Dublin, March 28, 2023 (GLOBE NEWSWIRE) -- The "MLOps Market By Component, By Deployment Mode, By Organization Size, By Industrial Vertical: Global Opportunity Analysis and Industry Forecast, 2021-2031" report has been added to ResearchAndMarkets.com's offering.
The MLOps market was valued at $983.64 million in 2021, and is estimated to reach $23.1 billion by 2031, growing at a CAGR of 37.5% from 2022 to 2031.
The MLOps Market is likely to experience a significant growth rate of 37.5% from 2022-2031, owing to increasing market demand from IT and telecom sector.
MLOps is the combination of machine learning and operations. It encompasses both data science and software operations. At the same time, operations encompasses all the activities involved in running applications, such as setting up servers, implementing infrastructure, and managing application performance. The goal of MLOps is to provide companies with a means to rapidly deploy machine learning models into their production environments while ensuring that can continuously improve these models over time.
On the contrary, the machine learning models in decision-making becomes more prevalent, it is increasingly important to ensure they are deployed responsibly. There are a lot of causes of algorithmic bias that need to be avoided when decisions are automated through AI systems.
Failure to successfully minimize bias can lead to punishment through government regulation or loss of demand and profits for a brand. To responsibly deploy AI systems, models must be trained on compliant and unbiased data sources, have interpretable and explainable results, and accountability throughout the organization where it is easy to find where in the development pipeline something potentially went wrong to fix it effectively.
To deploy AI models responsibly, organizations require a streamlined ML model life cycle. Deploying more and more models requires MLOps to be successful. It is necessary to have a streamlined process to keep track of versioning, to understand model performance versus retrained model performance, and to ensure that a model continues to perform well over time. Without these MLOps, it is very difficult to successfully add value and business impact with these models.
Factors such as increase in investments in AI/ML based systems and rise of data-centric approach to MLOps, drives the growth of the market.
In addition, increase in the number of libraries and packages for MLOps tasks, strengthening the growth of the market for future. However, inaccessible data and data security, rigid business models, lack of talent and time-consuming implementation, hamper the growth of the market. Furthermore, rapid changes in business model software due to geographical expansion of the businesses is expected to provide the lucrative growth opportunities for the market during the forecast period.
The market players operating in the MLOps market are Akira AI, Alteryx, Amazon Web Services, Inc., Cloudera, Inc., Databricks, Inc., DataRobot, Inc., GAVS Technologies, Google LLC, IBM Corporation and Microsoft Corporation.
The players in the market have been actively engaged in the adoption various Strategies such as partnership, product launch, collaboration, and acquisition to remain competitive and gain advantage over the competitors in the market.
Key Market Insights
By component, the platform segment was the highest revenue contributor to the market in 2021, and is estimated to reach $14,660.35 million by 2031, with a CAGR of 36%. However, the services segment is estimated to be the fastest growing segment with the CAGR of 39.6% during the forecast period.
By deployment mode, the on-premise segment dominated the global market share in 2021, and is estimated to reach $11,438.48 million by 2031, with a CAGR of 36.1%, However, the cloud segment is expected to be the fastest growing segment of market during the forecast period.
Based on organization size, the large enterprises segment was the highest revenue contributor to the market, with $6,38.1million in 2021, and is estimated to reach $13,697.77 million by 2031, with a CAGR of 36.2%.
Based on industry vertical, the IT and telecom sector was the highest revenue contributor to the market, with $229.41 million in 2021, and is estimated to reach $3,724.82 million by 2031, with a CAGR of 32.4%.
Region wise, North America was the highest revenue contributor, accounting for $3,57.16 million in 2021, and is estimated to reach $7,309.07 million by 2031, with a CAGR of 35.6%.
Market Dynamics
Drivers
- Increase in investments in AI/ML based systems.
- Increase in the number of libraries and packages for MLOps tasks.
- Rise of data-centric approach to MLOps
Restraints
- Inaccessible data and data security.
- Rigid business models.
- Lack of talent
- Time-consuming implementation
Opportunities
- Rapid changes in business model software due to geographical expansion of the businesses
Key Market Players
- Akira AI
- Amazon Web Services, Inc.
- Cloudera, Inc.
- DataRobot, Inc.
- Google LLC
- IBM Corporation
- Databricks, Inc.
- GAVS Technologies
- Microsoft Corporation
- Alteryx
Key Market Segments
By Component
- Platform
- Service
By Deployment Mode
- On Premise
- Cloud
By Organization Size
- Large Enterprises
- Small and Medium-sized Enterprises
By Industrial Vertical
- BFSI
- Manufacturing
- IT and Telecom
- Retail and E-commerce
- Energy and Utility
- Healthcare
- Media and Entertainment
By Region
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- France
- Italy
- Spain
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- Australia
- South Korea
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
For more information about this report visit https://www.researchandmarkets.com/r/dn3ptk
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