查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1857044

全球人工智慧賦能的DevOps自動化市場：預測至2032年－按組件、部署方式、組織規模、應用、最終用戶和地區進行分析

AI-Powered DevOps Automation Market Forecasts to 2032 - Global Analysis By Component, Deployment Mode, 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個工作天內

價格

根據 Stratistics MRC 的數據，全球 AI 驅動的 DevOps 自動化市場預計到 2025 年將達到 105 億美元，到 2032 年將達到 478 億美元，預測期內複合年成長率為 24.1%。

AI驅動的DevOps自動化平台整合了AI技術，用於自動化和增強軟體開發（Dev）和IT運維（Ops）。 AI演算法能夠分析程式碼、預測系統故障，並自動化測試、配置和事件回應。這可以加快發布週期、提高程式碼品質並最大限度地減少人工操作。隨著企業尋求數位轉型，以加快產品上市速度，並透過智慧自動化和預測分析實現更穩定、更有效率的軟體交付流程，該市場正在蓬勃發展。

據 Linux 基金會稱，75% 的大型企業正在採用 AI 驅動的 DevOps 自動化工具，以更頻繁地部署軟體並將事件解決時間縮短 50%。

對更快軟體交付速度和營運效率的需求

縮短產品上市時間的巨大壓力是推動市場發展的主要動力。為了保持競爭力，企業不得不縮短開發週期並提高應用程式品質。人工智慧驅動的DevOps工具透過自動化複雜的測試、監控和部署流程，最大限度地減少人為錯誤並簡化工作流程，從而直接解決這個問題。這種自動化不僅加快了交付速度，還最佳化了資源利用率，顯著降低了營運成本，並建立了更穩定的生產環境，從而推動了各行業在追求數​​位敏捷性的過程中廣泛採用這些工具。

與舊有系統和工具整合的挑戰

阻礙人工智慧工具普及的一大障礙在於，將新型人工智慧主導工具與現有傳統基礎設施進行複雜的整合。許多組織仍在使用由各種老舊系統拼湊而成的系統，這些系統並非為現代的、API驅動的自動化工作流程而設計。維修這些環境需要大量的客製化和專家資源，這可能會導致營運中斷。這種複雜性增加了部署成本和時間，往往會阻礙或延遲人工智慧工具的普及，尤其是在大型傳統企業中，系統全面改造並非短期內可行的選擇。

拓展至邊緣運算與物聯網應用領域

邊緣運算和物聯網 (IoT) 設備的快速普及帶來了巨大的成長機會。管理大規模分散式邊緣環境本身就十分複雜，需要自動化配置、監控和安全通訊協定。人工智慧驅動的 DevOps 具有獨特的優勢，能夠自動化管理這些分散式系統的生命週期，並確保邊緣的可靠性和效能。除了傳統的資料中心之外，製造業、汽車業和智慧城市等新興垂直領域也正在被探索，為 DevOps 解決方案提供者創造了新的收入來源。

工具氾濫與供應商鎖定風險

市場面臨新的威脅：工具氾濫，各種分散的、小眾的AI工具導致工作流程分散且效率低。此外，依賴單一供應商的專有生態系統可能導致鎖定，降低靈活性並增加長期成本。這種情況使得企業難以更換供應商或整合最佳解決方案，從而削弱了AI驅動的DevOps所承諾的敏捷性和效率優勢。

新冠疫情的影響：

疫情大大推動了人工智慧驅動的DevOps市場的發展。封鎖措施和遠距辦公的興起迫使企業迅速實現營運數位化，並高度依賴雲端基礎服務。這種對強大、擴充性且可遠端管理的軟體交付管道的突如其來的需求，凸顯了自動化的緊迫性。因此，企業優先投資於人工智慧主導的DevOps工具，以確保業務永續營運、加速數位轉型，並在分散式工作環境中維護軟體可靠性，從而在疫情期間及之後推動了市場成長。

預計在預測期內，解決方案板塊將成為最大的板塊。

預計在預測期內，解決方案領域將佔據最大的市場佔有率，因為它涵蓋了為人工智慧提供關鍵功能的核心創收軟體平台。這些整合平台透過自動化持續整合、配置和監控 (CI/CD) 等關鍵 DevOps 階段，提供即時的實際價值。企業正在優先考慮這些綜合解決方案，以建立基礎自動化層。對統一且強大的自動化套件的需求正在鞏固其在該領域的領先地位。

