1 エグゼクティブ・サマリー
2 序文
2.1 概要
2.2 ステークホルダー
2.3 調査範囲
2.4 調査方法
2.4.1 データマイニング
2.4.2 データ分析
2.4.3 データの検証
2.4.4 リサーチアプローチ
2.5 リサーチソース
2.5.1 一次調査ソース
2.5.2 セカンダリーリサーチソース
2.5.3 前提条件
3 市場動向分析
3.1 はじめに
3.2 推進要因
3.3 抑制要因
3.4 機会
3.5 脅威
3.6 アプリケーション分析
3.7 エンドユーザー分析
3.8 新興市場
3.9 Covid-19の影響
4 ポーターズファイブフォース分析
4.1 供給者の交渉力
4.2 買い手の交渉力
4.3 代替品の脅威
4.4 新規参入の脅威
4.5 競争上のライバル
5 IT運用人工知能（AIOps）の世界市場、コンポーネント別
5.1 はじめに
5.2 ソリューション
5.2.1 機械学習
5.2.2 自然言語処理（NLP）
5.2.3 データ分析
5.3 サービス
5.3.1 コンサルティング
5.3.2 インプリメンテーション
5.3.3 サポートとメンテナンス
5.4 その他のコンポーネント
6 IT運用人工知能（AIOps）の世界市場：展開タイプ別
6.1 導入
6.2 オンプレミス
6.3 クラウドベース
6.4 その他の展開タイプ
7 IT運用人工知能（AIOps）の世界市場：組織規模別
7.1 はじめに
7.2 中小企業（SMEs）
7.3 大企業
7.4 その他の組織規模
8 IT運用人工知能（AIOps）の世界市場：用途別
8.1 はじめに
8.2 インシデント管理
8.3 パフォーマンス監視
8.4 根本原因分析
8.5 変更管理
8.6 予測分析
8.7 その他のアプリケーション
9 IT運用人工知能（AIOps）の世界市場、エンドユーザー別
9.1 はじめに
9.2 ITおよび通信
9.3 銀行、金融サービス、保険
9.4 ヘルスケア
9.5 小売業
9.6 製造業
9.7 官公庁
9.8 その他のエンドユーザー
10 IT運用人工知能（AIOps）の世界市場：地域別
10.1 はじめに
10.2 北米
10.2.1 アメリカ
10.2.2 カナダ
10.2.3 メキシコ
10.3 ヨーロッパ
10.3.1 ドイツ
10.3.2 イギリス
10.3.3 イタリア
10.3.4 フランス
10.3.5 スペイン
10.3.6 その他のヨーロッパ
10.4 アジア太平洋
10.4.1 日本
10.4.2 中国
10.4.3 インド
10.4.4 オーストラリア
10.4.5 ニュージーランド
10.4.6 韓国
10.4.7 その他のアジア太平洋地域
10.5 南米
10.5.1 アルゼンチン
10.5.2 ブラジル
10.5.3 チリ
10.5.4 その他の南米地域
10.6 中東・アフリカ
10.6.1 サウジアラビア
10.6.2 アラブ首長国連邦
10.6.3 カタール
10.6.4 南アフリカ
10.6.5 その他の中東・アフリカ地域
11 主要開発
11.1 契約、パートナーシップ、提携、合弁事業
11.2 買収と合併
11.3 新製品上市
11.4 事業拡大
11.5 その他の主要戦略
12 会社プロファイル
AppDynamics
DataDog
BigPanda
New Relic
IBM Instana
Moogsoft
Dynatrace
LogicMonitor
Splunk
BMC
PagerDuty
ScienceLogic
Zabbix
Elastic
Cisco
Sumo Logic
Servicenow
Freshservice
CloudHealth and OpsRamp.
