AIOps Market Forecasts to 2032 – Global Analysis By Component (AIOps Core Platform, Event & Log Analytics Engines, Monitoring & Observability Tools and Other Components), Core Technology Stack, Deployment Model, Organization Size, End User and By Geograph
Description
According to Stratistics MRC, the Global AIOps Market is accounted for $2.27 billion in 2025 and is expected to reach $8.82 billion by 2032 growing at a CAGR of 21.4% during the forecast period. AIOps (Artificial Intelligence for IT Operations) refers to the application of artificial intelligence, machine learning, and advanced analytics to automate and enhance IT operations management. It enables organizations to collect, correlate, and analyze massive volumes of data generated by IT infrastructure, applications, networks, and cloud environments in real time. AIOps platforms proactively detect anomalies, predict incidents, identify root causes, and automate remediation actions, reducing downtime and operational costs. By replacing manual, rule-based monitoring with intelligent insights, AIOps improves system reliability, accelerates incident response, and supports scalable, resilient digital operations across complex hybrid and multi-cloud environments.
According to an IBM survey in 2022, 54% of companies have experienced the advantages of AI implementation across different industries. The adoption of AI helps enhance the performance of IT or network operations (53%), reduce costs with increased efficiency, and improve customer satisfaction (48%).
Market Dynamics:
Driver:
Increasing IT complexity across enterprises
Rising data volumes from multi-cloud, hybrid, and edge environments demand intelligent automation. Enterprises are accelerating investments in AI-driven monitoring to reduce manual intervention and improve service reliability. Distributed workloads and microservices foster operational challenges that require advanced analytics. Real-time anomaly detection boosts efficiency by minimizing downtime and enhancing customer experience. The growing intricacy of IT ecosystems strengthens the role of AIOps as a strategic enabler.
Restraint:
High implementation and integration costs
Substantial investments in infrastructure, skilled personnel, and legacy integration degrade adoption rates. Smaller enterprises face budgetary limitations that hinder deployment of advanced platforms. Continuous model training and pipeline optimization hamper operational efficiency. Extended deployment timelines limit scalability across diverse industries. Financial and technical barriers restrict widespread adoption, particularly in cost-sensitive regions.
Opportunity:
Growth in cloud-native and hybrid environments
Migration of workloads to public and private clouds accelerates the need for intelligent monitoring. Containerized applications and Kubernetes orchestration foster real-time operational insights. Vendors are propelling innovation by offering scalable, cloud-integrated AIOps platforms. Hybrid adoption boosts opportunities for anomaly detection and predictive intelligence. Expanding cloud-native ecosystems strengthen the market outlook for AI-driven operational intelligence.
Threat:
Competition from traditional ITSM tools
Established vendors constrain adoption by embedding automation into existing frameworks. Long-term contracts and entrenched customer bases limit opportunities for new entrants. Incremental AI features in ITSM solutions hinder differentiation of standalone AIOps offerings. Market confusion degrades clarity between ITSM and AIOps capabilities. Persistent competition restricts the pace of AIOps market expansion.
Covid-19 Impact:
Covid-19 impact accelerated digital transformation, boosting reliance on AIOps platforms. Remote work and digital service surges fostered heightened IT workloads. Enterprises accelerated adoption of AI-driven automation to ensure uptime and customer experience. Budget constraints initially hindered deployment in cost-sensitive industries. Over time, resilience needs propelled stronger investments in operational intelligence. The pandemic ultimately strengthened the strategic importance of AIOps in modern IT ecosystems.
The AIOps core platform segment is expected to be the largest during the forecast period
The AIOps core platform segment is expected to account for the largest market share during the forecast period fueled by enterprise demand for centralized visibility. Centralized platforms integrate machine learning, big data, and automation to accelerate operational intelligence. Enterprises prioritize holistic monitoring to foster proactive incident detection and resolution. Vendors are embedding anomaly detection and predictive analytics to boost responsiveness. Rising reliance on unified platforms is strengthening this segment as the backbone of AIOps adoption.