預計在預測期內，雲端基礎的細分市場將以最高的複合年成長率成長。

預計在預測期內，雲端基礎方案將實現最高成長率。這一快速成長得益於其固有的擴充性、較低的前期成本和易於部署等優勢，這些優勢對於採用 DevOps 實踐的企業至關重要。雲端基礎AI-DevOps 工具能夠實現無縫更新，並可輕鬆與其他雲端原生服務整合，使其成為現代敏捷開發環境的理想選擇。此外，隨著企業尋求靈活且便利的自動化解決方案，全球範圍內向雲端優先策略和混合辦公模式的轉變也持續推動著這一領域的擴張。

比最大的地區

預計北美將在預測期內佔據最大的市場佔有率。這一領先地位可歸功於主要技術供應商的強大實力、對新興技術的早期採用以及在銀行、金融服務和保險（BFSI）和通訊等關鍵行業的大規模IT投資。此外，成熟的雲端基礎設施和眾多具有複雜軟體交付需求的企業聚集，為人工智慧驅動的DevOps解決方案創造了肥沃的土壤。該地區對提升營運效率和安全性的高度重視，進一步鞏固了其在全球市場的主導地位。

複合年成長率最高的地區：

預計亞太地區在預測期內將呈現最高的複合年成長率。這項加速成長主要得益於快速的數位轉型、IT和BPO產業的擴張，以及中國、印度和東南亞等新興經濟體雲端運算應用的日益普及。該地區各國政府也積極支持技術現代化，而本地企業則大力投資DevOps以提升其全球競爭力。經濟活力與技術投資的結合，為自動化解決方案創造了高成長環境。

免費客製化服務

訂閱本報告的用戶可從以下免費自訂選項中選擇一項：

  • 公司簡介
    • 對最多三家其他公司進行全面分析
    • 對主要企業進行SWOT分析（最多3家公司）
  • 區域分類
    • 根據客戶興趣對主要國家進行市場估算、預測和複合年成長率分析（註：基於可行性檢查）
  • 競爭基準化分析
    • 基於產品系列、地域覆蓋和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 分析方法
  • 分析材料
    • 原始研究資料
    • 二手研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 市場機遇
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代產品的威脅
  • 新參與企業的威脅
  • 公司間的競爭

第5章 全球人工智慧賦能的DevOps自動化市場（按組件分類）

  • 解決方案
    • 平台
    • 工具/軟體
  • 服務
    • 專業服務
    • 託管服務

第6章 全球人工智慧賦能的DevOps自動化市場（以部署方式分類）

  • 雲端基礎的
  • 本地部署

第7章 全球人工智慧驅動的DevOps自動化市場：依組織規模分類

  • 主要企業
  • 小型企業

第8章 由全球人工智慧驅動的DevOps自動化市場：按應用分類

  • 預測分析、主動主動監測
  • 異常檢測、根本原因分析 (RCA)
  • 自動化測試、品質保證 (QA)
  • 智慧警報管理和事件回應
  • 自動程式碼產生和最佳化
  • 基礎設施最佳化、成本管理（財務營運）
  • 安全自動化（DevSecOps）
  • 發布管理、配置自動化
  • 流程挖掘與最佳化

第9章：全球人工智慧賦能的DevOps自動化市場（按最終用戶分類）

  • 資訊科技/通訊
  • 銀行、金融服務和保險業 (BFSI)
  • 醫學與生命科​​學
  • 零售與電子商務
  • 製造業
  • 媒體與娛樂
  • 政府/公共部門
  • 其他最終用戶

第10章：全球人工智慧賦能的DevOps自動化市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章：主要趨勢

  • 合約、商業夥伴關係和合資企業
  • 企業合併（M&A）
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第12章：公司簡介

  • Microsoft Corporation
  • International Business Machines Corporation
  • Amazon Web Services, Inc.
  • Google LLC
  • ServiceNow, Inc.
  • Dynatrace, Inc.
  • Datadog, Inc.
  • CloudBees, Inc.
  • GitLab Inc.
  • Atlassian Corporation Plc
  • HashiCorp, Inc.
  • Puppet, Inc.
  • Progress Software Corporation
  • Broadcom Inc.
  • Splunk Inc.
  • New Relic, Inc.
  • PagerDuty, Inc.
  • Elastic NV
Product Code: SMRC31909

