According to a new report, published by KBV research, The Global Machine Learning Model Operationalization Management (MLOps) Market size is expected to reach $29.05 billion by 2032, rising at a market growth of 39.3% CAGR during the forecast period.
The core use of MLOps is to operationalize machine learning models in a way that ensures reliability, scalability, and efficiency across their lifecycle. One primary use is the automation of the deployment process, which reduces manual errors, accelerates time-to-market, and enables continuous delivery of updated models. By incorporating continuous integration and continuous deployment (CI/CD) pipelines tailored for ML, organizations can push frequent model updates without disrupting production systems.
The Large Enterprise segment captured the maximum revenue in the Global Machine Learning Model Operationalization Management (MLOps) Market by Organization Size in 2024, thereby, achieving a market value of $20.8 billion by 2032. This strong presence is driven by their significant investments in advanced AI capabilities and the need to manage complex machine learning workflows at scale. Large organizations across sectors such as banking, healthcare, retail, and telecommunications deploy MLOps platforms to streamline model deployment, ensure compliance with regulatory standards, and maintain continuous monitoring and optimization of models in production.
The Platform segment is experiencing a CAGR of 38.8 % during the forecast period. This growth is driven by the increasing demand for comprehensive MLOps platforms that offer end-to-end solutions, including model development, deployment, monitoring, and governance. These platforms help organizations streamline workflows, improve model performance, and accelerate time-to-market. Their ability to integrate with various data sources, development tools, and cloud environments makes them essential for enterprises aiming to scale their AI initiatives effectively.
The Cloud segment led the maximum revenue in the Global Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode in 2024, thereby, achieving a market value of $20.6 billion by 2032. This dominance is largely attributed to the scalability, flexibility, and cost-efficiency offered by cloud-based solutions. Organizations increasingly rely on cloud platforms to deploy, manage, and monitor machine learning models due to the ease of integration with other digital services, real-time data processing capabilities, and reduced infrastructure maintenance.
The BFSI segment is growing at a CAGR of 37.6 % during the forecast period. The rising reliance on machine learning for core financial applications such as fraud detection, credit risk modeling, customer churn prediction, algorithmic trading, and personalized financial services has significantly driven the adoption of MLOps frameworks. Given the high volume of data transactions and the need for stringent regulatory compliance, MLOps tools provide the necessary support for automating model deployment, version control, model monitoring, and auditing processes.
Full Report: https://www.kbvresearch.com/machine-learning-model-operationalization-management-market/
The North America region dominated the Global Machine Learning Model Operationalization Management (MLOps) Market by Region in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of $11.2 billion by 2032. The Europe region is anticipated to grow at a CAGR of 38.8% during (2025 - 2032). Additionally, The Asia Pacific region would witness a CAGR of 40.1% during (2025 - 2032).
By Organization Size
By Component
By Deployment Mode
By Vertical
By Geography
Unique Offerings