表一覧
表1 IT運用人工知能（AIOps）の世界市場展望：地域別（2022-2030年）（MNドル）
表2 IT運用人工知能（AIOps）の世界市場展望：コンポーネント別（2022-2030年） ($MN)
表3 IT運用人工知能（AIOps）の世界市場展望：ソリューション別（2022-2030年） ($MN)
表4 IT運用人工知能（AIOps）の世界市場展望：機械学習別（2022-2030年） ($MN)
表5 IT運用人工知能（AIOps）の世界市場展望：自然言語処理（NLP）別（2022-2030年） ($MN)
表6 IT運用人工知能（AIOps）の世界市場展望：データ分析別（2022-2030年） ($MN)
表7 IT運用人工知能（AIOps）の世界市場展望：サービス別（2022-2030年） ($MN)
表8 IT運用人工知能（AIOps）の世界市場展望：コンサルティング別（2022-2030年） ($MN)
表9 IT運用人工知能（AIOps）の世界市場展望：実装別（2022-2030年） ($MN)
表10 IT運用人工知能（AIOps）の世界市場展望：サポートとメンテナンス別（2022-2030年） ($MN)
表11 IT運用人工知能（AIOps）の世界市場展望：その他のコンポーネント別（2022-2030年） ($MN)
表12 IT運用人工知能（AIOps）の世界市場展望：展開タイプ別（2022-2030年） ($MN)
表13 IT運用人工知能（AIOps）の世界市場展望：オンプレミス別（2022-2030年） ($MN)
表14 IT運用人工知能（AIOps）の世界市場展望：クラウドベース別（2022-2030年） ($MN)
表15 IT運用人工知能（AIOps）の世界市場展望：その他の展開タイプ別（2022-2030年） ($MN)
表16 IT運用人工知能（AIOps）の世界市場展望：組織規模別（2022-2030年） ($MN)
表17 IT運用人工知能（AIOps）の世界市場展望：中小企業（SMEs）別（2022-2030年） ($MN)
表18 IT運用人工知能（AIOps）の世界市場展望：大企業別（2022-2030年） ($MN)
表19 IT運用人工知能（AIOps）の世界市場展望：その他の組織規模別（2022-2030年） ($MN)
表20 IT運用人工知能（AIOps）の世界市場展望：用途別（2022-2030年） ($MN)
表21 IT運用人工知能（AIOps）の世界市場展望：インシデント管理別（2022-2030年） ($MN)
表22 IT運用人工知能（AIOps）の世界市場展望：パフォーマンス監視別（2022-2030年） ($MN)
表23 IT運用人工知能（AIOps）の世界市場展望：根本原因分析別（2022-2030年） ($MN)
表24 IT運用人工知能（AIOps）の世界市場展望：変更管理別（2022-2030年） ($MN)
表25 IT運用人工知能（AIOps）の世界市場展望：予測分析別（2022-2030年） ($MN)
表26 IT運用人工知能（AIOps）の世界市場展望：その他のアプリケーション別（2022-2030年） ($MN)
表27 IT運用人工知能（AIOps）の世界市場展望：エンドユーザー別（2022-2030年） ($MN)
表28 IT運用人工知能（AIOps）の世界市場展望：IT・通信別（2022-2030年） ($MN)
表29 IT運用人工知能（AIOps）の世界市場展望：銀行、金融サービス、保険別（2022-2030年） ($MN)
表30 IT運用人工知能（AIOps）の世界市場展望：ヘルスケア別（2022-2030年） ($MN)
表31 IT運用人工知能（AIOps）の世界市場展望：小売業別（2022-2030年） ($MN)
表32 IT運用人工知能（AIOps）の世界市場展望：製造業別（2022-2030年） ($MN)
表33 IT運用人工知能（AIOps）の世界市場展望：政府別（2022-2030年） ($MN)
表34 IT運用人工知能（AIOps）の世界市場展望：その他のエンドユーザー別（2022-2030年） ($MN)
注）北米、ヨーロッパ、APAC、南米、中東・アフリカ地域の表も上記と同様に表記しています。
Market Dynamics:
Driver:
Growing adoption of cloud computing and hybrid infrastructures
The growing adoption of cloud computing and hybrid infrastructures is because traditional IT management tools struggle to handle this complexity, making AIOps essential. AIOps platforms leverage AI and machine learning to process and analyze data across cloud and on-premises systems in real-time, providing actionable insights, automating tasks, and predicting potential issues. This enhances the performance, scalability, and efficiency of IT operations, driving the demand for AIOps as organizations transition to hybrid and cloud-based infrastructures, fuelling the growth of the market.
Restraint:
Limited understanding and awareness of AIOps benefits
Limited understanding and awareness of AIOps benefits many organizations, particularly small and medium-sized enterprises (SMEs), may not fully grasp how AIOps can enhance IT performance, automate processes, and reduce operational costs. This lack of knowledge creates scepticism and reluctance to invest in AIOps solutions. Additionally, without clear visibility into the long-term ROI, businesses may hesitate to adopt AIOps, leading to missed opportunities for automation, efficiency gains, and competitive advantage. Consequently, market growth is constrained.
