The global MLOps market size reached US$ 1.52 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 13.11 Billion by 2028, exhibiting a growth rate (CAGR) of 43.06% during 2023-2028. The increasing adoption of AI and ML technologies, the rising need for streamlined and efficient ML workflows, and the growing focus on model performance, reliability, and governance are some of the major factors propelling the market.
|MLOps Market Size in 2022
||US$ 1.52 Billion
|MLOps Market Forecast in 2028
||US$ 13.11 Billion
|MLOps Market Growth Rate (2023-2028)
MLOps (machine learning operations) is a comprehensive approach that combines machine learning (ML) with operations and software engineering practices to manage and streamline the entire lifecycle of ML models effectively. It encompasses processes, tools, and methodologies aimed at efficiently deploying, monitoring, and maintaining ML models in production environments. MLOps enables organizations to bridge the gap between data science and operations, ensuring smooth collaboration, reproducibility, scalability, and reliability of ML workflows. It is widely employed by various businesses to optimize model performance, enhance decision-making, and drive successful artificial intelligence (AI) initiatives.
The global MLOps market is primarily driven by the increasing adoption of AI and ML technologies across industries. MLOps provides the necessary frameworks, tools, and practices to effectively manage ML models, ensuring their seamless integration into business processes. Moreover, the rising need for streamlined and efficient ML workflows is propelling the market growth. In addition to this, the widespread product utilization to facilitate collaboration, automation, and standardization of these workflows, improving productivity, reducing development time, and ensuring reproducibility and scalability are presenting remunerative growth opportunities for the market. Furthermore, the rising focus on model performance, reliability, and governance is impelling the adoption of MLOps as ML models are essential for critical decision-making processes, acting as another major growth-inducing factor.
MLOps Market Trends/Drivers:
Increasing adoption of AI and ML technologies
The expanding adoption of AI and ML technologies across organizations to improve decision-making processes and optimize operations is a major driver fueling the growth of the global MLOps market. In line with this, MLOps provide frameworks, tools, and best practices to streamline the entire ML lifecycle, from data preprocessing and model development to deployment, monitoring, and maintenance, which, in turn, is aiding in market expansion. Furthermore, the expanding product employment to ensure the seamless operationalization of ML models is contributing to the market growth.
Expanding focus on model performance, reliability, and governance
Model performance, reliability, and governance are crucial concerns for organizations deploying ML models in production environments. As ML models play an increasingly significant role in critical decision-making processes, organizations need to ensure their performance, accuracy, and reliability over time. As a result, various businesses are employing MLOps to address these concerns by providing monitoring and management capabilities for ML models in real-world scenarios. In addition to this, MLOps enables organizations to continuously monitor model performance, detect anomalies, and initiate necessary actions for optimization, thus propelling its adoption across numerous industrial verticals. Moreover, the rising product employment to facilitate governance and compliance by providing audit trails, explainability features, and transparency in model predictions is contributing to the market growth.
Significant technological advancements
Ongoing advancements in technology have led to the introduction of new capabilities, tools, and solutions that enhance the effectiveness and efficiency of MLOps practices. This represents a significant factor fueling the market growth. Concurrent with this, the development of advanced ML algorithms and models and significant innovations in neural networks, natural language processing (NLP), and deep learning that enable organizations to develop more powerful and accurate ML models are strengthening the market growth. Moreover, advancements in cloud computing and infrastructure have influenced the market of MLOps as cloud platforms offer scalable and flexible computing resources that are essential for handling large-scale ML workloads.
MLOps Industry Segmentation:
IMARC Group provides an analysis of the key trends in each segment of the global MLOps market report, along with forecasts at the global, regional, and country levels from 2023-2028. Our report has categorized the market based on component, deployment mode, organization size, and vertical.
Breakup by Component:
Platforms dominate the market
The report has provided a detailed breakup and analysis of the market based on the component. This includes platform and services. According to the report, platform represented the largest segment.
The burgeoning demand for MLOps platforms and services is driven by the exponential growth of data and the increasing complexity of ML models. In addition to this, the expanding product utilization to provide a centralized and integrated environment, enabling seamless collaboration among data scientists, engineers, and operations teams, escalating the development lifecycle, and ensuring model reliability is strengthening the market growth. Moreover, with the introduction of stringent regulatory compliance and governance in the field of AI, there is an expanding adoption of MLOps solutions that offer model versioning, auditing, and explainability features, which, in turn, is presenting remunerative growth opportunities.
