Machine Learning Model Operationalization Management (MLOPS) Market Report 2025

This report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.

The machine learning model operationalization management (MLOPS) market size has grown exponentially in recent years. It will grow from $2.65 billion in 2024 to $3.83 billion in 2025 at a compound annual growth rate (CAGR) of 44.8%. The growth in the historic period can be attributed to proliferation of machine learning models, rising complexity of ml models, growing data volumes, increasing demand for automation, rise of cloud computing.

The machine learning model operationalization management (MLOPS) market size is expected to see exponential growth in the next few years. It will grow to $16.74 billion in 2029 at a compound annual growth rate (CAGR) of 44.5%. The growth in the forecast period can be attributed to advancements in model explainability, integration with ai governance, greater adoption of model versioning, focus on cost optimization, increased industry-specific solutions. Major trends in the forecast period include advancements in technology, product innovations, cloud security initiatives, web applications development.

The growth of the machine learning model operationalization management (MLOps) market is anticipated to be fueled by the increasing adoption of artificial intelligence (AI) technology. AI involves the development of computer systems or software capable of performing tasks that typically require human intelligence. MLOps utilizes AI technology to ensure the effective deployment, management, and monitoring of machine learning models in production environments, thereby enhancing the end-to-end lifecycle of machine learning (ML) models. According to a May 2022 report from International Business Machines Corporation (IBM), the global adoption rate of AI has significantly increased to 35%, marking a four-point rise from the previous year. In 2022, it is projected that 13% more firms will have employed AI compared to 2021. With 35% of organizations having already adopted AI, 42% considering AI adoption, and two-thirds of companies (66%) either executing or planning to utilize AI for sustainability goals, the upsurge in AI adoption is identified as a driving force behind the MLOps market's growth.

The proliferation of AI technology is set to propel the expansion of the machine learning model operationalization management (MLOps) market. Artificial intelligence (AI) involves the development of computer systems or software capable of performing tasks traditionally requiring human intelligence. MLOps leverages AI technology to ensure the efficient deployment, management, and monitoring of machine learning models in production environments, contributing to the comprehensive lifecycle enhancement of machine learning (ML) models. As per a May 2022 report by International Business Machines Corporation (IBM), the global adoption rate of AI has notably risen to 35%, marking a four-point increase from the preceding year. Furthermore, 2022 is projected to witness a 13% growth in firms using AI compared to 2021. With 35% of organizations already embracing AI, 42% contemplating AI adoption, and two-thirds of companies (66%) either implementing or planning to leverage AI for sustainability goals, the surge in AI adoption is identified as a pivotal factor propelling the growth of the MLOps market.

In July 2022, DataRobot Inc., a US-based technology company and platform innovator, executed a strategic acquisition by acquiring Algorithmia, Inc., for $6.3 billion. This strategic move aims to augment DataRobot's machine learning operations (MLOps) infrastructure, complementing its robust offerings in DataOps and other segments. The acquisition is strategically positioned to provide enterprises with an end-to-end machine learning production system. Algorithmia Inc., based in the US, specializes in empowering developers to convert algorithms into scalable web services, aligning seamlessly with DataRobot's commitment to advancing machine learning capabilities and operations.

Major companies operating in the machine learning model operationalization management (mlops) market report are Google LLC, Microsoft Corporation, Amazon Web Services Inc., IBM Corporation, Oracle Corporation, SAP SE, Hewlett Packard Enterprise Development LP, SAS Institute Inc., Informatica Corporation, Cloudera Inc., Databricks Inc., TIBCO Software Inc., Alteryx Inc., DataRobot Inc., Dataiku Inc., Domino Data Lab Inc., Neptune Labs, H2O.ai, RapidMiner, Tecton Inc., Data Science Dojo, ModelOp Inc., Aible, Inc., Algorithmia, Inc., KNIME AG.

North America was the largest region in the machine learning model operationalization management (MLOPS) market in 2024. The regions covered in the machine learning model operationalization management (mlops) market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the machine learning model operationalization management (MLOPS) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The machine learning model operationalization management (MLOPS) market consists of revenues earned by entities by providing services such as model development and training, scalability, resource management, data management, model deployment, model serving, and data management. The market value includes the value of related goods sold by the service provider or included within the service offering. The machine learning model operationalization management (MLOPS) market also includes sales of version control, git, bitbucket, orchestration tools, and logging and tracing. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

Machine Learning Model Operationalization Management (MLOps) is the process of preparing and deploying machine learning models in a production environment. This encompasses the integration of machine learning models into business applications, analytical platforms, and other systems to ensure their effective and efficient operation in real-world scenarios. MLOps focuses on streamlining the workflow from model development to deployment, monitoring, and maintenance, ensuring that machine learning models are seamlessly integrated into the operational aspects of a business.

The primary components in Machine Learning Model Operationalization Management (MLOps) are platforms and services. A platform in this context refers to a software environment that offers a set of tools and services to oversee the complete lifecycle of machine learning models. This encompasses both on-premises and cloud deployments, catering to organizations of varying sizes, including large enterprises and small to medium-sized enterprises. End-users of MLOps platforms span across diverse sectors such as banking, financial services, and insurance, retail and e-commerce, government and defense, health and life sciences, manufacturing, telecom, IT and ITeS, energy and utilities, transportation and logistics, and others.

The machine learning model operationalization management (MLOPS) market research report is one of a series of new reports that provides machine learning model operationalization management (MLOPS) market statistics, including machine learning model operationalization management (MLOPS) industry global market size, regional shares, competitors with a machine learning model operationalization management (MLOPS) market share, detailed machine learning model operationalization management (MLOPS) market segments, market trends and opportunities, and any further data you may need to thrive in the machine learning model operationalization management (MLOPS) industry. This machine learning model operationalization management (MLOPS) market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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