The real-time data processing segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the real-time data processing segment is predicted to witness the highest growth rate due to rising complexity in IT ecosystems. These platforms unify diverse data sources to foster real-time visibility and proactive remediation. Vendors are propelling innovation by embedding advanced analytics and automation features. Large enterprises benefit from scalability that boosts efficiency across distributed workloads. The segment is strengthening its leadership by anchoring enterprise modernization strategies.
Region with largest share:
During the forecast period, the North America region is expected to hold the largest market share by demand for immediate insights, real-time processing is accelerating growth across dynamic IT environments. Stream-processing architectures foster proactive remediation and anomaly detection. IoT devices and 5G networks are propelling adoption of instant operational intelligence. Vendors are investing in AI models optimized for speed to boost responsiveness. Expanding edge computing ecosystems are strengthening this segment’s competitive edge in the market.
Region with highest CAGR:
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR because of rising workloads requiring instant intelligence, enterprises are accelerating investments in real-time analytics. Streamlined architectures foster anomaly detection and proactive resolution. IoT expansion and 5G connectivity are propelling demand for continuous monitoring. Vendors are embedding stream-processing capabilities to boost operational efficiency. Rapid adoption is strengthening this segment as the fastest-growing driver of AIOps adoption.
Key players in the market
Some of the key players in AIOps Market include IBM Corporation, Microsoft Corporation, Cisco Systems, Inc., Broadcom Inc., Splunk Inc., Dynatrace Inc., New Relic, Inc., Moogsoft, Inc., BMC Software, Inc., Hewlett Packard Enterprise Company, Dell Technologies Inc., Elastic N.V., AppDynamics LLC, Resolve Systems, LLC and Sumo Logic, Inc.
Key Developments:
In May 2025, Microsoft and Dynatrace deepened their integration, embedding Dynatrace's observability and application security data directly into the Microsoft Teams and Azure ecosystems for streamlined AIOps workflows. This allows joint customers to surface AI-powered insights and automated actions within their daily collaboration and cloud management tools.
In October 2024, IBM and SAP announced an expanded partnership to integrate IBM's Watsonx AI governance capabilities with SAP's generative AI offerings, including Joule. This collaboration aims to provide clients with enhanced, governed AI-powered automation and insights across their SAP environments, directly feeding into AIOps use cases.
Components Covered:
• AIOps Core Platform
• Event & Log Analytics Engines
• Monitoring & Observability Tools
• Predictive Analytics Engines
• Automation & Remediation Tools
• Other Components
Core Technology Stacks Covered:
• Machine Learning & Deep Learning
• Real-Time Data Processing
• Natural Language Processing
• API & Microservices Framework
• Other Core Technology Stacks
Deployment Models Covered:
• Cloud-Native
• On-Premise
Organization Sizes Covered:
• Small & Medium Enterprises
• Large Enterprises
End Users Covered:
• IT & Telecommunications
• Banking, Financial Services & Insurance
• Healthcare & Life Sciences
• Retail & Consumer Goods
• Manufacturing
• Energy & Utilities
• Other End Users
Regions Covered:
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
According to an IBM survey in 2022, 54% of companies have experienced the advantages of AI implementation across different industries. The adoption of AI helps enhance the performance of IT or network operations (53%), reduce costs with increased efficiency, and improve customer satisfaction (48%).
Market Dynamics:
Driver:
Increasing IT complexity across enterprises
Rising data volumes from multi-cloud, hybrid, and edge environments demand intelligent automation. Enterprises are accelerating investments in AI-driven monitoring to reduce manual intervention and improve service reliability. Distributed workloads and microservices foster operational challenges that require advanced analytics. Real-time anomaly detection boosts efficiency by minimizing downtime and enhancing customer experience. The growing intricacy of IT ecosystems strengthens the role of AIOps as a strategic enabler.
Restraint:
High implementation and integration costs
Substantial investments in infrastructure, skilled personnel, and legacy integration degrade adoption rates. Smaller enterprises face budgetary limitations that hinder deployment of advanced platforms. Continuous model training and pipeline optimization hamper operational efficiency. Extended deployment timelines limit scalability across diverse industries. Financial and technical barriers restrict widespread adoption, particularly in cost-sensitive regions.
