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市场调查报告书
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2022-2032 年全球 AIOps 平台市场规模研究（按组件、部署、组织规模、应用、垂直和区域预测）

Global AIOps Platform Market Size Study, by Component, by Deployment, by Organization Size, by Application, by Vertical and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 200 Pages | 商品交期: 2-3个工作天内

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简介目录

2023年全球AIOps平台市场价值约134.4亿美元，预计在2024-2032年预测期内将以超过21.76%的健康成长率成长。 IT 营运人工智慧 (AIOps) 平台利用先进演算法、机器学习和巨量资料分析来自动化和增强 IT 营运。透过仔细分析来自各种 IT 工具和设备的大量营运资料，AIOps 平台有助于问题检测、根本原因分析和主动问题解决。因此，这些平台可以简化 IT 营运、最大限度地减少停机时间并优化服务效能。 IT 基础架构的复杂性不断升级和资料量的快速成长是推动市场成长的关键驱动力。然而，市场面临重大挑战，例如缺乏能够有效实施和管理 AIOps 平台的熟练专业人员，以及阻碍这些平台采用的资料安全和隐私问题。

对高效且经过验证的服务产品的需求凸显了 AIOps 中平台组件的重要性，其中包括资料聚合、分析、机器学习模型和视觉化仪表板的基本工具。随着 IT 环境变得越来越复杂，传统的监控工具难以应付资料的数量、速度和种类，因此需要采用 AIOps 平台。此外，服务组件涵盖咨询、支援、维护和託管服务，在 AIOps 平台的部署、整合和营运中发挥关键作用。

部署环境正在向基于云端的模型发生重大转变，这主要是由于其灵活性、可扩展性和成本效益。基于云端的部署透过将基础设施管理外包给服务提供者来促进远端工作并减少维护要求。相反，本地部署吸引优先考虑资料控制和合规性的组织，提供广泛的客製化潜力和更高的安全性，但代价是大量的前期投资和持续维护。

大型企业通常具有广泛的 IT 基础设施和大量资料产生的特点，他们发现 AIOps 平台对于即时监控、事件管理和 IT 服务自动化不可或缺。中小型企业 (SME) 在面临较低复杂性的同时，也受益于 AIOps 解决方案提供的营运效率和成本降低，这些解决方案旨在具有成本效益、易于实施且需要最少的维护。

在应用方面，AIOps平台越来越多地用于网路和安全管理、应用效能分析、基础设施管理和即时分析。金融、医疗保健和技术等行业优先考虑基础设施管理，而网路和安全管理对于电信、政府和託管 IT 服务供应商至关重要。即时提供可操作情报的能力使得 AIOps 平台对于零售、製造和物流领域的决策具有不可估量的价值。

全球 AIOps 平台市场研究考虑的关键区域包括亚太地区、北美、欧洲、拉丁美洲和世界其他地区。在成熟的 IT 基础设施和大量早期采用人工智慧技术的大型企业的推动下，北美被认为是 AIOps 平台市场的主导地区。此外，严格的监管环境和对数位转型的关注，显示出对确保遵守地区法规和规范的 AIOps 解决方案的强烈需求。然而，由于政府措施的不断增加和 IT 行业的蓬勃发展，预计亚太地区的市场在预测期内将以最快的速度增长，其中中国、日本和印度等国家处于领先地位。

市场的详细细分和细分市场解释如下：

目录

第 1 章：全球 AIOps 平台市场执行摘要

  • 全球AIOps平台市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 按组件
    • 按部署
    • 按组织规模
    • 按申请
    • 按垂直方向
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球 AIOps 平台市场定义与研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包含与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第 3 章：全球 AIOps 平台市场动态

  • 市场驱动因素
    • IT 基础架构的复杂性不断增加
    • 营运数据量不断成长
    • 人工智慧和机器学习的进步
  • 市场挑战
    • 缺乏熟练的专业人员
    • 资料安全和隐私问题
  • 市场机会
    • 逐步采用基于云端的解决方案
    • 与智慧 IT 营运解决方案集成
    • 扩展到新的垂直领域

第 4 章：全球 AIOps 平台市场产业分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的未来方法
    • 波特的 5 力影响分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 最佳制胜策略
  • 颠覆性趋势
  • 产业专家视角
  • 分析师推荐与结论