According to Stratistics MRC, the Global AI-Powered DevOps Automation Market is accounted for $10.5 billion in 2025 and is expected to reach $47.8 billion by 2032 growing at a CAGR of 24.1% during the forecast period. AI-Powered DevOps Automation involves platforms integrating AI to automate and enhance software development (Dev) and IT operations (Ops). AI algorithms analyze code, predict system failures, and automate testing, deployment, and incident response. This accelerates release cycles, improves code quality, and minimizes manual toil. The market is expanding as organizations pursue digital transformation, seeking to achieve faster time-to-market and more stable, efficient software delivery pipelines through intelligent automation and predictive analytics.

According to The Linux Foundation, 75% of large enterprises have adopted AI-powered DevOps automation tools, increasing software deployment frequency and reducing incident resolution time by 50%.

Market Dynamics:

Driver:

Need for faster software delivery and operational efficiency

The relentless pressure to accelerate time-to-market is a primary market catalyst. Businesses are compelled to shorten development cycles and enhance application quality to maintain a competitive edge. AI-powered DevOps tools directly address this by automating complex testing, monitoring, and deployment processes, which minimizes manual errors and streamlines workflows. This automation not only speeds up delivery but also optimizes resource utilization, leading to significant operational cost savings and more stable production environments, thereby fueling widespread adoption across industries seeking digital agility.

Restraint:

Integration challenges with legacy systems and tools

A significant barrier to adoption is the complex integration of new AI-driven tools with established legacy infrastructure. Many organizations operate on a patchwork of older systems that are not designed for modern, API-driven, automated workflows. Retrofitting these environments requires substantial customization, expert resources, and can lead to operational downtime. This complexity increases implementation costs and timelines, often discouraging or delaying adoption, particularly in large, traditional enterprises where a complete system overhaul is not a feasible short-term option.

Opportunity:

Expansion into edge computing and IoT deployments

The rapid proliferation of edge computing and Internet of Things (IoT) devices presents a substantial growth avenue. Managing distributed, large-scale edge environments is inherently complex, requiring automated deployment, monitoring, and security protocols. AI-powered DevOps is uniquely positioned to automate lifecycle management for these decentralized systems, ensuring reliability and performance at the edge. This expansion beyond traditional data centers opens up new verticals like manufacturing, automotive, and smart cities, creating a fresh revenue stream for DevOps solution providers.

Threat:

Tool sprawl and vendor lock-in risks

The market faces the emerging threat of tool sprawl, where an overabundance of disparate, niche AI tools creates fragmented and inefficient workflows. Moreover, reliance on a single vendor's proprietary ecosystem can lead to lock-in, reducing flexibility and increasing long-term costs. This situation makes it difficult for organizations to switch providers or integrate best-of-breed solutions, potentially eroding the very agility and efficiency benefits that AI-powered DevOps promises to deliver, thus posing a strategic risk to market growth and customer satisfaction.

Covid-19 Impact:

The pandemic acted as a significant accelerant for the AI-Powered DevOps market. Lockdowns and the shift to remote work forced enterprises to rapidly digitize operations and rely heavily on cloud-based services. This sudden demand for robust, scalable, and remotely manageable software delivery pipelines highlighted the critical need for automation. Consequently, organizations prioritized investments in AI-driven DevOps tools to ensure business continuity, accelerate digital transformation initiatives, and maintain software reliability in a distributed work environment, boosting market growth during and beyond the crisis.

The solutions segment is expected to be the largest during the forecast period

The solutions segment is expected to account for the largest market share during the forecast period, as it encompasses the core, revenue-generating software platforms that deliver essential AI functionalities. These integrated platforms offer immediate, tangible value by automating key DevOps phases like continuous integration, deployment, and monitoring (CI/CD). Enterprises are prioritizing these comprehensive solutions to build a foundational automation layer, as they provide a more cohesive and manageable environment compared to assembling disparate point tools. This demand for unified, powerful automation suites solidifies the segment's dominant position.

