USD 1.4 billion
Report ID:
SQMIG45D2064 |
Region:
Global |
Published Date: March, 2025
Pages:
197
|Tables:
59
|Figures:
75
Global MLOps Market size was valued at USD 1.4 billion in 2023 and is poised to grow from USD 1.97 billion in 2024 to USD 30.45 billion by 2032, growing at a CAGR of 40.8% during the forecast period (2025-2032).
The growing demand for ML and AI-based solutions across industries has led to remarkable global MLOps market growth in the recent past. The epidemic of COVID-19 had further fueled this expansion, as companies sought novel ways of leveraging AI and ML technology to meet customers' needs, improve productivity, and increase profitability. Digitization and internet penetration are also on an upward trajectory globally, thus promoting the market since companies can now use data and analytics in a real-time basis. The healthcare industry has been one of the biggest beneficiaries of MLOps solutions, where AI and ML are being applied to advance patient outcomes, speed up medical procedures, and accelerate healthcare delivery. Technologies, such as image analysis, tailored care recommendations, and predictive modeling, change the approach of health practitioners in diagnosis and treatment. These innovations are scaled by healthcare companies using MLOps solutions, ensuring compliance with strict privacy and data security laws.
For challenges involving model deployment, monitoring, and constant improvement into healthcare systems arising from integrating AI and ML technologies, strong solutions in MLOps become necessary. Therefore, based on its adaptation in recent years by the healthcare industry, using technologies such as healthcare analytics, precision medicine, and telemedicine significantly, the healthcare industry is highly expected to contribute to rising MLOps growth rates.
Market snapshot - 2025-2032
Global Market Size
USD 1.4 billion
Largest Segment
Platform
Fastest Growth
Services
Growth Rate
40.8% CAGR
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Global MLOps Market is segmented by Component, Deployment Mode, Organization Size, End Use and region. Based on Component, the market is segmented into Platform and Services. Based on Deployment Mode, the market is segmented into On-Premises and Cloud. Based on Organization Size, the market is segmented into Large Enterprises and SMEs. Based on End Use, the market is segmented into Banking, Financial Services, and Insurance, Retail and eCommerce, Government and Defense, Healthcare and Life Sciences, Manufacturing, Telecom, IT and ITeS, Energy and Utilities, Transportation and Logistics and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
As per the 2024 global MLOps market analysis, due to effectiveness in optimizing the management and running of machine learning models, the platform segment dominated the market, taking over more than 76% of global revenue. In a machine learning environment, it helps enterprises develop, maintain, train, and deploy models. The combination of a specifically designed suite of data preparation, categorization, monitoring, training, and tuning tools into other work categories accelerates business experimentation. For instance, the MLOps platform provider Weights & Biases recently announced significant upgrades to the platform in October 2022. The biggest changes promise to further develop ML activity by both practitioners and companies who use it by providing an end-to-end, frictionless MLOps experience.
The services segment is expected to grow significantly over the forecast period. MLOps development, consulting, monitoring, and license and maintenance services are included in the MLOps services. MLOps services will help enterprises grow through efficient development, deployment, and management of machine learning models. These services will enhance the operational efficiency of organizations, extend use cases, improve model accuracy, fasten time-to-market, and encourage collaboration. NxtGen Datacenter & Cloud Technologies Pvt., to make, simplify, and accelerate mainstream adoption of AI by digital native startups, enterprises, educational institutions, research institutes, and government agencies. Ltd., the provider of data center and cloud services, entered a partnership in December 2021 to launch MLOps as a Service with Katonic Pty. Ltd., an AI startup.
Based on the 2024 global MLOps market forecast, the BFSI category had the highest revenue share, more than 19%. The financial industry has been increasingly applying machine learning to solve specific problems like fraud detection, yield management, and predictive maintenance of legacy systems. To enhance customer experiences as a whole, financial institutions may use MLOps to automate the integration of ML/AI models into applications at digital channels or touchpoints where customers interact with banks. Moreover, it allows financial organizations to utilize their data and analytics to train the models. Due to their inability to produce enterprise-grade data on large scales, third-party vendors are no longer required to outsource their stored figures and facts to them.
Whereas the healthcare & life sciences segment is expected to grow at a significant pace during the projection period. With the rising healthcare industry, usage of AI tools and procedures in getting better and faster results, primarily in the diagnosis of diseases, there is a growing need to operationalize machine learning. In healthcare, such technologies would generate diagnosis improvements through analysis of images, medical records with other tools and software. Well-trained machine learning systems, for example, would identify patterns and could predict some illness based on similar conditions. This area of automation will enable the use of technology over manual procedures and will consequently increase the general cost-effectiveness of health care.
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Since North America had many developed economies and research institutes and some top Al firms, the region held the dominant position in 2024. North America contributed over 41% of revenue in the global market in the year 2024. Its growth prospect will be larger as its investment to develop cutting-edge technology is witnessed for making a customer-friendly better corporate process. It has also significantly invested in Al-related technology in the last couple of years and developed great R&D skills with Al. They also came up with legislation to make further progress in the industry. For instance, an open-source startup called Allegro AI in December 2022 stated that it was a historic growth year for the company, breaking new highs in user base, revenues, and partnerships.
Asia-Pacific is predicted to grow at the fastest CAGR throughout the forecast period. Major players, such as Amazon Web Services, Inc., Microsoft, and Google, are rapidly strengthening their positions in the fast-growing MLOps market in Asia-Pacific. Thus, it is expected that cloud-based MLOps solutions will foster wider-scale adoption by the Asia-Pacific enterprises as they exploit the scalability and flexibility of cloud infrastructure. There are also investments by both companies and governments in this region in AI and machine learning. The investments will increase the demand for MLOps solutions so that they can be developed and deployed to build large-scale machine learning models.
