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In recent years, the AIOps platform market has been witnessing significant growth and innovation, driven by the increasing complexity of IT environments and the growing need for intelligent automation and analytics solutions. AIOps, which stands for Artificial Intelligence for IT Operations, refers to the use of artificial intelligence (AI) and machine learning (ML) techniques to automate and enhance various aspects of IT operations, including monitoring, troubleshooting, incident management, and performance optimization. One of the key trends in this market is the adoption of AIOps platforms by organizations across various industries to improve the efficiency, reliability, and agility of their IT infrastructure and services. This trend is driven by the growing complexity of modern IT environments, which often consist of a mix of on-premises and cloud-based infrastructure, as well as a wide range of applications and services.
Moreover, there is a growing emphasis on proactive and predictive IT operations within the AIOps platform market. Traditional IT monitoring and management tools often rely on manual intervention and reactive responses to incidents and issues. AIOps platforms, on the other hand, leverage AI and ML algorithms to analyze vast amounts of data from various sources, including logs, metrics, events, and alerts, in real time. By proactively identifying patterns, anomalies, and trends in IT data, AIOps platforms can predict potential issues before they occur, enabling IT teams to take preemptive action to prevent downtime, optimize performance, and improve overall system reliability.
Another key trend in the AIOps platform market is the convergence of AIOps with other IT and business operations management tools and disciplines, such as DevOps, IT service management (ITSM), and application performance monitoring (APM). This convergence reflects the growing recognition of the interdependencies and interconnectedness of various aspects of IT operations and the need for integrated and holistic approaches to managing and optimizing IT services. By integrating AIOps capabilities with existing IT management tools and practices, organizations can streamline workflows, break down silos, and improve collaboration among different teams and stakeholders, leading to faster problem resolution, higher service availability, and better business outcomes.
Furthermore, there is a growing demand for cloud-native AIOps platforms that are designed to operate in cloud-based and hybrid IT environments. As organizations increasingly migrate their IT infrastructure and workloads to the cloud, they need AIOps solutions that can seamlessly integrate with cloud-native technologies and provide visibility and control across distributed and dynamic environments. Cloud-native AIOps platforms leverage containerization, microservices architecture, and serverless computing to deliver scalability, agility, and flexibility, enabling organizations to adapt to changing business requirements and scale their operations with ease.
Additionally, the AIOps platform market is witnessing increased adoption of autonomous and self-healing capabilities. With the proliferation of AI and ML technologies, AIOps platforms are becoming increasingly autonomous, able to analyze, diagnose, and resolve IT issues without human intervention. Autonomous AIOps platforms can automatically detect anomalies, correlate events, and recommend or execute remediation actions in real time, reducing the burden on IT teams and enabling them to focus on more strategic initiatives. By automating routine tasks and responses, autonomous AIOps platforms can improve operational efficiency, reduce mean time to resolution (MTTR), and enhance overall system reliability and availability.
Moreover, there is a growing focus on democratizing AIOps capabilities and making them accessible to a wider range of users within organizations. Traditionally, AIOps has been the domain of specialized IT teams with expertise in data science and machine learning. However, there is a growing recognition of the need to democratize AIOps capabilities and make them available to IT operations teams, developers, and business users with varying levels of technical expertise. This trend is driving the development of user-friendly AIOps platforms with intuitive interfaces, pre-built analytics models, and self-service capabilities, enabling users to leverage AI and ML techniques without requiring specialized skills or knowledge.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Segment Outlook | Component, Services, Application, Deployment Mode, Organization Size, Vertical, and Region |
AIOps Platform Market Highlights:
AIOps Platform Market Overview
AIOps Platform Market Size was valued at USD 7.5 Billion in 2022. The AIOps Platform market is projected to grow from USD 8.9 Billion in 2023 to USD 33.8 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 18.20% during the forecast period (2023 - 2032). The growth of image recognition systems and the increasing adoption of cloud platforms by various associations of various industries, are the key market drivers enhancing the market growth.
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AIOps Platform Market Trends
The increasing reception of cloud platforms from different associations of different verticals is driving the market growth
The need for AlOps platforms accelerated due to the growing adoption of cloud platforms by many associations of various industries, such as banking, e-commerce, healthcare, and others, which in turn boosted growth. The AIOps platform combines a variety of artificial intelligence techniques, including automation, machine learning, research, and others. Machine learning technology is now widely employed in a variety of systems that are used in daily life, including recommender systems, image recognition systems, and voice recognition systems. The demand for machine learning has increased as a result of this growing application. Additionally, the development of image recognition systems has improved system accuracy, which will raise need for machine learning in the coming years.