Breakup by Deployment Mode:
On-premises hold the largest share in the market
A detailed breakup and analysis of the market based on the deployment mode has also been provided in the report. This includes cloud-based, and on premises. According to the report, on-premises accounted for the largest market share.
The rising popularity of cloud-based MLOps platforms due to their inherent advantages, such as scalability and elasticity of cloud infrastructure, represents one of the key factors driving the market growth. In addition to this, expanding product adoption across various industrial verticals to enable easy handling of the growing volume and complexity of data required for ML is contributing to the market growth. Moreover, the expanding demand for on-premises MLOps solutions due to the strict data privacy and security requirements of organizations that necessitate keeping sensitive data within their own infrastructure is fueling the market growth. Besides this, on-premises MLOps offer greater control and allow organizations to maintain data sovereignty and compliance with regulatory frameworks, which is further propelling product adoption.
Breakup by Organization Size:
- Large Enterprises
- Small and Medium-sized Enterprises
Small and medium-sized enterprises are dominating the market
The report has provided a detailed breakup and analysis of the market based on the organization size. This includes large, and small and medium-sized enterprises. According to the report, small and medium-sized enterprises represented the largest segment.
The rising product adoption to leverage predictive analytics for a wide range of applications, such as demand forecasting, sales prediction, customer churn analysis, fraud detection, and risk assessment, is contributing to the market growth. Besides this, the widespread product employment to streamline the development and deployment of predictive models and ensure accurate and timely insights to support decision-making is aiding in market expansion. Moreover, MLOps suppports NLP models for applications, such as sentiment analysis, chatbots, language translation, and content categorization, which is creating a favorable outlook for market expansion. By integrating MLOps into NLP pipelines, enterprises can improve the accuracy and efficiency of language processing tasks, enabling enhanced customer support, content moderation, and information retrieval.
Breakup by Vertical:
- Healthcare and Life Sciences
- Retail and E-Commerce
- IT and Telecom
- Energy and Utilities
- Government and Public Sector
- Media and Entertainment
BFSI hold a larger share in the market
A detailed breakup and analysis of the market based on the vertical has also been provided in the report. This includes BFSI, healthcare and life sciences, retail and e-commerce, IT and telecom, energy and utilities, government and public sector, media and entertainment, and others. According to the report, BFSI accounted for the largest market share.
The bolstering growth of the retail and e-commerce sector, wherein MLOps is utilized to predict customer demand, optimize inventory management, and improve supply chain efficiency, is strengthening the market growth. Besides this, the increasing product utilization across the flourishing IT and telecom industry to monitor network performance, detect anomalies, optimize resource allocation, and automate network management tasks are presenting remunerative growth opportunities for the market. Moreover, MLOps facilitates the deployment of conversational AI models, powering chatbots and virtual assistants for customer support, troubleshooting, and self-service interactions, which is further propelling its adoption. Furthermore, the rising use of MLOps in the healthcare sector for medical imaging analysis, drug discovery, developing personalized treatment plans, predicting disease outcomes, and recommending tailored interventions based on patient data is positively impacting the market growth.
Breakup by Region:
- North America
- United Kingdom
- Asia Pacific
- South Korea
- Latin America
- Middle East and Africa
North America exhibits a clear dominance in the market, accounting for the largest MLOps market share
The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Europe (Germany, France, the United Kingdom, Italy, Spain, and others); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa.
The expanding adoption of advanced technology across various industrial verticals in North America, particularly the United States, is positively impacting the market growth. Besides this, the presence of several leading technology companies that heavily rely on ML for their products and services in the regions are aiding in market expansion. Moreover, the stringent regulatory framework and standards in industries, such as finance, healthcare, and cybersecurity, are strengthening the market growth. In line with this, a strong emphasis on data privacy and security in Europe and the implementation of the General Data Protection Regulation (GDPR) are impelling the demand for MLOps. Furthermore, rapid digital transformation in the Asia Pacific region and the surging adoption of AI and ML technologies to improve operational efficiency and customer experience are fueling the market growth.
