Artificial intelligence (AI) and machine learning (ML) technologies are combined with IT operations management in a comprehensive software solution known as an AIOps (Artificial Intelligence for IT Operations) platform. To optimise and simplify IT processes, boost system efficiency, and raise overall corporate productivity, it integrates data analysis, automation, and sophisticated analytics capabilities. The Global AIOPs platform market generated revenue of US$ 7.6 Bn in 2023. The global AIOps Platform market is expected to generate a revenue of US$ 35.24 Bn with a CAGR of 24.5% by 2030.
Global AIOps Platform Market: Covid 19 Impact Analysis
During the Covid 19 period, businesses quickly shifted to remote work settings, the pandemic created severe interruptions to IT operations. IT staff have to adjust to new working practises, dispersed infrastructure management and monitoring, and handling a greater workload. The abrupt change made it difficult to maintain system availability, guarantee data security, and manage performance. Moreover, IT complexity has increased as a result of the abrupt move to remote labour. Home networks, cloud services, and a variety of collaboration tools were among the heterogeneous and dispersed IT infrastructure that organisations had to manage. Due to this complexity, it was difficult for IT staff to have comprehensive visibility, identify problems, and efficiently manage the IT system.
Global AIOps Platform Market: Regional Insights
Figure 1: Global Aiops Platform Market Share (%), By Region, 2023
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On the basis of regional analysis, the Artificial intelligence for IT operation platform market is segmented into North America, Europe, Asia Pacific, Latin America, Middle East, and Africa. North America held the dominant position in the market in 2022 and is projected to retain its dominance throughout the forecast period. The U.S. and Canada are major economies driving the growth of the AIops platform market in this region, owing to the region being an early adopter of advanced technologies such as artificial intelligence, machine learning, big data, and analytics in the region. Moreover, the presence of IT companies such as Google, Microsoft Corporation, IBM, Oracle, and others plays a major role in the growth of the market in the region.
Global AIOps Platform Market- Drivers
Aiops Platform Market Report Coverage
Report Coverage | Details | ||
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Base Year: | 2022 | Market Size in 2023: | US$ 7.6 Bn |
Historical Data for: | 2018 to 2021 | Forecast Period: | 2023 to 2030 |
Forecast Period 2023 to 2030 CAGR: | 24.5% | 2030 Value Projection: | US$ 35.24 Bn |
Geographies covered: |
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Segments covered: |
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Companies covered: |
International Business Machines Corporation, Splunk Inc., CA Technologies, VMware, Inc., Micro Focus International plc., HCL Technologies Limited, AppDynamics, BMC Software, Inc., Moogsoft, and FixStream Network Inc. |
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Growth Drivers: |
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Restraints & Challenges: |
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Global AIops Platform Market- Opportunities
Global AIops Platform Market-Trends
The demand for smart machines and devices
The activities and transactions involved in banking operations are frequently done by clients, employees, and outside organizations. Due to the complexity of these processes, monitoring is crucial. Over the course of the projection period, AIOps provided real-time information and automated problem-solving are anticipated to fuel market growth. Financial institutions are able to resolve complex IT issues, such as performance, capacity, and configuration concerns, thanks to the AIOps platform from C.A. technologies, also known as C.A. Digital Experience Insights.
Because of the numerous high-profile data breaches over the past few years, banks and other financial institutions are particularly concerned with protecting the security of the data they produce.
AIops is being used by many banks and other financial organizations to improve efficiency. For instance, major Indian banks wanted to improve the efficiency of the on boarding of their digital merchants as well as streamline and make transactions easier for their new customers. QualityKiosk's AIops-based analytics solution AnaBot improved merchant onboarding success rates and increased revenue by 7% by better supporting ON-US & OFF-US transactions.
Approximately three-fourths (74%) of financial institutions in the U.S. and the U.K. reported an increase in cybercrime, according to British Aerospace (BAE) Systems Applied Intelligence. Cybercrime can have serious financial repercussions for businesses in addition to known financial losses, including collapsing stock prices, reputational harm, and legal action. AIops can assist in the prosecution of this crime. To protect vulnerable systems, AIops solutions provide round-the-clock monitoring, suspicious activity detection, and defense operation activation.
Additionally, the capabilities put into the service desk systems were improved by the integration of A.I. in operating services across financial institutions. As a result, it offers the supervision and key performance indicators required for top management to spot operational trends before they negatively affect the current goods and processes.
Global AIOps Platform Market- Restraints
Global AIOps Platform Market- Segmentation:
Global AIOps platform market report is segmented into component, organization size, vertical, and region.
On the basis of component, the global AIops platform market is segmented into platforms and services. The platform segment held a dominant position in the AIOps Platform market in 2022 and is projected to retain its dominance throughout the forecast period. The AIops platform encompasses a combination of various Artificial Intelligence such as machine learning, automation, analytics, and others. In today’s world, the high adoption of machine learning technology in various systems such as image recognition systems, voice recognition systems, and recommender systems, which are used in day-to-day activities has accelerated the demand for machine learning. Moreover, the advancement in image recognition systems has led to increased system accuracy, which in turn has propelled the demand for machine learning. For instance, according to Coherent Market Insights' analysis of the image labeling challenge, the accuracy of machine learning was 85% in 2020 and it reached 90% in 2022. The ability of machines to process large volumes of data and to use the data for prediction has made machine learning a key tool in various applications such as BFSI, healthcare, and others. Therefore, the high adoption of machine learning is expected to propel the growth of the AIOps platform market.
Moreover, the exponential growth of data has increased the demand for analytics solutions, which is expected to fuel the growth of the AIops platform market. For instance, according to Coherent Market Insights’ analysis, 97 zeta byte of data is estimated to be generated by IOT technology by 2022.
Global AIOps Platform Market: Key Developments
Global AIOps Platform Market: Key Companies Insights
Small and mid-size company segment is expected to witness significant growth with the highest CAGR during the forecast period. This is owing to the increasing adoption of cloud computing technology and advanced technologies such as machine learning, analytics, and others in the segment. For instance, a business analytics tool is a resource-intensive software or solution, which requires huge data storage capacity provided by cloud platforms. Moreover, cost-effective and rapidly implementing features have increased the demand for cloud-based business analytics solutions by small and mid-sized companies. Such high adoption of cloud-based platforms fuels demand for AIops platforms.
The major players operating in the global AIOps platform market include International Business Machines Corporation, Splunk Inc., CA Technologies, VMware, Inc., Micro Focus International plc., HCL Technologies Limited, AppDynamics, BMC Software, Inc., Moogsoft, and FixStream Network Inc.
Definition: Artificial Intelligence for IT Operations (AIOps) is a multilayered technology platform that enhances IT operations by using machine learning and analytics to analyze the big data collected for various IT operations tools and devices to resolve issues in real-time.
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About Author
Monica Shevgan has 9+ years of experience in market research and business consulting driving client-centric product delivery of the Information and Communication Technology (ICT) team, enhancing client experiences, and shaping business strategy for optimal outcomes. Passionate about client success.
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