第 5 章：2022-2032 年全球 AIOps 平台市场规模及组件预测

  • 细分仪表板
  • 全球 AIOps 平台市场：2022 年和 2032 年组件收入趋势分析
    • 平台
    • 服务

第 6 章：2022-2032 年全球 AIOps 平台市场规模与部署预测

  • 细分仪表板
  • 全球 AIOps 平台市场：2022 年和 2032 年部署收入趋势分析
    • 云
    • 本地部署

第 7 章：2022-2032 年全球 AIOps 平台市场规模及组织规模预测

  • 细分仪表板
  • 全球 AIOps 平台市场：2022 年和 2032 年组织规模收入趋势分析
    • 大型企业
    • 中小企业

第 8 章：2022-2032 年全球 AIOps 平台市场规模及应用预测

  • 细分仪表板
  • 全球 AIOps 平台市场：2022 年和 2032 年应用收入趋势分析
    • 应用效能分析
    • 基础设施管理
    • 网路与安全管理
    • 即时分析

第 9 章：2022-2032 年全球 AIOps 平台市场规模及垂直产业预测

  • 细分仪表板
  • 全球 AIOps 平台市场：2022 年和 2032 年垂直收入趋势分析
    • BFSI
    • 能源与公用事业
    • 政府与国防
    • 医疗保健与生命科学
    • 资讯科技与电信
    • 媒体与娱乐
    • 零售与电子商务

第 10 章：2022-2032 年全球 AIOps 平台市场规模及区域预测

  • 北美AIOps平台市场
    • 美国AIOps平台市场
      • 2022-2032 年组件细分尺寸与预测
      • 2022-2032 年部署细分规模与预测
      • 2022-2032 年组织规模细分规模与预测
      • 2022-2032 年应用细分规模与预测
      • 垂直细分规模与预测，2022-2032
    • 加拿大AIOps平台市场
  • 欧洲AIOps平台市场
    • 英国AIOps平台市场
    • 德国AIOps平台市场
    • 法国AIOps平台市场
    • 西班牙AIOps平台市场
    • 义大利AIOps平台市场
    • 欧洲其他地区 AIOps 平台市场
  • 亚太AIOps平台市场
    • 中国AIOps平台市场
    • 印度AIOps平台市场
    • 日本AIOps平台市场
    • 澳洲AIOps平台市场
    • 韩国AIOps平台市场
    • 亚太地区其他 AIOps 平台市场
  • 拉丁美洲AIOps平台市场
    • 巴西AIOps平台市场
    • 墨西哥AIOps平台市场
    • 拉丁美洲其他地区 AIOps 平台市场
  • 中东和非洲 AIOps 平台市场
    • 沙乌地阿拉伯AIOps平台市场
    • 南非AIOps平台市场
    • 中东和非洲其他地区 AIOps 平台市场

第 11 章：竞争情报

  • 重点企业SWOT分析
    • 亚马逊网路服务公司
    • 大猫熊公司
    • BMC 软体公司
  • 顶级市场策略
  • 公司简介
    • Amazon Web Services, Inc.
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • BigPanda, Inc.
    • BMC Software, Inc.
    • Broadcom Inc.
    • Cisco Systems, Inc.
    • CloudFabrix Software Inc.
    • Datadog, Inc.
    • Dynatrace, Inc.
    • Google LLC
    • Hewlett Packard Enterprise Company
    • IBM Corporation
    • Microsoft Corporation
    • New Relic, Inc.
    • ServiceNow, Inc.
    • Tata Consultancy Services Limited

第 12 章：研究过程

  • 研究过程
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

Global AIOps Platform Market is valued at approximately USD 13.44 billion in 2023 and is anticipated to grow with a healthy growth rate of more than 21.76% over the forecast period 2024-2032. An Artificial Intelligence for IT Operations (AIOps) platform leverages advanced algorithms, machine learning, and big data analytics to automate and enhance IT operations. By meticulously analyzing vast volumes of operational data from various IT tools and devices, AIOps platforms facilitate problem detection, root cause analysis, and proactive issue resolution. Consequently, these platforms streamline IT operations, minimize downtime, and optimize service performance. The escalating complexity of IT infrastructure and the burgeoning volume of data are key drivers propelling market growth. However, the market faces significant challenges, such as a scarcity of skilled professionals capable of effectively implementing and managing AIOps platforms, alongside concerns regarding data security and privacy that hinder the adoption of these platforms.