The cloud-based segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud-based segment is predicted to witness the highest growth rate. This surge is driven by its inherent scalability, lower upfront costs, and ease of implementation, which are critical for businesses adopting DevOps practices. Cloud-based AI-DevOps tools facilitate seamless updates and integrate effortlessly with other cloud-native services, making them ideal for modern, agile development environments. Furthermore, the global shift toward cloud-first strategies and hybrid work models continues to propel this segment's expansion as organizations seek flexible and accessible automation solutions.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. This leadership is attributed to the strong presence of major technology vendors, early adoption of advanced technologies, and significant IT investments across key sectors like BFSI and telecom. Moreover, a mature cloud infrastructure and a high concentration of enterprises with complex software delivery needs create a fertile ground for AI-powered DevOps solutions. The region's stringent focus on achieving superior operational efficiency and security further consolidates its dominant position in the global market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. This accelerated growth is fueled by rapid digital transformation, expanding IT and BPO industries, and increasing cloud adoption in emerging economies such as China, India, and Southeast Asia. Governments in the region are also actively supporting technological modernization, while local businesses are investing heavily in DevOps to improve their global competitiveness. This combination of economic dynamism and technological investment creates a high-growth environment for automation solutions.

Key players in the market

Some of the key players in AI-Powered DevOps Automation Market include Microsoft Corporation, International Business Machines Corporation, Amazon Web Services, Inc., Google LLC, ServiceNow, Inc., Dynatrace, Inc., Datadog, Inc., CloudBees, Inc., GitLab Inc., Atlassian Corporation Plc, HashiCorp, Inc., Puppet, Inc., Progress Software Corporation, Broadcom Inc., Splunk Inc., New Relic, Inc., PagerDuty, Inc., and Elastic N.V.

Key Developments:

In June 2025, Datadog, Inc. the monitoring and security platform for cloud applications, today introduced three new AI agents that perform interactive investigations and asynchronous code fixes for development, security and operations teams. Today's launch of the Bits AI SRE, Bits AI Dev Agent and Bits AI Security Analyst agents, alongside the new Proactive App Recommendations and APM Investigator capabilities, marks the continued evolution of Bits AI, Datadog's generative AI assistant that helps engineers resolve application issues in real time.

Components Covered:

  • Solutions
  • Services

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises

Organization Sizes Covered:

  • Large Enterprises
  • Small and Medium-sized Enterprises (SMEs)

Applications Covered:

  • Predictive Analytics & Proactive Monitoring
  • Anomaly Detection & Root Cause Analysis (RCA)
  • Automated Testing & Quality Assurance (QA)
  • Intelligent Alert Management & Incident Response
  • Automated Code Generation & Optimization
  • Infrastructure Optimization & Cost Management (FinOps)
  • Security Automation (DevSecOps)
  • Release Management & Deployment Automation
  • Process Mining & Optimization

End Users Covered:

  • IT & Telecommunications
  • BFSI (Banking, Financial Services, and Insurance)
  • Healthcare & Life Sciences
  • Retail & E-commerce
  • Manufacturing
  • Media & Entertainment
  • Government & Public Sector
  • 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

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 AI-Powered DevOps Automation Market, By Component

  • 5.1 Introduction
  • 5.2 Solutions
    • 5.2.1 Platforms
    • 5.2.2 Tools/Software
  • 5.3 Services
    • 5.3.1 Professional Services
    • 5.3.2 Managed Services

6 Global AI-Powered DevOps Automation Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 Cloud-Based
  • 6.3 On-Premises

7 Global AI-Powered DevOps Automation Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Large Enterprises
  • 7.3 Small and Medium-sized Enterprises (SMEs)

8 Global AI-Powered DevOps Automation Market, By Application

  • 8.1 Introduction
  • 8.2 Predictive Analytics & Proactive Monitoring
  • 8.3 Anomaly Detection & Root Cause Analysis (RCA)
  • 8.4 Automated Testing & Quality Assurance (QA)
  • 8.5 Intelligent Alert Management & Incident Response
  • 8.6 Automated Code Generation & Optimization
  • 8.7 Infrastructure Optimization & Cost Management (FinOps)
  • 8.8 Security Automation (DevSecOps)
  • 8.9 Release Management & Deployment Automation
  • 8.10 Process Mining & Optimization

9 Global AI-Powered DevOps Automation Market, By End User

  • 9.1 Introduction
  • 9.2 IT & Telecommunications
  • 9.3 BFSI (Banking, Financial Services, and Insurance)
  • 9.4 Healthcare & Life Sciences
  • 9.5 Retail & E-commerce
  • 9.6 Manufacturing
  • 9.7 Media & Entertainment
  • 9.8 Government & Public Sector
  • 9.9 Other End Users