To deliver meaningful insights, cutting-edge machine learning algorithms collect the relevant data that is being processed in the background. For instance, BMC, a market leader in software solutions, introduced numerous new Control-M innovations including BMC Helix in October 2021. These developments allowed businesses to obtain more value-added insights, improve customer service, and boost both resilience and agility. The enterprise is extending data science through this.
Modern technical developments have made it possible for AI to be used in IT operations. To provide better AIOps platforms and services, several businesses are integrating knowledge, Natural Language Processing (NLP), and domain-enriched Machine Learning (ML) techniques. For self-driving automobiles, for instance, a number of factors were simultaneously recognised, examined, and acknowledged in February 2021. Self-driving cars can use deep learning algorithms to help contextualise data collected by its sensors, including movement speed, distance from other objects, and an estimate of where they will be in 5–10 seconds.
The AIOps platform uses intelligent, self-learning algorithms enabled by ML to automate common IT operations. It also recognises and anticipates any prospective events through the use of behavioural and historical data analysis. With the aid of big data analytics, it also offers a cognitive analysis of the data and pulls out pertinent information for further processing. Integrating IT operations with AI enables real-time data correlation, multi-dimensional data normalisation, and severity-based issue prioritising, and developed response strategies to lessen future calamities. Thus, driving the AIOps Platform market revenue.
AIOps Platform Market Segment Insights
AIOps Platform Component Insights
The AIOps Platform Market segmentation, based on component, includes platforms and services. Platforms segment dominated the global market in 2022. AIOps suppliers provide corporate organisations with dependable, adaptable, and cutting-edge platform experiences to give them a competitive edge in the marketplace.
AIOps Platform Services Insights
The AIOps Platform Market segmentation, based on services, includes implementation service, license and maintenance service, training and education service, consulting service, and managed service. Implementation service segment dominated the global market in 2022. Its corporate advantages, including improved decision-making, quicker digital transformation, effective data processing, and integrated agility, should be credited for this significant market share.
AIOps Platform Application Insights
The AIOps Platform Market segmentation, based on application, includes real-time analytics, infrastructure management, network and security management, application performance management, and others. Real-time analytics segment dominated the AIOps Platform Market in 2022. Production quality (vendor quality, data accuracy, and cost overruns), lead times (cycle time, and customer service time), delivery dependability (schedule adherence, and vendor delivery performance), and costs (waste rates, inventory turns, system complexity, and overhead efficiency) are all areas where the manufacturing sector is utilising real-time analytics.
AIOps Platform Deployment Mode Insights
The AIOps Platform Market segmentation, based on deployment mode, includes on-premise and cloud. On-premise segment dominated the global market in 2022. The increased security and privacy offered by on-premise solutions in IT operations is responsible for this high proportion.
AIOps Platform Organization Size Insights
The AIOps Platform Market segmentation, based on organization size, includes SMEs and large enterprises. Large enterprises segment dominated the global market in 2022. Large businesses are implementing AIOps solutions for several sectors, including media & entertainment.
AIOps Platform Vertical Insights
The AIOps Platform Market segmentation, based on vertical, includes BFSI, healthcare and life sciences, retail and consumer goods, telecom and IT, manufacturing, media and entertainment, and others. BFSI segment dominated the global market in 2022. The use of AIOps technology for protecting banking and financial data has increased significantly in this industry. In banking and financial IT operations, AI has a wide range of applications, including real-time analytics, resolving challenging IT problems, automating banking, and boosting scalability, among other use-cases.
Figure 1: AIOps Platform Market, by Vertical, 2022 & 2032 (USD Billion)
Services: Secondary Research, Primary Research, MRFR Database and Analyst Review
AIOps Platform Regional Insights
By region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. The North America AIOps Platform Market dominated this market in 2022 (45.80%). Consumer applications for AI-based investing advice are gaining steam in the US to help investors make better investment choices. This is explained by the region's abundance of AIOps platform suppliers. AIOps platforms are being created by numerous companies, including tech heavyweights and start-ups. Further, the U.S. AIOps Platform market held the largest market share, and the Canada AIOps Platform market was the fastest growing market in the North America region.
