The artificial intelligence (AI) devops market size is expected to see exponential growth in the next few years. It will grow to $13.48 billion in 2030 at a compound annual growth rate (CAGR) of 22.0%. The growth in the forecast period can be attributed to increasing demand for AI-powered code optimization, rising adoption of predictive incident detection, growing need for autonomous infrastructure remediation, increasing deployment of AI model operations platforms, and rising demand for intelligent DevOps observability. Major trends in the forecast period include increasing adoption of AI-assisted software development, rising use of predictive analytics for DevOps operations, growing adoption of self-healing software infrastructure, increasing automation of continuous integration and continuous delivery pipelines, and rising use of intelligent software monitoring and incident management.
The increasing adoption of cloud computing across enterprises is expected to drive the growth of the artificial intelligence (AI) DEVOPS market in the coming years. Cloud computing across enterprises refers to the use of shared, scalable, and on-demand computing resources, such as storage, applications, and processing power, delivered over the internet to support business operations across multiple organizations. The increasing adoption of cloud computing across enterprises is attributed to its ability to reduce information technology costs by eliminating the need for large upfront investments in physical infrastructure and lowering ongoing expenses related to maintenance, upgrades, and in-house information technology management. The increasing adoption of cloud computing across enterprises is driving artificial intelligence (AI) DevOps by providing scalable infrastructure, on-demand computing resources, and cloud-native services that enable faster AI model development, deployment, automation, and continuous monitoring. For instance, in January 2026, according to Eurostat, a Luxembourg-based official European Union statistical office, in 2025, 52.74% of EU enterprises used paid cloud computing services, primarily for e-mail, office software, and file storage, showing an increase compared with 2023. Therefore, the increasing adoption of cloud computing across enterprises is driving the growth of the artificial intelligence (AI) DEVOPS market.
Major companies operating in the artificial intelligence (AI) DevOps market are focusing on developing innovative solutions, such as agentic AI-driven automation platforms, to improve infrastructure provisioning, deployment efficiency, and real-time system optimization. Agentic AI-driven automation platforms are systems that use autonomous AI agents to independently plan, execute, and optimize complex workflows, including software deployment, infrastructure management, and operational troubleshooting, with minimal human intervention. For instance, in December 2025, DuploCloud Inc., a US-based AI DevOps automation company, launched AI DevOps engineers designed to perform real infrastructure operations, including provisioning, troubleshooting, and optimization tasks. The platform introduces specialized AI agents for Kubernetes management, observability, compliance, cost optimization, and architecture management, operating through DuploCloud’s orchestration layer that connects AI agents with enterprise DevOps tools and cloud environments. Additionally, the system incorporates an Agentic Help Desk that enables conversational interactions for incident resolution, deployment execution, and ticket triaging while maintaining human oversight and compliance visibility.
In November 2023, Broadcom Inc., a US-based technology company, acquired VMware, Inc. for $61 billion. Through this acquisition, Broadcom aimed to strengthen its infrastructure software portfolio, expand its hybrid and private cloud capabilities, and accelerate its strategy of becoming a leading infrastructure technology company serving enterprise customers worldwide. VMware Inc. is a US-based company that provides a comprehensive suite of AI and DevOps tools.
Major companies operating in the artificial intelligence (AI) devops market are Amazon Web Services Inc., Google LLC, Microsoft Corporation, International Business Machines Corporation, Oracle Corporation, Intel Corporation, Atlassian Corporation, Datadog Inc., Dynatrace Inc., Progress Software Corporation, GitLab Inc., JFrog Ltd., Perforce Software Inc., DataRobot Inc., Harness Inc., CloudBees Inc., Zymr Inc., DBmaestro Ltd., Rootly Inc.
North America was the dominant region in the artificial intelligence (AI) devops market in 2025. Asia-Pacific is expected to be the rapidly growing region in the forecast period. The regions covered in the artificial intelligence (AI) devops market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
The countries covered in the artificial intelligence (AI) devops market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
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Table of Contents
Executive Summary
Artificial Intelligence (AI) DEVOPS Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses artificial intelligence (ai) devops market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for artificial intelligence (ai) devops? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The artificial intelligence (ai) devops market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
- The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
- The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
- The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
- The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
- The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
- Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.
Scope
Markets Covered:
1) By Component: Platform Software; Services2) By Deployment Mode: Cloud-Based; On-Premises; Hybrid Cloud
3) By Organization Size: Small And Medium-Sized Enterprises; Large Enterprises
4) By Application: Artificial Intelligence Model Development; Artificial Intelligence Model Training; Artificial Intelligence Model Deployment; Artificial Intelligence Model Monitoring And Management; Generative Artificial Intelligence Applications
5) By End-Use Industry: Information Technology And Telecommunications; Banking, Financial Services, And Insurance; Healthcare And Life Sciences; Manufacturing; Retail And E-Commerce; Automotive; Government And Defense
Subsegments:
1) By Platform Software: Infrastructure Automation Platforms; Continuous Integration And Continuous Delivery Platforms; Artificial Intelligence Model Operations Platforms; Observability And Monitoring Platforms; Security And Compliance Platforms; Configuration And Orchestration Platforms2) By Services: Consulting Services; Implementation And Integration Services; Managed Services; Training And Support Services; Maintenance And Optimization Services; Artificial Intelligence Model Management Services
Companies Mentioned: Amazon Web Services Inc.; Google LLC; Microsoft Corporation; International Business Machines Corporation; Oracle Corporation; Intel Corporation; Atlassian Corporation; Datadog Inc.; Dynatrace Inc.; Progress Software Corporation; GitLab Inc.; JFrog Ltd.; Perforce Software Inc.; DataRobot Inc.; Harness Inc.; CloudBees Inc.; Zymr Inc.; DBmaestro Ltd.; Rootly Inc.
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain
Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentations: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits
- Bi-Annual Data Update
- Customisation
- Expert Consultant Support
Companies Mentioned
- Amazon Web Services Inc.
- Google LLC
- Microsoft Corporation
- International Business Machines Corporation
- Oracle Corporation
- Intel Corporation
- Atlassian Corporation
- Datadog Inc.
- Dynatrace Inc.
- Progress Software Corporation
- GitLab Inc.
- JFrog Ltd.
- Perforce Software Inc.
- DataRobot Inc.
- Harness Inc.
- CloudBees Inc.
- Zymr Inc.
- DBmaestro Ltd.
- Rootly Inc.

