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市场调查报告书
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1577259

到 2030 年 AIOps（IT 营运人工智慧）市场预测：按组件、部署类型、组织规模、应用程式、最终用户和区域进行的全球分析

Artificial Intelligence for IT Operations (AIOps) Market Forecasts to 2030 - Global Analysis By Component (Solutions, Services and Other Components), Deployment Type, Organization Size, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 预测，2024 年全球 AIOps（IT 营运人工智慧）市场规模将达到 49.9 亿美元，预测期内复合年增长率为 29%，预计到 2030 年将达到 230 亿美元。

IT 营运人工智慧 (AIOps) 是指使用人工智慧、机器学习和巨量资料分析来增强和自动化 IT 营运。 AIOps 平台支援即时资料分析、事件关联、异常侦测和自动事件回应。 AIOps 收集和分析大量 IT资料，以优化系统效能，在问题发生之前进行预测和解决，同时最大限度地减少日益复杂的 IT 环境中的手动干预，减少停机时间并提高营运效率。

越来越多采用云端处理和混合

由于传统 IT 管理工具无法处理这种复杂性，云端处理和混合基础架构的采用正在不断增长，因此 AIOps 至关重要。 AIOps 平台利用人工智慧和机器学习来即时处理和分析云端和本地系统中的资料，以提供可操作的见解、自动化任务并预测潜在问题。这提高了 IT 营运的效能、可扩展性和效率，随着组织转向混合和云端基础的基础设施，增加了对 AIOps 的需求，从而推动市场成长。

对 AIOps 优势的理解与认知不足

对 AIOps 的好处的理解和认识有限 许多组织，尤其是中小型企业 (SME)，对 AIOps 如何提高 IT 效能、自动化流程和降低营运成本缺乏充分的了解。这种知识的缺乏导致了人们对 AIOps 解决方案的怀疑和不愿意投资。此外，如果没有清晰的长期投资报酬率，公司就会犹豫是否要采用 AIOps，并错过自动化、效率和竞争优势的机会。因此，市场成长受到限制。

人们越来越关注网路安全

网路安全威胁变得更加复杂，传统的安全措施已不足以应对。 AIOps 利用人工智慧和机器学习来侦测异常、预测潜在违规并自动回应，以提高网路安全并加快事件解决速度。 AIOps 透过即时分析大量安全资料，帮助企业主动防御攻击、提高威胁可见度并增强整体安全态势。

快速的技术创新

快速的技术创新以及新演算法、工具和平台的频繁引入使得企业很难保持 AIOps 解决方案的最新状态。供应商必须在研发方面投入大量资金才能保持竞争力，而这可能会占用大量资源。此外，快速变化可能会导致与现有 IT 系统的互通性问题，并增加整合和部署的复杂性。这种动态也会让小型供应商不知所措，并给潜在买家带来不确定性。

COVID-19 的影响

由于远距工作和线上活动活性化，企业增加了对数位基础设施的依赖，COVID-19 大流行加速了 AIOps 的采用。 IT 工作负载的激增和复杂性增加了对自动化解决方案的需求，以确保营运连续性和效率。 AIOps 已成为管理云端环境、最佳化系统效能和主动解决问题的关键。然而，由于经济前景的不确定性，一些投资尤其是中小企业的投资被推迟，这对整体市场的成长轨迹产生了不同程度的影响。

在预测期内，服务业预计将是最大的。

透过为 AIOps 解决方案的实施、整合和持续管理提供必要的支持，服务业预计将出现良好的成长。咨询服务可协助企业评估其需求并设计适合其需求的 AIOps 策略，确保有效部署。託管服务透过对 AIOps 平台进行持续监控、维护和最佳化来提高营运效率。随着组织越来越多地寻求最大限度地发挥 AIOps 的优势，对专业服务的需求正在推动市场的成长和采用。