Further, the major countries studied in the market report are The US, Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 2: AIOPS PLATFORM MARKET SHARE BY REGION 2022 (USD Billion)
Services: Secondary Research, Primary Research, MRFR Database and Analyst Review
Europe AIOps Platform market accounted for the healthy market share in 2022. Significant factors influencing the adoption of AIOps platforms in the region include the substantial R&D expenditures and ongoing digital transformation in developed nations. Further, the German AIOps Platform market held the largest market share, and the U.K AIOps Platform market was the fastest growing market in the European region
The Asia Pacific AIOps Platform market is expected to register significant growth from 2023 to 2032. This can be attributable to the region's diverse industries quickly adopting automation. Data analytics and other AI-based products and services have also been made possible by the rapid and massive data creation. For instance, in order to promote innovation in the AIOps development process, Micro Focus introduced a brand-new software as a service platform in December 2021. This platform combines SaaS with full-stack AIOps. Moreover, China’s AIOps Platform market held the largest market share, and the Indian AIOps Platform market was the fastest growing market in the Asia-Pacific region.
AIOps Platform Key Market Players & Competitive Insights
Leading market players are investing heavily in research and development in order to expand their product lines, which will help the AIOps Platform market, grow even more. Market participants are also undertaking a variety of strategic activities to expand their global footprint, with important market developments including new product launches, contractual agreements, mergers and acquisitions, higher investments, and collaboration with other organizations. To expand and survive in a more competitive and rising market climate, AIOps Platform industry must offer cost-effective items.
Manufacturing locally to minimize operational costs is one of the key business tactics used by manufacturers in the global AIOps Platform industry to benefit clients and increase the market sector. In recent years, the AIOps Platform industry has offered some of the most significant advantages to medicine. Major players in the AIOps Platform market, including AppDynamics, BMC Software, Inc., Broadcom, HCL Technologies Limited, International Business Machines Corporation, Micro Focus, Moogsoft, Prophet Stor Data Services, Inc., Resolve Systems, and Splunk Inc., are attempting to increase market demand by investing in research and development operations.
Monq Lab is a creator of an AIOps platform that offers straightforward and effective solutions to technology professionals all over the world in order to detect and prevent IT problems in complicated, dynamically changing IT settings. Using a combination of Big Data, ML models, and AI, the company's platform enables businesses to reduce the risks, financial losses, and reputational damage brought on by IT failures and manual IT management. It also identifies areas for improvement and automatically manages infrastructure. To help businesses and SMEs with preventative IT system maintenance, Latvian AIops company Monq Lab published a free version of their incident control and automation platform in February 2022. The solution, officially known as Monq Free Community Edition, is based on a topological database and combines machine learning and robust correlation to detect and address impending IT crises.
The incident management platform created by Moogsoft is intended to assist humans and machines in cooperating to bring order out of chaos. Enterprise ITOps and DevOps teams can learn more quickly, recover more quickly from outages and downtime, and spend less time fixing issues thanks to the company's platform, which automatically identifies performance issues and provides the immediate insight needed to manage problems pro-actively before they spin out of control. One of the market leaders in AIOps solutions that help IT teams work more productively and efficiently, Moogsoft gave DevOps teams and SREs real-time visibility into IT issues in October 2021. This enabled them to identify, analyse, and fix incidents before they had a negative impact on the customer experience.
Key Companies in the AIOps Platform market include
- AppDynamics
- BMC Software, Inc.
- Broadcom
- HCL Technologies Limited
- International Business Machines Corporation
- Micro Focus
- Moogsoft
- Prophet Stor Data Services, Inc.
- Resolve Systems
- Splunk Inc.
AIOps Platform Industry Developments
January 2023: A device management firm called Servify purchased the AI-enabled engagement platform Jubi.ai. After the deal, Servify will include Jubi.ai.
AIOps Platform Market Segmentation
AIOps Platform Component Outlook
- Platforms
- Services
AIOps Platform Services Outlook
- Implementation Service
- License and Maintenance Service
- Training and Education Service
- Consulting Service
- Managed Service
AIOps Platform Application Outlook
- Real-Time Analytics
- Infrastructure Management
- Network and Security Managment
- Application Performance Management
- Others (Cloud monitoring, Anomaly dectection, Log and Event management, and Root cause and App experience analytics)
AIOps Platform Deployment Mode Outlook
- On-premise
- Cloud
AIOps Platform Organization Size Outlook
- SMEs
- Large Enterprises
AIOps Platform Vertical Outlook
- BFSI
- Healthcare and Life Sciences
- Retail and Consumer Goods
- Telecom and IT
- Manufacturing
- Media and Entertainment
- Others (Education, Automotive, Transport and Logistics, Energy and Utilities)
AIOps Platform Regional Outlook
-
North America
- US
- Canada
-
Europe
- Germany
- France
- UK
- Italy
- Spain
- Rest of Europe
-
Asia-Pacific
- China
- Japan
- India
- Australia
- South Korea
- Australia
- Rest of Asia-Pacific
-
Rest of the World
-
Middle East
-
Africa
-
Latin America
-
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