Austin, Dec. 03, 2025 (GLOBE NEWSWIRE) -- The MLOps Market size was valued at USD 1.3 Billion in 2023. It is expected to grow to USD 29.6 Billion by 2032 and grow at a CAGR of 41.6% during the forecast period (2024-2032).
The need for MLOps solutions is growing as more people become aware of how revolutionary AI and machine learning can be in boosting operational effectiveness and company creativity.
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Increasing Adoption of Machine Learning and Artificial Intelligence
The growing need for cloud-based MLOps solutions that assist businesses in structuring their machine learning activities. The problem of managing multiple ML models has become particularly pertinent as a result of the increasing use of AI and ML technologies by different businesses. Cloud-based MLOps solutions provide businesses a smooth answer to this issue. First of all, they guarantee the infrastructure's great efficiency and scalability. Thus, enterprises dynamically manage cloud-implemented resources based on the amount of uploaded data, models, and needed computational capacity, reaping significant benefits in workload management. Second, the platforms improve cooperation among data scientists, engineers, and business experts by executing all required tools in the cloud.
Segmentation Analysis:
By Component
The platform segment held the largest market share of over 64% as of 2023. MLOps platforms are offered as comprehensive tools with a variety of integrated services, covering the whole range of tasks necessary to support this life cycle. They help enhance the collaboration of data scientists, engineers, IT departments, and others, ensuring that all of the parties involved experience simplified and more facilitated operations.
By Deployment
The cloud segment held the largest market share around 42% in 2023. Cloud-based solutions are widespread nowadays due to the scalability and flexibility they provide. This is a feature an organization can manage and deploy machine learning solutions without the necessity of having a vast on-the-ground facility.
By End-Use
IT & Telecom segment held the largest market share around 30% in 2023. IT and telecom are dominant in their specific features that make the demand for solutions and products they have very high. Companies operating in the segment have to look for new and more efficient ways of working, seek to cut costs and improve the quality of products and services.
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Regional Insights:
With more than 44% of global revenue in 2023, North America dominated the market. As Al's robust R&D capabilities in developed economies, research centers, and several leading Al companies located in this region. The increased investment in cutting-edge technologies to enhance corporate processes and customer experience is expected to create profitable growth opportunities in North America.
Over the forecast period, Asia Pacific is anticipated to have the greatest CAGR. Cloud computing is rapidly growing in the region, and big companies like Google, Microsoft, and Amazon Web Services, Inc. are extending their presence there. Cloud-based MLOps solutions are expected to become more and more popular in the area as businesses utilize the scalability and flexibility of cloud infrastructure. Furthermore, the APAC region's governments and businesses are investing heavily in AI and machine learning.
Key Players:
- IBM Corporation (IBM Watson Studio)
- GAVS Technologies (MLOps.ai)
- Amazon Web Services, Inc. (Amazon SageMaker)
- Databricks, Inc. (Databricks Unified Analytics Platform)
- DataRobot, Inc. (DataRobot MLOps)
- Microsoft Corporation (Azure Machine Learning)
- Cloudera, Inc. (Cloudera Machine Learning)
- Akira AI (Akira AI Platform)
- Alteryx (Alteryx Designer)
- Google LLC (Google AI Platform)
- H2O.ai (H2O Driverless AI)
- NVIDIA Corporation (NVIDIA Triton Inference Server)
- Tecton (Tecton Feature Store)
- Paperspace (Paperspace Gradient)
- Kubeflow (Kubeflow Pipelines)
- MLflow (MLflow Tracking)
- Seldon Technologies (Seldon Core)
- ClearML (ClearML Platform)
- Weight & Biases (WandB)
- Neptune.ai (Neptune.ai)
MLOps Market Report Scope:
| Report Attributes | Details |
| Market Size in 2023 | USD 1.3 Bilion |
| Market Size by 2032 | USD 29.6 Billion |
| CAGR | CAGR of 41.6% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Component (Platform, Service) • By Deployment Mode (On-Premise, Cloud) • By Organization Size (Large Enterprises, Small and Medium-sized Enterprises) • By End-Use Vertical (IT, Telecom Services, Government, BFSI, Retail, Consumer Goods, Transportation, Others) |
| Customization Scope | Available upon request |
| Pricing | Available upon request |
Recent Developments:
- In April 2023, Canonical Ltd., launched Charmed Kubeflow, its machine learning operations toolkit, on Amazon Web Services Inc.’s cloud marketplace. The new launch is planned for businesses looking to kickstart their ML and AI initiatives.
- In 2023, AWS introduced new features in Amazon SageMaker, including SageMaker Canvas for visual data science and SageMaker Model Registry, enabling better management of machine learning models.
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Exclusive Sections of the Report (The USPs):
- Emerging Technology Adoption Rate – helps you understand how fast enterprises are integrating next-gen MLOps capabilities such as automated model monitoring, feature stores, and CI/CD for ML across key industries.
- Regional Network Infrastructure Expansion – helps you assess which regions are strengthening their data and compute infrastructure, enabling scalable MLOps deployment and cloud-native ML workflows.
- Cybersecurity Incident Index (2020–2023) – helps you identify regions with higher security vulnerabilities, guiding risk assessment for ML model deployment, data governance, and infrastructure protection.
- Cloud Service Utilization Trends – helps you evaluate the shift toward cloud-based MLOps platforms and understand regional differences in the adoption of AWS, Azure, GCP, and hybrid environments.
- Competitive Landscape – helps you gauge the competitive strength of key vendors offering MLOps tools, supported by insights into their market reach, innovation pipelines, and recent technological advancements.
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