The demand for efficient and proven service offerings has underscored the importance of the platform component within AIOps, which includes essential tools for data aggregation, analysis, machine learning models, and visualization dashboards. As IT environments grow increasingly complex, traditional monitoring tools struggle to cope with the volume, velocity, and variety of data, necessitating the adoption of AIOps platforms. Additionally, the services component, which encompasses consulting, support, maintenance, and managed services, plays a pivotal role in the deployment, integration, and operation of AIOps platforms.

The deployment landscape is witnessing a significant shift towards cloud-based models, primarily due to their flexibility, scalability, and cost-effectiveness. Cloud-based deployments facilitate remote work and reduce maintenance requirements by outsourcing infrastructure management to service providers. Conversely, on-premise deployments appeal to organizations prioritizing data control and compliance, offering extensive customization potential and heightened security at the expense of significant upfront investment and ongoing maintenance.

Large enterprises, typically characterized by extensive IT infrastructures and substantial data generation, find AIOps platforms indispensable for real-time monitoring, incident management, and IT service automation. Small and medium enterprises (SMEs), while facing less complexity, also benefit from the operational efficiency and cost reduction offered by AIOps solutions, which are designed to be cost-effective, easy to implement, and require minimal maintenance.

In terms of application, AIOps platforms are increasingly adopted for network and security management, application performance analysis, infrastructure management, and real-time analytics. Industries such as finance, healthcare, and technology prioritize infrastructure management, while network and security management is crucial for telecommunications, government, and managed IT service providers. The ability to provide actionable intelligence in real-time makes AIOps platforms invaluable for decision-making in retail, manufacturing, and logistics sectors.

The key regions considered for the global AIOps platforms market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America is accounted as the dominating region in the AIOps platform market, driven by mature IT infrastructure and a significant presence of large-scale enterprises that are early adopters of AI technology. Also, presence of stringent regulatory environment and focus on digital transformation, exhibits strong demand for AIOps solutions that ensure compliance with regional regulations and norms. Whereas, the market in Asia Pacific is anticipated to grow at the fastest rate over the forecast period owing to the rising government initiatives and a burgeoning IT sector, with countries like China, Japan, and India at the forefront.

Major market players included in this report are:

  • Amazon Web Services, Inc.
  • BigPanda, Inc.
  • BMC Software, Inc.
  • Broadcom Inc.
  • Cisco Systems, Inc.
  • CloudFabrix Software Inc.
  • Datadog, Inc.
  • Dynatrace, Inc.
  • Google LLC
  • Hewlett Packard Enterprise Company
  • IBM Corporation
  • Microsoft Corporation
  • New Relic, Inc.
  • ServiceNow, Inc.
  • Tata Consultancy Services Limited

The detailed segments and sub-segments of the market are explained below:

By Component:

  • Platform
  • Services

By Deployment:

  • Cloud
  • On-premise

By Organization Size:

  • Large Enterprises
  • Small & Medium Enterprises

By Application:

  • Application Performance Analysis
  • Infrastructure Management
  • Network & Security Management
  • Real-Time Analytics

By Vertical:

  • BFSI
  • Energy & Utilities
  • Government & Defense
  • Healthcare & Life Sciences
  • IT & Telecom
  • Media & Entertainment
  • Retail & eCommerce

By Region:

  • North America
  • U.S.
  • Canada
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • ROE
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • RoAPAC
  • Latin America
  • Brazil
  • Mexico
  • RoLA
  • Middle East & Africa
  • Saudi Arabia
  • South Africa
  • RoMEA

Years considered for the study are as follows:

  • Historical year - 2022
  • Base year - 2023
  • Forecast period - 2024 to 2032

Key Takeaways:

  • Market Estimates & Forecast for 10 years from 2022 to 2032.
  • Annualized revenues and regional level analysis for each market segment.
  • Detailed analysis of geographical landscape with Country level analysis of major regions.
  • Competitive landscape with information on major players in the market.
  • Analysis of key business strategies and recommendations on future market approach.
  • Analysis of competitive structure of the market.
  • Demand side and supply side analysis of the market.