Opportunity:
Increased focus on cybersecurity
The cybersecurity threats grow in complexity, traditional security measures struggle to keep pace. AIOps enhances cybersecurity by leveraging AI and machine learning to detect anomalies, predict potential breaches, and automate responses, ensuring faster incident resolution. By analyzing vast amounts of security data in real-time, AIOps helps organizations proactively defend against attacks, improve threat visibility, and strengthen their overall security posture, accelerating the adoption of AIOps solutions.
Threat:
Rapid technological change
Rapid technological change and new algorithms, tools, and platforms are frequently introduced, making it difficult for companies to maintain up-to-date AIOps solutions. Vendors need to invest heavily in R&D to stay competitive, which can be resource-intensive. Additionally, rapid changes may lead to interoperability issues with existing IT systems, increasing the complexity of integration and adoption. These dynamics can also overwhelm smaller vendors and create uncertainty for potential buyers.
Covid-19 Impact
The COVID-19 pandemic accelerated the adoption of AIOps as businesses increasingly relied on digital infrastructures due to remote work and heightened online activity. The surge in IT workloads and complexity drove demand for automated solutions to ensure operational continuity and efficiency. AIOps became essential for managing cloud environments, optimizing system performance, and resolving issues proactively. However, economic uncertainty delayed some investments, particularly in small to mid-sized businesses, creating mixed effects on the market's overall growth trajectory.
The services segment is expected to be the largest during the forecast period
The services segment is estimated to have a lucrative growth, by providing essential support for implementation, integration, and ongoing management of AIOps solutions. Consulting services help organizations assess their needs and design tailored AIOps strategies, ensuring effective deployment. Managed services enhance operational efficiency by offering continuous monitoring, maintenance, and optimization of AIOps platforms. As organizations increasingly seek to maximize the benefits of AIOps, the demand for specialized services drives market growth and adoption.
The government segment is expected to have the highest CAGR during the forecast period
The government segment is anticipated to witness the highest CAGR growth during the forecast period, due to increased adoption AI-driven solutions to enhance efficiency and responsiveness in public services. Governments utilize AIOps for monitoring IT infrastructure, optimizing resource allocation, and improving cybersecurity measures. Additionally, government regulations and funding for AI research and development create a favourable environment for AIOps adoption, leading to increased investments and collaboration with private sector vendors, thereby driving market growth.
Region with largest share:
Asia Pacific is projected to hold the largest market share during the forecast period driven by the increasing adoption of digital transformation initiatives across various industries. Countries like China, India, and Japan are witnessing significant investments in cloud computing, big data, and AI technologies, which enhance IT efficiency and agility. The rising complexity of IT environments and the need for proactive incident management further fuel demand for AIOps solutions. Additionally, government support for AI innovation and smart city initiatives is accelerating market growth, positioning Asia Pacific as a key player in the AIOps landscape.
Region with highest CAGR:
North America is projected to have the highest CAGR over the forecast period, owing to the presence of leading technology companies and extensive IT infrastructure. High adoption rates of cloud computing, big data analytics, and digital transformation initiatives fuel demand for AIOps solutions among enterprises seeking to optimize operations and enhance service delivery. Additionally, increasing cyber threats and regulatory compliance requirements prompt organizations to invest in AIOps for improved security and operational efficiency. The region's focus on innovation and technology integration positions it as a key player in the global AIOps market.
Key players in the market
Some of the key players profiled in the Artificial Intelligence for IT Operations (AIOps) Market include AppDynamics , DataDog, BigPanda, New Relic, IBM Instana, Moogsoft, Dynatrace, LogicMonitor, Splunk, BMC, PagerDuty, ScienceLogic, Zabbix, Elastic, Cisco, Sumo Logic, Servicenow, Freshservice, CloudHealth and OpsRamp.
Key Developments:
In August 2024, Dynatrace partnered with Google Cloud to enhance observability solutions for customers, leveraging Google Cloud’s infrastructure and AI capabilities to improve application performance and user experiences.
In June 2023, DataDog announced a partnership with Snowflake to enhance observability and security for cloud applications. This integration enables users to analyze DataDog data alongside their Snowflake data, providing deeper insights into performance and security.
In March 2023, DataDog introduced Security Monitoring, a new product designed to enhance threat detection and incident response capabilities within its observability platform, enabling organizations to monitor and respond to security threats in real-time.