Opportunity:
Growth in cloud-native and hybrid environments
Migration of workloads to public and private clouds accelerates the need for intelligent monitoring. Containerized applications and Kubernetes orchestration foster real-time operational insights. Vendors are propelling innovation by offering scalable, cloud-integrated AIOps platforms. Hybrid adoption boosts opportunities for anomaly detection and predictive intelligence. Expanding cloud-native ecosystems strengthen the market outlook for AI-driven operational intelligence.
Threat:
Competition from traditional ITSM tools
Established vendors constrain adoption by embedding automation into existing frameworks. Long-term contracts and entrenched customer bases limit opportunities for new entrants. Incremental AI features in ITSM solutions hinder differentiation of standalone AIOps offerings. Market confusion degrades clarity between ITSM and AIOps capabilities. Persistent competition restricts the pace of AIOps market expansion.
Covid-19 Impact:
Covid-19 impact accelerated digital transformation, boosting reliance on AIOps platforms. Remote work and digital service surges fostered heightened IT workloads. Enterprises accelerated adoption of AI-driven automation to ensure uptime and customer experience. Budget constraints initially hindered deployment in cost-sensitive industries. Over time, resilience needs propelled stronger investments in operational intelligence. The pandemic ultimately strengthened the strategic importance of AIOps in modern IT ecosystems.
The AIOps core platform segment is expected to be the largest during the forecast period
The AIOps core platform segment is expected to account for the largest market share during the forecast period fueled by enterprise demand for centralized visibility. Centralized platforms integrate machine learning, big data, and automation to accelerate operational intelligence. Enterprises prioritize holistic monitoring to foster proactive incident detection and resolution. Vendors are embedding anomaly detection and predictive analytics to boost responsiveness. Rising reliance on unified platforms is strengthening this segment as the backbone of AIOps adoption.
The real-time data processing segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the real-time data processing segment is predicted to witness the highest growth rate due to rising complexity in IT ecosystems. These platforms unify diverse data sources to foster real-time visibility and proactive remediation. Vendors are propelling innovation by embedding advanced analytics and automation features. Large enterprises benefit from scalability that boosts efficiency across distributed workloads. The segment is strengthening its leadership by anchoring enterprise modernization strategies.
Region with largest share:
During the forecast period, the North America region is expected to hold the largest market share by demand for immediate insights, real-time processing is accelerating growth across dynamic IT environments. Stream-processing architectures foster proactive remediation and anomaly detection. IoT devices and 5G networks are propelling adoption of instant operational intelligence. Vendors are investing in AI models optimized for speed to boost responsiveness. Expanding edge computing ecosystems are strengthening this segment’s competitive edge in the market.
Region with highest CAGR:
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR because of rising workloads requiring instant intelligence, enterprises are accelerating investments in real-time analytics. Streamlined architectures foster anomaly detection and proactive resolution. IoT expansion and 5G connectivity are propelling demand for continuous monitoring. Vendors are embedding stream-processing capabilities to boost operational efficiency. Rapid adoption is strengthening this segment as the fastest-growing driver of AIOps adoption.
Key players in the market
Some of the key players in AIOps Market include IBM Corporation, Microsoft Corporation, Cisco Systems, Inc., Broadcom Inc., Splunk Inc., Dynatrace Inc., New Relic, Inc., Moogsoft, Inc., BMC Software, Inc., Hewlett Packard Enterprise Company, Dell Technologies Inc., Elastic N.V., AppDynamics LLC, Resolve Systems, LLC and Sumo Logic, Inc.
Key Developments:
In May 2025, Microsoft and Dynatrace deepened their integration, embedding Dynatrace's observability and application security data directly into the Microsoft Teams and Azure ecosystems for streamlined AIOps workflows. This allows joint customers to surface AI-powered insights and automated actions within their daily collaboration and cloud management tools.
