New York, June 08, 2023 (GLOBE NEWSWIRE) -- According to MarketResearch.biz, the Generative AI in DevOps Market size is projected to surpass around USD 22,100 Million by 2032, and it is poised to reach a registered CAGR of 38.20% from 2023 to 2032. It was USD 942.5 Million in 2022.
Generative AI is a type of machine learning that uses previously learned examples to create new information, such as text, code, or graphics. DevOps, on the other hand, is a methodology that emphasizes collaboration & communication with IT experts & software developers in order to provide software quickly and reliably. Together, DevOps and generative AI can automate some tasks in the software development process, boosting output and effectiveness. Due to the increased popularity of cloud computing and the expanding desire for automation in the software development process, it is projected that the market for generative AI in DevOps will grow dramatically.
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Key Takeaway
- By component, in 2022, the generative AI in the DevOps market was dominated by the solution segment.
- By deployment mode, the cloud-based deployment mode is the most lucrative in the market.
- By application, generative AI is mostly used in testing data and automating the testing process.
- In 2022, North America dominated the market with the highest revenue share of 40%.
- APAC is anticipated to have the highest CAGR among all the regions.
- APAC is expected to grow at a greater pace owing to the growing adoption of cloud computing and DevOps approach.
Factors affecting the growth of Generative AI in the DevOps industry?
There are several factors that can affect the growth of generative AI in DevOps industry, including:
- Adoption of Cloud Computing: The main factor responsible for the expansion of the industry is the adoption of cloud computing. As more organizations shift their IT infrastructure and operations to the cloud, the demand for AI solutions that can assist in automating various tasks in software development is expected to rise.
- Development and developments in AI and machine learning technologies have made it possible for generative AI solutions to increase in sophistication and efficiency when it comes to automating jobs during the software development process. The need for generative AI solutions in the DevOps sector is anticipated to rise as these technologies continue to advance.
- Adoption of DevOps techniques: As they help teams operate more effectively and cooperatively, DevOps techniques are growing in popularity in the software development industry. Automation of numerous DevOps workflow processes, including testing, deployment, monitoring, and maintenance, can be aided by generative AI technologies. The demand for generative AI solutions is anticipated to rise as more businesses adopt DevOps practices.
- Privacy and Security Issues: The usage of generative AI in DevOps presents privacy and security issues. Organizations need to check that their data & system are secure from any online attack. The adoption of generative AI solutions will be significantly influenced by their capacity to address security and privacy issues.
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Top Trends in Generative AI in DevOps Market
A growing emphasis on tools that can offer insights into how generative AI models are making decisions and producing content is a result of how transparent and explainable generative AI solutions are becoming. Another development is the application of generative AI to cybersecurity, which enables real-time detection and reaction to cyber threats.
Also, there is a slew of brand-new AI platforms and tools that are entering the market. It ranges from open-source software frameworks to cloud-based platforms. These tools make it easier and more efficient for enterprises to create and implement generative AI solutions. Overall, the generative AI in DevOps market is expanding rapidly and innovating, and new trends and advancements are always appearing. In the upcoming years, it is anticipated that the market will continue to expand and change as more firms use cloud computing, DevOps practices, and cutting-edge technologies like generative AI.
Market Growth
The growth of generative AI in DevOps market can be attributed to several factors, including the increasing adoption of cloud computing, the growing need for automation, advancements in AI and machine learning, and increased adoption of DevOps methodologies. Moreover, the COVID-19 pandemic has also accelerated the adoption of digital transformation initiatives, including the adoption of cloud computing & DevOps methodologies, which has further fueled the growth of generative AI in DevOps market.
We can anticipate continued growth and development in this fascinating subject as more companies come to understand the advantages of generative AI solutions in the DevOps market. The availability of trained labour, however, as well as security and privacy issues, may have an impact on the market's expansion.
Regional Analysis
Due to the widespread use of cloud computing and DevOps practices in the region, North America is home to the greatest generative AI in DevOps market. The market share of North America is about 40%. Major businesses like IBM, Microsoft, and Google are all present in this sector which is helping it to expand.
Additionally, Europe is a sizable generative AI in DevOps market, with Germany, UK, and France setting the bar high. The market in Europe is expanding because of the increasing demand for automation in software development and rising cloud computing use.
The APAC market has substantial growth in the upcoming years in the countries such as Japan, China, and India, because of the growing adoption of cloud computing and DevOps approach. Also, this region is home to a significant number of start-ups that make investments in generative AI solutions.
The generative AI in DevOps market is also anticipated to expand in Latin America, the Middle East, and Africa because of the rising popularity of cloud computing and the rising demand for software development automation.
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Scope of the Report
| Report Attribute | Details |
| Market Value (2022) | US$ 942.5 Mn |
| Market Size (2032) | US$ 22,100 Mn |
| CAGR (from 2023 to 2032) | 38.20% |
| North America Revenue Share | 40.00% |
| Historic Period | 2016 to 2022 |
| Base Year | 2022 |
| Forecast Year | 2023 to 2032 |
Market Drivers
One of the main drivers is the increasing popularity of cloud computing. It gives businesses access to powerful computer resources whenever they need them. It also increases the scalability and flexibility of the software development process. The need for automation & efficiency in software development is growing as more businesses migrate to the cloud, also generative AI is viewed as a critical tool for attaining these objectives.