10 Global AI-Powered DevOps Automation 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 Microsoft Corporation
  • 12.2 International Business Machines Corporation
  • 12.3 Amazon Web Services, Inc.
  • 12.4 Google LLC
  • 12.5 ServiceNow, Inc.
  • 12.6 Dynatrace, Inc.
  • 12.7 Datadog, Inc.
  • 12.8 CloudBees, Inc.
  • 12.9 GitLab Inc.
  • 12.10 Atlassian Corporation Plc
  • 12.11 HashiCorp, Inc.
  • 12.12 Puppet, Inc.
  • 12.13 Progress Software Corporation
  • 12.14 Broadcom Inc.
  • 12.15 Splunk Inc.
  • 12.16 New Relic, Inc.
  • 12.17 PagerDuty, Inc.
  • 12.18 Elastic N.V.

List of Tables

  • Table 1 Global AI-Powered DevOps Automation Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-Powered DevOps Automation Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI-Powered DevOps Automation Market Outlook, By Solutions (2024-2032) ($MN)
  • Table 4 Global AI-Powered DevOps Automation Market Outlook, By Platforms (2024-2032) ($MN)
  • Table 5 Global AI-Powered DevOps Automation Market Outlook, By Tools/Software (2024-2032) ($MN)
  • Table 6 Global AI-Powered DevOps Automation Market Outlook, By Services (2024-2032) ($MN)
  • Table 7 Global AI-Powered DevOps Automation Market Outlook, By Professional Services (2024-2032) ($MN)
  • Table 8 Global AI-Powered DevOps Automation Market Outlook, By Managed Services (2024-2032) ($MN)
  • Table 9 Global AI-Powered DevOps Automation Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 10 Global AI-Powered DevOps Automation Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 11 Global AI-Powered DevOps Automation Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 12 Global AI-Powered DevOps Automation Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 13 Global AI-Powered DevOps Automation Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 14 Global AI-Powered DevOps Automation Market Outlook, By Small and Medium-sized Enterprises (SMEs) (2024-2032) ($MN)
  • Table 15 Global AI-Powered DevOps Automation Market Outlook, By Application (2024-2032) ($MN)
  • Table 16 Global AI-Powered DevOps Automation Market Outlook, By Predictive Analytics & Proactive Monitoring (2024-2032) ($MN)
  • Table 17 Global AI-Powered DevOps Automation Market Outlook, By Anomaly Detection & Root Cause Analysis (RCA) (2024-2032) ($MN)
  • Table 18 Global AI-Powered DevOps Automation Market Outlook, By Automated Testing & Quality Assurance (QA) (2024-2032) ($MN)
  • Table 19 Global AI-Powered DevOps Automation Market Outlook, By Intelligent Alert Management & Incident Response (2024-2032) ($MN)
  • Table 20 Global AI-Powered DevOps Automation Market Outlook, By Automated Code Generation & Optimization (2024-2032) ($MN)
  • Table 21 Global AI-Powered DevOps Automation Market Outlook, By Infrastructure Optimization & Cost Management (FinOps) (2024-2032) ($MN)
  • Table 22 Global AI-Powered DevOps Automation Market Outlook, By Security Automation (DevSecOps) (2024-2032) ($MN)
  • Table 23 Global AI-Powered DevOps Automation Market Outlook, By Release Management & Deployment Automation (2024-2032) ($MN)
  • Table 24 Global AI-Powered DevOps Automation Market Outlook, By Process Mining & Optimization (2024-2032) ($MN)
  • Table 25 Global AI-Powered DevOps Automation Market Outlook, By End User (2024-2032) ($MN)
  • Table 26 Global AI-Powered DevOps Automation Market Outlook, By IT & Telecommunications (2024-2032) ($MN)
  • Table 27 Global AI-Powered DevOps Automation Market Outlook, By BFSI (Banking, Financial Services, and Insurance) (2024-2032) ($MN)
  • Table 28 Global AI-Powered DevOps Automation Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 29 Global AI-Powered DevOps Automation Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
  • Table 30 Global AI-Powered DevOps Automation Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 31 Global AI-Powered DevOps Automation Market Outlook, By Media & Entertainment (2024-2032) ($MN)
  • Table 32 Global AI-Powered DevOps Automation Market Outlook, By Government & Public Sector (2024-2032) ($MN)
  • Table 33 Global AI-Powered DevOps Automation 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.