In October 2024, IBM and SAP announced an expanded partnership to integrate IBM's Watsonx AI governance capabilities with SAP's generative AI offerings, including Joule. This collaboration aims to provide clients with enhanced, governed AI-powered automation and insights across their SAP environments, directly feeding into AIOps use cases.
Components Covered:
• AIOps Core Platform
• Event & Log Analytics Engines
• Monitoring & Observability Tools
• Predictive Analytics Engines
• Automation & Remediation Tools
• Other Components
Core Technology Stacks Covered:
• Machine Learning & Deep Learning
• Real-Time Data Processing
• Natural Language Processing
• API & Microservices Framework
• Other Core Technology Stacks
Deployment Models Covered:
• Cloud-Native
• On-Premise
Organization Sizes Covered:
• Small & Medium Enterprises
• Large Enterprises
End Users Covered:
• IT & Telecommunications
• Banking, Financial Services & Insurance
• Healthcare & Life Sciences
• Retail & Consumer Goods
• Manufacturing
• Energy & Utilities
• Other End Users
Regions Covered:
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Table of Contents
200 Pages
- 1 Executive Summary
- 2 Preface
- 2.1 Abstract
- 2.2 Stake Holders
- 2.3 Research Scope
- 2.4 Research Methodology
- 2.4.1 Data Mining
- 2.4.2 Data Analysis
- 2.4.3 Data Validation
- 2.4.4 Research Approach
- 2.5 Research Sources
- 2.5.1 Primary Research Sources
- 2.5.2 Secondary Research Sources
- 2.5.3 Assumptions
- 3 Market Trend Analysis
- 3.1 Introduction
- 3.2 Drivers
- 3.3 Restraints
- 3.4 Opportunities
- 3.5 Threats
- 3.6 End User Analysis
- 3.7 Emerging Markets
- 3.8 Impact of Covid-19
- 4 Porters Five Force Analysis
- 4.1 Bargaining power of suppliers
- 4.2 Bargaining power of buyers
- 4.3 Threat of substitutes
- 4.4 Threat of new entrants
- 4.5 Competitive rivalry
- 5 Global AIOps Market, By Component
- 5.1 Introduction
- 5.2 AIOps Core Platform
- 5.3 Event & Log Analytics Engines
- 5.4 Monitoring & Observability Tools
- 5.5 Predictive Analytics Engines
- 5.6 Automation & Remediation Tools
- 5.7 Other Components
- 6 Global AIOps Market, By Core Technology Stack
- 6.1 Introduction
- 6.2 Machine Learning & Deep Learning
- 6.3 Real-Time Data Processing
- 6.4 Natural Language Processing
- 6.5 API & Microservices Framework
- 6.6 Other Core Technology Stacks
- 7 Global AIOps Market, By Deployment Model
- 7.1 Introduction
- 7.2 Cloud-Native
- 7.3 On-Premise
- 8 Global AIOps Market, By Organization Size
- 8.1 Introduction
- 8.2 Small & Medium Enterprises
- 8.3 Large Enterprises
- 9 Global AIOps Market, By End User
- 9.1 Introduction
- 9.2 IT & Telecommunications
- 9.3 Banking, Financial Services & Insurance
- 9.4 Healthcare & Life Sciences
- 9.5 Retail & Consumer Goods
- 9.6 Manufacturing
- 9.7 Energy & Utilities
- 9.8 Other End Users
- 10 Global AIOps Market, By Geography
- 10.1 Introduction
- 10.2 North America
- 10.2.1 US
- 10.2.2 Canada
- 10.2.3 Mexico
- 10.3 Europe
- 10.3.1 Germany
- 10.3.2 UK
- 10.3.3 Italy
- 10.3.4 France
- 10.3.5 Spain
- 10.3.6 Rest of Europe
- 10.4 Asia Pacific
- 10.4.1 Japan
- 10.4.2 China
- 10.4.3 India
- 10.4.4 Australia
- 10.4.5 New Zealand
- 10.4.6 South Korea
- 10.4.7 Rest of Asia Pacific
- 10.5 South America
- 10.5.1 Argentina
- 10.5.2 Brazil
- 10.5.3 Chile
- 10.5.4 Rest of South America
- 10.6 Middle East & Africa
- 10.6.1 Saudi Arabia
- 10.6.2 UAE
- 10.6.3 Qatar
- 10.6.4 South Africa
- 10.6.5 Rest of Middle East & Africa
- 11 Key Developments
- 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
- 11.2 Acquisitions & Mergers
- 11.3 New Product Launch
- 11.4 Expansions
- 11.5 Other Key Strategies
- 12 Company Profiling
- 12.1 IBM Corporation
- 12.2 Microsoft Corporation
- 12.3 Cisco Systems, Inc.