The global MLOps market is characterized by a highly competitive landscape with the presence of numerous players offering a range of MLOps solutions and services. The competitive dynamics within the market are driven by factors such as technological advancements, strategic partnerships, product innovation, and market expansion initiatives. Key players in the global MLOps market include established technology companies, specialized MLOps solution providers, cloud service providers, and consulting firms. These players compete based on factors such as product features, scalability, ease of integration, pricing models, customer support, and industry expertise. To gain a competitive edge, companies are also investing in research and development (R&D) activities to enhance their MLOps offerings.
The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:
- Akira AI (XenonStack)
- Alteryx Inc.
- Amazon Web Services Inc.
- Dataiku Inc.
- Datarobot Inc.
- Domino Data Lab Inc.
- Google LLC (Alphabet Inc.)
- Hewlett Packard Enterprise Development LP
- International Business Machines Corporation
- Microsoft Corporation
- Neptune Labs
- In June 2023, Amazon Web Services, Inc. (AWS), announced the launch of AWS AppFabric, a no-code service that enhances companies’ existing investment in software as a service (SaaS) applications with improved security, management, and productivity.
- In June 2023, Hewlett Packard Enterprise Development LP announced the launch of HPE GreenLake for Large Language Models (LLMs) for any enterprise to privately train, tune, and deploy large-scale AI through an on-demand, multi-tenant supercomputing cloud service.
- In May 2023, Microsoft announced the launch of a suite of new AI solutions and improvements to Microsoft Cloud for Nonprofit that are designed to transform the nonprofit industry and how fundraisers engage with donors, manage campaigns, and optimize operations.
MLOps Market Report Scope:
|Base Year of the Analysis
| Historical Period
|Scope of the Report
||Exploration of Historical and Forecast Trends, Industry Catalysts and Challenges, Segment-Wise Historical and Predictive Market Assessment:
- Deployment Mode
- Organization Size
|Deployment Modes Covered
|Organization Sizes Covered
||Large Enterprises, Small and Medium-sized Enterprises
| Verticals Covered
||BFSI, Healthcare and Life Sciences, Retail and E-Commerce, IT and Telecom, Energy and Utilities, Government and Public Sector, Media and Entertainment, Others
||Asia Pacific, Europe, North America, Latin America, Middle East and Africa
||United States, Canada, Germany, France, United Kingdom, Italy, Spain, China, Japan, India, South Korea, Australia, Indonesia, Brazil, Mexico
||Akira AI (XenonStack), Alteryx Inc., Amazon Web Services Inc., Dataiku Inc., Datarobot Inc., Domino Data Lab Inc., Google LLC (Alphabet Inc.), H2O.ai, Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, Neptune Labs, etc.
||10% Free Customization
|Report Price and Purchase Option
||Single User License: US$ 2499
Five User License: US$ 3499
Corporate License: US$ 4499
|Post-Sale Analyst Support
||PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)
Key Questions Answered in This Report:
- How has the global MLOps market performed so far, and how will it perform in the coming years?
- What are the drivers, restraints, and opportunities in the global MLOps market?
- What is the impact of each driver, restraint, and opportunity on the global MLOps market?
- What are the key regional markets?
- Which countries represent the most attractive MLOps market?
- What is the breakup of the market based on the component?
- Which is the most attractive component in the MLOps market?
- What is the breakup of the market based on the deployment mode?
- Which is the most attractive deployment mode in the MLOps market?
- What is the breakup of the market based on the organization size?
- Which is the most attractive organization size in the MLOps market?
- What is the breakup of the market based on the vertical?
- Which is the most attractive vertical in the MLOps market?
- What is the competitive structure of the global MLOps market?
- Who are the key players/companies in the global MLOps market?
Key Benefits for Stakeholders:
- IMARC’s report offers a comprehensive quantitative analysis of various market segments, historical and current market trends, market forecasts, and dynamics of the MLOps market from 2017-2028.
- The research study provides the latest information on the market drivers, challenges, and opportunities in the global MLOps market.
- The study maps the leading, as well as the fastest-growing, regional markets. It further enables stakeholders to identify the key country-level markets within each region.
- Porter's five forces analysis assist stakeholders in assessing the impact of new entrants, competitive rivalry, supplier power, buyer power, and the threat of substitution. It helps stakeholders to analyze the level of competition within the MLOps industry and its attractiveness.
- Competitive landscape allows stakeholders to understand their competitive environment and provides an insight into the current positions of key players in the market.