (2020-2032)
11.1.9. Government & Public Sector
11.1.9.1. Market Revenue and Forecast (2020-2032)
11.1.10. Media & Entertainment
11.1.10.1. Market Revenue and Forecast (2020-2032)
11.1.11. Others
11.1.11.1. Market Revenue and Forecast (2020-2032)
Chapter 12. Global Artificial Intelligence for IT Operations Platform Market, Regional Estimates and Trend Forecast
12.1. North America
12.1.1. Market Revenue and Forecast, by Offering (2020-2032)
12.1.2. Market Revenue and Forecast, by Application (2020-2032)
12.1.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.1.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.1.5. U.S.
12.1.5.1. Market Revenue and Forecast, by Offering (2020-2032)
12.1.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.1.5.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.1.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.1.6. Rest of North America
12.1.6.1. Market Revenue and Forecast, by Offering (2020-2032)
12.1.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.1.6.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.1.6.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.2. Europe
12.2.1. Market Revenue and Forecast, by Offering (2020-2032)
12.2.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.2.5. UK
12.2.5.1. Market Revenue and Forecast, by Offering (2020-2032)
12.2.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.5.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.2.6. Germany
12.2.6.1. Market Revenue and Forecast, by Offering (2020-2032)
12.2.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.6.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.6.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.2.7. France
12.2.7.1. Market Revenue and Forecast, by Offering (2020-2032)
12.2.7.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.7.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.7.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.2.8. Rest of Europe
12.2.8.1. Market Revenue and Forecast, by Offering (2020-2032)
12.2.8.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.8.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.2.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.3. APAC
12.3.1. Market Revenue and Forecast, by Offering (2020-2032)
12.3.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.3.5. India
12.3.5.1. Market Revenue and Forecast, by Offering (2020-2032)
12.3.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.5.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.3.6. China
12.3.6.1. Market Revenue and Forecast, by Offering (2020-2032)
12.3.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.6.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.6.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.3.7. Japan
12.3.7.1. Market Revenue and Forecast, by Offering (2020-2032)
12.3.7.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.7.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.7.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.3.8. Rest of APAC
12.3.8.1. Market Revenue and Forecast, by Offering (2020-2032)
12.3.8.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.8.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.3.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.4. MEA
12.4.1. Market Revenue and Forecast, by Offering (2020-2032)
12.4.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.4.5. GCC
12.4.5.1. Market Revenue and Forecast, by Offering (2020-2032)
12.4.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.5.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.4.6. North Africa
12.4.6.1. Market Revenue and Forecast, by Offering (2020-2032)
12.4.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.6.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.6.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.4.7. South Africa
12.4.7.1. Market Revenue and Forecast, by Offering (2020-2032)
12.4.7.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.7.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.7.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.4.8. Rest of MEA
12.4.8.1. Market Revenue and Forecast, by Offering (2020-2032)
12.4.8.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.8.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.4.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.5. Latin America
12.5.1. Market Revenue and Forecast, by Offering (2020-2032)
12.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.5.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.5.5. Brazil
12.5.5.1. Market Revenue and Forecast, by Offering (2020-2032)
12.5.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.5.5.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.5.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)
12.5.6. Rest of LATAM
12.5.6.1. Market Revenue and Forecast, by Offering (2020-2032)
12.5.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.5.6.3. Market Revenue and Forecast, by Deployment (2020-2032)
12.5.6.4. Market Revenue and Forecast, by Organization Size (2020-2032)
Chapter 13. Company Profiles
13.1. IBM Corporation
13.1.1. Company Overview
13.1.2. Product Offerings
13.1.3. Financial Performance
13.1.4. Recent Initiatives
13.2. Micro Focus
13.2.1. Company Overview
13.2.2. Product Offerings
13.2.3. Financial Performance
13.2.4. Recent Initiatives
13.3. Broadcom
13.3.1. Company Overview
13.3.2. Product Offerings
13.3.3. Financial Performance
13.3.4. Recent Initiatives
13.4. HCL Technologies Limited
13.4.1. Company Overview
13.4.2. Product Offerings
13.4.3. Financial Performance
13.4.4. Recent Initiatives
13.5. Splunk Inc.
13.5.1. Company Overview
13.5.2. Product Offerings
13.5.3. Financial Performance
13.5.4. Recent Initiatives
13.6. BMC Software, Inc.
13.6.1. Company Overview
13.6.2. Product Offerings
13.6.3. Financial Performance
13.6.4. Recent Initiatives
13.7. Moogsoft
13.7.1. Company Overview
13.7.2. Product Offerings
13.7.3. Financial Performance
13.7.4. Recent Initiatives
13.8. ProphetStor Data Services, Inc.
13.8.1. Company Overview
13.8.2. Product Offerings
13.8.3. Financial Performance
13.8.4. Recent Initiatives
13.9. Resolve Systems
13.9.1. Company Overview
13.9.2. Product Offerings
13.9.3. Financial Performance
13.9.4. Recent Initiatives
13.10. AppDynamics
13.10.1. Company Overview
13.10.2. Product Offerings
13.10.3. Financial Performance
13.10.4. Recent Initiatives
Chapter 14. Research Methodology
14.1. Primary Research
14.2. Secondary Research
14.3. Assumptions
Chapter 15. Appendix
15.1. About Us
15.2. Glossary of Terms
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