政府部门预计在预测期内复合年增长率最高

由于越来越多地采用人工智慧驱动的解决方案来提高公共服务的效率和响应能力，预计政府部门在预测期内将以最高的复合年增长率成长。政府正在使用 AIOps 来监控IT基础设施、优化资源分配并改善网路安全措施。此外，政府法规和人工智慧研发资金为 AIOps 的采用创造了有利的环境，导致投资增加以及与私人供应商的合作，推动市场成长。

比最大的地区

由于各行业越来越多地采用数位转型倡议，预计亚太地区在预测期内将占据最大的市场占有率。中国、印度和日本等国家正在对云端运算、巨量资料和人工智慧技术进行大量投资，使其IT更有效率和敏捷。 IT 环境日益复杂以及主动事件管理的需求进一步推动了对 AIOps 解决方案的需求。此外，政府对人工智慧创新和智慧城市计画的支持正在加速市场成长，使亚太地区成为人工智慧营运领域的关键参与者。

复合年增长率最高的地区：

由于大型科技公司和广泛的IT基础设施的存在，预计北美在预测期内将出现最高的复合年增长率。云端处理、巨量资料分析和数位转型倡议的高采用率正在推动寻求优化营运和增强服务交付的企业对 AIOps 解决方案的需求。此外，不断增加的网路威胁和监管合规要求正在推动企业投资 AIOps，以提高安全性和营运效率。该地区对创新和技术整合的关注使其成为全球 AIOps 市场的关键参与者。

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目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 研究资讯来源
    • 主要研究资讯来源
    • 二次研究资讯来源
    • 先决条件

第三章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19 的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第五章 AIOps（IT 营运人工智慧）的全球市场：按组成部分

  • 解决方案
    • 机器学习
    • 自然语言处理（NLP）
    • 资料分析
  • 服务
    • 咨询
    • 执行
    • 支援与维护
  • 其他组件

第 6 章 AIOps（IT 营运人工智慧）的全球市场：按部署类型

  • 本地
  • 云端基础
  • 其他部署类型

第七章 AIOps（IT 营运人工智慧）的全球市场：依组织规模

  • 小型企业
  • 大公司
  • 其他组织规模

第八章 AIOps（IT 营运人工智慧）的全球市场：按应用分类

  • 事件管理
  • 绩效监控
  • 根本原因分析
  • 变革管理
  • 预测分析
  • 其他用途

第 9 章 AIOps（IT 营运人工智慧）全球市场：按最终用户分类

  • 资讯科技和通讯
  • 银行、金融服务和保险
  • 卫生保健
  • 零售
  • 製造业
  • 政府
  • 其他最终用户

第十章 AIOps（IT 营运人工智慧）的全球市场：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东/非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲

第十一章 主要进展

  • 合约、伙伴关係、合作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十二章 公司概况

  • AppDynamics
  • DataDog
  • BigPanda
  • New Relic
  • IBM Instana
  • Moogsoft
  • Dynatrace
  • LogicMonitor
  • Splunk
  • BMC
  • PagerDuty
  • ScienceLogic
  • Zabbix
  • Elastic
  • Cisco
  • Sumo Logic
  • Servicenow
  • Freshservice
  • CloudHealth
  • OpsRamp
Product Code: SMRC27579

According to Stratistics MRC, the Global Artificial Intelligence for IT Operations (AIOPS) Market is accounted for $4.99 billion in 2024 and is expected to reach $23.00 billion by 2030 growing at a CAGR of 29% during the forecast period. Artificial Intelligence for IT Operations (AIOps) refers to the use of artificial intelligence, machine learning, and big data analytics to enhance and automate IT operations. AIOps platforms enable real-time data analysis, event correlation, anomaly detection, and automated incident response. By collecting and analyzing vast amounts of IT data, AIOps helps organizations optimize system performance, predict and resolve issues proactively, reduce downtime, and improve operational efficiency, all while minimizing manual intervention in increasingly complex IT environments.

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

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

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.