The rising demand for DevOps approaches, which emphasize cooperation and communication between software developers and IT experts, is another motivating reason. DevOps is gaining popularity as a means of accelerating the software development lifecycle and enhancing software product quality. In the DevOps process, processes like code generation and testing may be automated with the use of generative AI, making it a useful tool for DevOps teams.
Market Restraints
The possibility of bias in generative AI models is potential restraint. When generative AI models are trained on biased datasets, the resulting models run the risk of amplifying and perpetuating the bias. This might raise moral and legal concerns and limit the applicability of generative AI solutions in some fields.
Market Opportunities
Integration with other emerging technology: Generative AI can be integrated with other technologies such as IoT (Internet of Things), blockchain, and edge computing to create new applications and uses cases. This integration can help businesses achieve greater efficiency, productivity, and cost savings.
Expansion to new industries: The DevOps market for generative AI has already gained traction across industries like IT and telecom, BFSI, and healthcare. There are many industries that can benefit by adopting generative AI solutions. These include manufacturing, retail, and transportation. Demand for generative AI is expected to rise as businesses in different industries adopt digital-transformation initiatives.
Adoption of hybrid clouds: The adoption of hybrid cloud models that combine public and private cloud architecture is expected to open up new opportunities for generative AI. Hybrid cloud models allow businesses to have more flexibility and control over IT infrastructure while also taking advantage of the scalability, cost-savings, and benefits provided by public cloud providers.
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Report Segmentation
Component Insight
Software platforms and solutions that use generative AI to automate various processes in the software development process are included in the solutions sector. Tools for code development, test data generation, and model training are just a few examples of these solutions. The market for generative AI in DevOps is anticipated to be dominated by the solutions sector, thanks to the growing popularity of cloud computing and DevOps practices. The consulting, integration, and support services pertaining to generative AI products in the DevOps industry are included in the services sector. Providing clients with guidance on the optimal methods for adopting generative AI solutions, integrating generative AI solutions with current processes, and providing ongoing support and maintenance for generative AI solutions are a few examples of the services that may fall under this category.
Deployment Mode Insight
Microsoft Azure, Google Cloud, or AWS are some third-party providers whose cloud infrastructure is maintained by third parties and is known as "cloud-based deployment." Due to it enabling companies to scale their operations effectively and fast without the need for sizable upfront expenditures in IT infrastructure, cloud-based deployment is growing in popularity in the DevOps industry. On-premise deployment means software installation on the firm's own servers. These servers are controlled and maintained by the IT department. Larger businesses that demand tighter control over their software and data frequently employ on-premise implementation.
Application Insight
The applications of generative AI in the DevOps market include testing, deployment, monitoring, maintenance, and other applications. Generative AI is used to produce test data and automate the testing process in software development when testing apps. Because of this, software testing can be done more rapidly and efficiently, which improves both quality and efficiency. Generative AI is used in monitoring apps to track software systems and spot potential problems or anomalies in real-time. This enhances system efficiency and reduces downtime. Generative AI is used in maintenance applications to automate maintenance chores like system updates, patching, and bug patches. This lowers maintenance expenses and increases system reliability.
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Market Segmentation
Based on Component
- Solutions
- Services
Based on Deployment Mode
- On-premise
- Cloud-based
Based on Application
- Testing
- Deployment
- Monitoring
- Maintenance
- Other Applications
Key Regions
- North America
- The US
- Canada
- Mexico
- Western Europe
- Germany
- France
- The UK
- Spain
- Italy
- Portugal
- Ireland
- Austria
- Switzerland
- Benelux
- Nordic
- Rest of Western Europe
- Eastern Europe
- Russia
- Poland
- The Czech Republic
- Greece
- Rest of Eastern Europe
- APAC
- China
- Japan
- South Korea
- India
- Australia & New Zealand
- Indonesia
- Malaysia
- Philippines
- Singapore
- Thailand
- Vietnam
- Rest of APAC
- Latin America
- Brazil
- Colombia
- Chile
- Argentina
- Costa Rica
- Rest of Latin America
- Middle East & Africa
- Algeria
- Egypt
- Israel
- Kuwait
- Nigeria
- Saudi Arabia
- South Africa
- Turkey
- United Arab Emirates
- Rest of MEA
Competitive Landscape
Key participants in the generative AI in DevOps market have been identified based on market share, including IBM, Microsoft, Google, AWS, Intel, Infosys, HCL Technologies, Wipro, Happiest Minds, and Cognizant. To fulfill the rising need for automation and efficiency in software development, these businesses are making research and development investments in the creation of new generative AI solutions and platforms.
Some of the major players include:
- IBM Corporation
- Google LLC
- Microsoft Corporation
- Oracle Corporation
- Amazon Web Services (AWS)
- Puppet
- Chef Software Inc.
- Red Hat Inc.
- Atlassian Corporation Plc
- CloudBees Inc.
- Other Key Players
Recent Development
- In 2021: IBM launched its Cloud Pak for Watson AIOps, which uses generative AI to automate IT operations and improve efficiency in software development.
- Google announced the launch of its Cloud AI Platform Pipelines, which enables users to deploy and manage machine learning workflows using generative AI.
- In 2020: AWS launched its Amazon DevOps Guru, which uses generative AI to identify operational issues and recommend solutions.
- Cognizant launched it's In Catalyst platform, which uses generative AI to automate software development tasks and improve efficiency.
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