- 12.4 Broadcom Inc.
- 12.5 Splunk Inc.
- 12.6 Dynatrace Inc.
- 12.7 New Relic, Inc.
- 12.8 Moogsoft, Inc.
- 12.9 BMC Software, Inc.
- 12.10 Hewlett Packard Enterprise Company
- 12.11 Dell Technologies Inc.
- 12.12 Elastic N.V.
- 12.13 AppDynamics LLC
- 12.14 Resolve Systems, LLC
- 12.15 Sumo Logic, Inc.
- List of Tables
- Table 1 Global AIOps Market Outlook, By Region (2024-2032) ($MN)
- Table 2 Global AIOps Market Outlook, By Component (2024-2032) ($MN)
- Table 3 Global AIOps Market Outlook, By AIOps Core Platform (2024-2032) ($MN)
- Table 4 Global AIOps Market Outlook, By Event & Log Analytics Engines (2024-2032) ($MN)
- Table 5 Global AIOps Market Outlook, By Monitoring & Observability Tools (2024-2032) ($MN)
- Table 6 Global AIOps Market Outlook, By Predictive Analytics Engines (2024-2032) ($MN)
- Table 7 Global AIOps Market Outlook, By Automation & Remediation Tools (2024-2032) ($MN)
- Table 8 Global AIOps Market Outlook, By Other Components (2024-2032) ($MN)
- Table 9 Global AIOps Market Outlook, By Core Technology Stack (2024-2032) ($MN)
- Table 10 Global AIOps Market Outlook, By Machine Learning & Deep Learning (2024-2032) ($MN)
- Table 11 Global AIOps Market Outlook, By Real-Time Data Processing (2024-2032) ($MN)
- Table 12 Global AIOps Market Outlook, By Natural Language Processing (2024-2032) ($MN)
- Table 13 Global AIOps Market Outlook, By API & Microservices Framework (2024-2032) ($MN)
- Table 14 Global AIOps Market Outlook, By Other Core Technology Stacks (2024-2032) ($MN)
- Table 15 Global AIOps Market Outlook, By Deployment Model (2024-2032) ($MN)
- Table 16 Global AIOps Market Outlook, By Cloud-Native (2024-2032) ($MN)
- Table 17 Global AIOps Market Outlook, By On-Premise (2024-2032) ($MN)
- Table 18 Global AIOps Market Outlook, By Organization Size (2024-2032) ($MN)
- Table 19 Global AIOps Market Outlook, By Small & Medium Enterprises (2024-2032) ($MN)
- Table 20 Global AIOps Market Outlook, By Large Enterprises (2024-2032) ($MN)
- Table 21 Global AIOps Market Outlook, By End User (2024-2032) ($MN)
- Table 22 Global AIOps Market Outlook, By IT & Telecommunications (2024-2032) ($MN)
- Table 23 Global AIOps Market Outlook, By Banking, Financial Services & Insurance (2024-2032) ($MN)
- Table 24 Global AIOps Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
- Table 25 Global AIOps Market Outlook, By Retail & Consumer Goods (2024-2032) ($MN)
- Table 26 Global AIOps Market Outlook, By Manufacturing (2024-2032) ($MN)
- Table 27 Global AIOps Market Outlook, By Energy & Utilities (2024-2032) ($MN)
- Table 28 Global AIOps Market Outlook, By Other End Users (2024-2032) ($MN)
- Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
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