Components Covered:
• Solutions
• Services
• Other Components
Deployment Types Covered:
• On-Premises
• Cloud-Based
• Other Deployment Types
Organization Sizes Covered:
• Small and Medium-Sized Enterprises (SMEs)
• Large Enterprises
• Other Organization Sizes
Applications Covered:
• Incident Management
• Performance Monitoring
• Root Cause Analysis
• Change Management
• Predictive Analytics
• Other Applications
End Users Covered:
• IT and Telecommunications
• Banking, Financial Services, and Insurance
• Healthcare
• Retail
• Manufacturing
• Government
• 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 2022, 2023, 2024, 2026, and 2030
- 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
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 Application Analysis
3.7 End User Analysis
3.8 Emerging Markets
3.9 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 Artificial Intelligence for IT Operations (AIOps) Market, By Component
5.1 Introduction
5.2 Solutions
5.2.1 Machine Learning
5.2.2 Natural Language Processing (NLP)
5.2.3 Data Analytics
5.3 Services
5.3.1 Consulting
5.3.2 Implementation
5.3.3 Support and Maintenance
5.4 Other Components
6 Global Artificial Intelligence for IT Operations (AIOps) Market, By Deployment Type
6.1 Introduction
6.2 On-Premises
6.3 Cloud-Based
6.4 Other Deployment Types
7 Global Artificial Intelligence for IT Operations (AIOps) Market, By Organization Size
7.1 Introduction
7.2 Small and Medium-Sized Enterprises (SMEs)
7.3 Large Enterprises
7.4 Other Organization Sizes
8 Global Artificial Intelligence for IT Operations (AIOps) Market, By Application
8.1 Introduction
8.2 Incident Management
8.3 Performance Monitoring
8.4 Root Cause Analysis
8.5 Change Management
8.6 Predictive Analytics
8.7 Other Applications
9 Global Artificial Intelligence for IT Operations (AIOps) Market, By End User
9.1 Introduction
9.2 IT and Telecommunications
9.3 Banking, Financial Services, and Insurance
9.4 Healthcare
9.5 Retail
9.6 Manufacturing
9.7 Government
9.8 Other End Users
10 Global Artificial Intelligence for IT Operations (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 AppDynamics
12.2 DataDog
12.3 BigPanda
12.4 New Relic
12.5 IBM Instana
12.6 Moogsoft
12.7 Dynatrace
12.8 LogicMonitor
12.9 Splunk
12.10 BMC
12.11 PagerDuty
12.12 ScienceLogic
12.13 Zabbix
12.14 Elastic
12.15 Cisco
12.16 Sumo Logic
12.17 Servicenow
12.18 Freshservice
12.19 CloudHealth
12.20 OpsRamp
List of Tables
Table 1 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Region (2022-2030) ($MN)
Table 2 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Component (2022-2030) ($MN)
Table 3 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Solutions (2022-2030) ($MN)
Table 4 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Machine Learning (2022-2030) ($MN)
Table 5 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Natural Language Processing (NLP) (2022-2030) ($MN)
Table 6 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Data Analytics (2022-2030) ($MN)
Table 7 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Services (2022-2030) ($MN)
Table 8 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Consulting (2022-2030) ($MN)
Table 9 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Implementation (2022-2030) ($MN)
Table 10 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Support and Maintenance (2022-2030) ($MN)
Table 11 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Other Components (2022-2030) ($MN)
Table 12 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Deployment Type (2022-2030) ($MN)
Table 13 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By On-Premises (2022-2030) ($MN)
Table 14 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Cloud-Based (2022-2030) ($MN)
Table 15 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Other Deployment Types (2022-2030) ($MN)
Table 16 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Organization Size (2022-2030) ($MN)
Table 17 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Small and Medium-Sized Enterprises (SMEs) (2022-2030) ($MN)
Table 18 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Large Enterprises (2022-2030) ($MN)
Table 19 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Other Organization Sizes (2022-2030) ($MN)
Table 20 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Application (2022-2030) ($MN)
Table 21 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Incident Management (2022-2030) ($MN)
Table 22 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Performance Monitoring (2022-2030) ($MN)
Table 23 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Root Cause Analysis (2022-2030) ($MN)
Table 24 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Change Management (2022-2030) ($MN)
Table 25 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Predictive Analytics (2022-2030) ($MN)
Table 26 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Other Applications (2022-2030) ($MN)
Table 27 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By End User (2022-2030) ($MN)
Table 28 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By IT and Telecommunications (2022-2030) ($MN)
Table 29 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Banking, Financial Services, and Insurance (2022-2030) ($MN)
Table 30 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Healthcare (2022-2030) ($MN)
Table 31 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Retail (2022-2030) ($MN)
Table 32 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Manufacturing (2022-2030) ($MN)
Table 33 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Government (2022-2030) ($MN)
Table 34 Global Artificial Intelligence for IT Operations (AIOps) Market Outlook, By Other End Users (2022-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