Table of Contents

Chapter 1. Global AIOps Platform Market Executive Summary

  • 1.1. Global AIOps Platform Market Size & Forecast (2022-2032)
  • 1.2. Regional Summary
  • 1.3. Segmental Summary
    • 1.3.1. By Component
    • 1.3.2. By Deployment
    • 1.3.3. By Organization Size
    • 1.3.4. By Application
    • 1.3.5. By Vertical
  • 1.4. Key Trends
  • 1.5. Recession Impact
  • 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global AIOps Platform Market Definition and Research Assumptions

  • 2.1. Research Objective
  • 2.2. Market Definition
  • 2.3. Research Assumptions
    • 2.3.1. Inclusion & Exclusion
    • 2.3.2. Limitations
    • 2.3.3. Supply Side Analysis
      • 2.3.3.1. Availability
      • 2.3.3.2. Infrastructure
      • 2.3.3.3. Regulatory Environment
      • 2.3.3.4. Market Competition
      • 2.3.3.5. Economic Viability (Consumer's Perspective)
    • 2.3.4. Demand Side Analysis
      • 2.3.4.1. Regulatory frameworks
      • 2.3.4.2. Technological Advancements
      • 2.3.4.3. Environmental Considerations
      • 2.3.4.4. Consumer Awareness & Acceptance
  • 2.4. Estimation Methodology
  • 2.5. Years Considered for the Study
  • 2.6. Currency Conversion Rates

Chapter 3. Global AIOps Platform Market Dynamics

  • 3.1. Market Drivers
    • 3.1.1. Increasing Complexity of IT Infrastructure
    • 3.1.2. Growing Volume of Operational Data
    • 3.1.3. Advancements in AI and Machine Learning
  • 3.2. Market Challenges
    • 3.2.1. Lack of Skilled Professionals
    • 3.2.2. Data Security and Privacy Concerns
  • 3.3. Market Opportunities
    • 3.3.1. Progressive Adoption of Cloud-Based Solutions
    • 3.3.2. Integration with Smart IT Operations Solutions
    • 3.3.3. Expansion into New Verticals

Chapter 4. Global AIOps Platform Market Industry Analysis

  • 4.1. Porter's 5 Force Model
    • 4.1.1. Bargaining Power of Suppliers
    • 4.1.2. Bargaining Power of Buyers
    • 4.1.3. Threat of New Entrants
    • 4.1.4. Threat of Substitutes
    • 4.1.5. Competitive Rivalry
    • 4.1.6. Futuristic Approach to Porter's 5 Force Model
    • 4.1.7. Porter's 5 Force Impact Analysis
  • 4.2. PESTEL Analysis
    • 4.2.1. Political
    • 4.2.2. Economical
    • 4.2.3. Social
    • 4.2.4. Technological
    • 4.2.5. Environmental
    • 4.2.6. Legal
  • 4.3. Top investment opportunity
  • 4.4. Top winning strategies
  • 4.5. Disruptive Trends
  • 4.6. Industry Expert Perspective
  • 4.7. Analyst Recommendation & Conclusion

Chapter 5. Global AIOps Platform Market Size & Forecasts by Component 2022-2032

  • 5.1. Segment Dashboard
  • 5.2. Global AIOps Platform Market: Component Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 5.2.1. Platform
    • 5.2.2. Services

Chapter 6. Global AIOps Platform Market Size & Forecasts by Deployment 2022-2032

  • 6.1. Segment Dashboard
  • 6.2. Global AIOps Platform Market: Deployment Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 6.2.1. Cloud
    • 6.2.2. On-premise

Chapter 7. Global AIOps Platform Market Size & Forecasts by Organization Size 2022-2032

  • 7.1. Segment Dashboard
  • 7.2. Global AIOps Platform Market: Organization Size Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 7.2.1. Large Enterprises
    • 7.2.2. Small & Medium Enterprises

Chapter 8. Global AIOps Platform Market Size & Forecasts by Application 2022-2032