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MLOps Market Drivers
Growing Interest in AI and ML Solutions
Their rapid adoption in all industries is for purposes such as productivity, innovation, and satisfaction of customers. Organizations work towards data-driven decision-making, process automation, and analysis on a larger scale with these technologies. The global MLOps industry is booming, as organizations look toward scalable solutions managing machine learning best practices efficiently. This is becoming a critical area with the focus moving to healthcare, finance, and retail-an area well served for a while with AI and ML efforts.
Internet penetration and Digital Transformation
The global trend of digital transformation has created the need for MLOps solutions. Cloud-based technologies and increased internet penetration have enabled the use of machine learning models on a large scale in businesses. The growth in digital infrastructure enables the practical implementation, monitoring, and management of AI and ML systems. Most of them make huge investments in MLOps for improving their operational abilities while competing in a data-oriented environment across different industries that range from healthcare to finance.
MLOps Market Restraints
Issues Regarding Data Privacy and Compliance
As MLOps solutions often involve handling massive amounts of sensitive data, compliance with the pertinent data protection regulations-GDPR, HIPAA, and so on-becomes significant. To avoid legal issues, therefore, organizations need to ensure that models for machine learning align strictly with regulatory standards. Ensuring compliance across many sectors and regions can slow down MLOps implementation, at least in highly regulated industries such as banking and health care.
Integration Complexity with Current Systems
It may be quite a challenge to integrate MLOps solutions with existing business and IT solutions. It might also necessitate significant re-structuring and alignment of legacy systems which a majority of firms have today in an attempt to align machine learning operations to existing infrastructures. Due to this complexity, firms would be discouraged from embracing such full-scale MLOps implementation, leading to cost-push, time-push, and operational interruptions mostly when resources are few in number.
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Key players in the highly competitive MLOps market are Microsoft, Google, IBM, Amazon Web Services (AWS), and DataRobot. They are full-fledged platforms to develop, deploy, and manage machine learning models. More specialized solutions started coming for startups and specialty companies in areas such as automation, model monitoring, and healthcare. Strategic alliances, acquisitions, and continuous innovation shape the competitive landscape of such a highly dynamic industry.
SkyQuest's ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Correlates, and Analyses the Data collected using Primary Exploratory Research backed by robust Secondary Desk research.
As per SkyQuest analysis, the increasing adoption of AI and ML technologies is bound to be a significant booster for the MLOps market growth. The ever-growing demand for better, scalable machine learning solutions prompted organizations to employ MLOps platforms for accelerating the process of model creation, deployment, and monitoring. While there are problems such as high installation costs, data privacy issues, and integration concerns, the market is shifting for reasons such as constant improvement of automation, cloud solutions, and AI-driven technologies. Continuous innovation, especially in healthcare, finance and retail, is going to sustain market growth wherein MLOps solutions are intrinsic in improving operational efficiency and decision-making.
Report Metric | Details |
---|---|
Market size value in 2023 | USD 1.4 billion |
Market size value in 2032 | USD 30.45 billion |
Growth Rate | 40.8% |
Base year | 2024 |
Forecast period | 2025-2032 |
Forecast Unit (Value) | USD Billion |
Segments covered |
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Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
Companies covered |
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Customization scope | Free report customization with purchase. Customization includes:-
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Table Of Content
Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
Methodology
For the MLOps Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the MLOps Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Analyst Support
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the MLOps Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the MLOps Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
MLOps Market size was valued at USD 1.55 Billion in 2023 and is poised to grow from USD 2.19 Billion in 2024 to USD 34.16 Billion by 2032, growing at a CAGR of 41% during the forecast period (2025-2032).
Key players in the highly competitive MLOps market are Microsoft, Google, IBM, Amazon Web Services (AWS), and DataRobot. They are full-fledged platforms to develop, deploy, and manage machine learning models. More specialized solutions started coming for startups and specialty companies in areas such as automation, model monitoring, and healthcare. Strategic alliances, acquisitions, and continuous innovation shape the competitive landscape of such a highly dynamic industry. 'IBM (US)', 'Microsoft (US)', 'Google (US)', 'AWS (US)', 'HE (US)', 'GAVS Technologies (US)', 'DataRobot (US)', 'Cloudera (US)', 'Altery (US)', 'Domino Data Lab (US)', 'Valohai (US)', 'H20.ai (US)', 'MLflow (Netherlands)', 'Neptune. ai (Europe)', 'Comet (US)', 'SparkCognition (US)', 'Hopsworks (Europe)', 'Datatron (US)', 'Weights & Biases (US)', 'Katonic.ai (Australia)'
Integrating MLOps in Healthcare: AI/ML is gradually turning out to be the backbench support for this industry, be it image analysis in healthcare, customization of treatment, or predictive modeling. MLOps solutions are increasingly utilized to speed up the construction and deployment of models while remaining scalable and meeting healthcare industry standards. The increasing need for cutting-edge healthcare technology and better patient outcomes is driving the use of MLOps platforms, which enable better decision-making and effective healthcare delivery.
Since North America had many developed economies and research institutes and some top Al firms, the region held the dominant position in 2024. North America contributed over 41% of revenue in the global market in the year 2024. Its growth prospect will be larger as its investment to develop cutting-edge technology is witnessed for making a customer-friendly better corporate process. It has also significantly invested in Al-related technology in the last couple of years and developed great R&D skills with Al. They also came up with legislation to make further progress in the industry. For instance, an open-source startup called Allegro AI in December 2022 stated that it was a historic growth year for the company, breaking new highs in user base, revenues, and partnerships.
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