  • 8.1. Segment Dashboard
  • 8.2. Global AIOps Platform Market: Application Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 8.2.1. Application Performance Analysis
    • 8.2.2. Infrastructure Management
    • 8.2.3. Network & Security Management
    • 8.2.4. Real-Time Analytics

Chapter 9. Global AIOps Platform Market Size & Forecasts by Vertical 2022-2032

  • 9.1. Segment Dashboard
  • 9.2. Global AIOps Platform Market: Vertical Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 9.2.1. BFSI
    • 9.2.2. Energy & Utilities
    • 9.2.3. Government & Defense
    • 9.2.4. Healthcare & Life Sciences
    • 9.2.5. IT & Telecom
    • 9.2.6. Media & Entertainment
    • 9.2.7. Retail & eCommerce

Chapter 10. Global AIOps Platform Market Size & Forecasts by Region 2022-2032

  • 10.1. North America AIOps Platform Market
    • 10.1.1. U.S. AIOps Platform Market
      • 10.1.1.1. Component breakdown size & forecasts, 2022-2032
      • 10.1.1.2. Deployment breakdown size & forecasts, 2022-2032
      • 10.1.1.3. Organization Size breakdown size & forecasts, 2022-2032
      • 10.1.1.4. Application breakdown size & forecasts, 2022-2032
      • 10.1.1.5. Vertical breakdown size & forecasts, 2022-2032
    • 10.1.2. Canada AIOps Platform Market
  • 10.2. Europe AIOps Platform Market
    • 10.2.1. U.K. AIOps Platform Market
    • 10.2.2. Germany AIOps Platform Market
    • 10.2.3. France AIOps Platform Market
    • 10.2.4. Spain AIOps Platform Market
    • 10.2.5. Italy AIOps Platform Market
    • 10.2.6. Rest of Europe AIOps Platform Market
  • 10.3. Asia-Pacific AIOps Platform Market
    • 10.3.1. China AIOps Platform Market
    • 10.3.2. India AIOps Platform Market
    • 10.3.3. Japan AIOps Platform Market
    • 10.3.4. Australia AIOps Platform Market
    • 10.3.5. South Korea AIOps Platform Market
    • 10.3.6. Rest of Asia Pacific AIOps Platform Market
  • 10.4. Latin America AIOps Platform Market
    • 10.4.1. Brazil AIOps Platform Market
    • 10.4.2. Mexico AIOps Platform Market
    • 10.4.3. Rest of Latin America AIOps Platform Market
  • 10.5. Middle East & Africa AIOps Platform Market
    • 10.5.1. Saudi Arabia AIOps Platform Market
    • 10.5.2. South Africa AIOps Platform Market
    • 10.5.3. Rest of Middle East & Africa AIOps Platform Market

Chapter 11. Competitive Intelligence

  • 11.1. Key Company SWOT Analysis
    • 11.1.1. Amazon Web Services, Inc.
    • 11.1.2. BigPanda, Inc.
    • 11.1.3. BMC Software, Inc.
  • 11.2. Top Market Strategies
  • 11.3. Company Profiles
    • 11.3.1. Amazon Web Services, Inc.
      • 11.3.1.1. Key Information
      • 11.3.1.2. Overview
      • 11.3.1.3. Financial (Subject to Data Availability)
      • 11.3.1.4. Product Summary
      • 11.3.1.5. Market Strategies
    • 11.3.2. BigPanda, Inc.
    • 11.3.3. BMC Software, Inc.
    • 11.3.4. Broadcom Inc.
    • 11.3.5. Cisco Systems, Inc.
    • 11.3.6. CloudFabrix Software Inc.
    • 11.3.7. Datadog, Inc.
    • 11.3.8. Dynatrace, Inc.
    • 11.3.9. Google LLC
    • 11.3.10. Hewlett Packard Enterprise Company
    • 11.3.11. IBM Corporation
    • 11.3.12. Microsoft Corporation
    • 11.3.13. New Relic, Inc.
    • 11.3.14. ServiceNow, Inc.
    • 11.3.15. Tata Consultancy Services Limited

Chapter 12. Research Process

  • 12.1. Research Process
    • 12.1.1. Data Mining
    • 12.1.2. Analysis
    • 12.1.3. Market Estimation
    • 12.1.4. Validation
    • 12.1.5. Publishing
  • 12.2. Research Attributes