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Premium Report Details
Base Year: 2024
Companies covered: 20
Tables & Figures: 200
Countries covered: 21
Pages: 180
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MLOps Market
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MLOps Market Size
The global MLOps market was valued at USD 1.7 billion in 2024 and is projected to grow at a CAGR of 37.4% between 2025 and 2034. The market is integrates with cloud computing. With a shift to cloud computing, the cloud-based platforms provide scalability that is critical in handling large datasets and complex machine learning workflows. Non-premise infrastructure is not a necessity as the cloud infrastructure allows MLOps solutions to be deployed across numerous environments which improves compromise, performance and scalability.
For instance, Snowflake revealed last month that additional features will be added to its MLOps capabilities which are intended to manage features and models in May of 2024. These updates purport to address the issues of lack of integrated and ‘simplistic ML workflows,' as many enterprises have. The features include Snowflake's Model Registry, controlled cloud-based model management and inference for efficient scalable models, as well as the pre-released Feature Store, Snowflake's integrated ML feature management tool that ensures dependable and consistent data throughout the ML pipeline.
In this age of rapid technological advancement, companies have a strong orientation towards having new machine learning models developed and deployed at a significantly rapid pace. Speed is of the essence in the competitive landscape, and thus, MLOps makes it possible to design, test, and implement machine learning models with great efficiency. MLOps platforms facilitate CI/CD, meaning the deployment of new products and features can happen rapidly and with minimal manual work. Not only is the speed of deployment increased, but the ability to improve models while they are live is also provided.
MLOps Market Trends
The changes related to MLOps are redefining the entire industry of machine learning model development, deployment, and management. One of the major advancements is the rise and better adoption of Automation and Continuous Integration/ Continuous Deployment (CI/CD) pipelines, which help in releasing features and products much faster and with fewer bugs. These pipelines are instrumental in deploying machine learning models into production systems without compromising on the standard of work done.
The concepts of Model Monitoring and Governance are becoming increasingly important since the organizations want to ensure that the models that are in use are being used to their optimal capacity while also following required deadlines. As the model is used, it will confidently track its effectiveness as well as have the flexibility to accommodate model drift or changes in data patterns. The other important development is that the blending of MLOps, Cloud Computing, and Edge Computing is enabling the MLOps market growth by supporting autonomous site-specific data processing with self-controlled vehicles, IoT devices, and many other similar applications.
Similarly, privacy and data security is a major issue that regards MLOps wherein sensitive data is at stake for the company’s model training and its deployment. There needs to be more focus on methods to control and mitigate attacks that could lead to violation of GDPR and HIPPA which make data leaks and intellectual property protection difficult while also building effective security mechanisms as well as encoding the data.
The other major problem in MLOps remains lack of skilled human resources who are not just knowledgeable about machine learning, but even its operations. The difficulties with data collection, deployment, monitoring and the entire lifecycle of AI models Management means that there is a real skills gap which hinders MLOps processes from being leveraged at scale.
MLOps Market Analysis
In the MLOps market, based on components, the segmentation includes platforms and services. Platforms emerged as key players in the market with a share of 72% in 2024, owing to the steady growth in global all-in-one MLOps solutions adoption by Enterprises. The main reason behind this is the need for Enterprises to have a single place to manage their data pipelines, track experiments, deploy models and monitor performance, especially when scaling their AI initiatives.
However, integration and managed services along with consulting services are among the fastest-growing segments. The workflows of MLOps adoption in organizations are quite complex when it comes to cloud migration, infrastructure optimization, and even compliance, which is why these services prove to be invaluable.
In the MLOps market, based on end use, the market is segmented into Large Enterprises and SMEs. In 2024, the Large Enterprises segment dominated the market, holding 64.3% share, A steady increase in the adoption of global all-in-one MLOps solutions by Enterprises is the main factor behind this trend. These platforms allow enterprises to organize the data pipeline, track experiments, deploy models, and monitor performance all under a single umbrella which is instrumental while scaling AI initiatives.
However, integration and managed services along with consulting services are among the fastest-growing segments. The workflows of MLOps adoption in organizations are quite complex when it comes to cloud migration, infrastructure optimization, and even compliance, which is why these services prove to be invaluable.
In 2024, the United States holds a significant position within the North American MLOps market, projected to reach over USD 11 billion by 2034, widespread increase in using AI and machine learning technologies across different sectors like healthcare, finance, and even manufacturing. There is an increased demand for a completer and more effective MLOps infrastructure that can integrate well with the organization’s training and operational ML models.
U.S. companies are beginning to adopt more sophisticated systems for model deployment, monitoring, governance, and management to improve inter departmental workflow between data science, IT, and operations teams. The continued spending on cloud infrastructure and high-performance computing resources also accelerates the growth of MLOps in the server as companies look to optimize model operations and lower their time to market.
As in the case with China, India and Japan, MLOps is on the rise due to the region's fast moving AI digitalization, which is causing a constant need for tools that facilitate the deployment and scaling of AI models. E-commerce, manufacturing, and healthcare where the modification of machine learning workflow processes is very important for the efficient functioning of operations and within the confines of the data privacy laws in the region.
The rising adoption of decision-making and automation of processes directly correlates with the rising MLOps usage in the region. Similar patterns can be deduced with the regions sectors such as finance, automotive, and retail, as they look to enhance their model deployment and monitoring. MLOps Integration is also on the rise in Europe with the ethical regulations such as privacy and AI compliance championing it.
MLOps Market Share
In 2024, Amazon, Atos, Capgemini, Cisco, Alphabet, Microsoft, and IBM collectively accounted for 39.1% of the MLOps industry. Their presence in the market is fueled by investments in more advanced machine learning technologies, sophisticated cloud infrastructure, and specific services towards any enterprise. Competitors such as Amazon and Microsoft, serve numerous enterprises through AWS and Azure cloud platforms by offering tailored and integrated MLOps services that are easy to scale.
With the introduction of AI platforms such as Vertex AI, Alphabet’s Google Cloud is in the fore front. In contrast, Atos, Cap Gemini and IBM are more concentrated on hybrid cloud solutions and industry-specific consulting services to tackle the unique issues in the market. Cisco pursues the strategy in combination Z while adding MLOPs strategies such as edge computing security. These and other companies are responsible for shaping the competition and the innovation in the adoption of MLOPS for different industries.
MLOps Market Companies
Major players operating in the MLOps industry are:
The MLOps market has a unique structure consisting of both global and local players which helps address specific customer requirements across industries such as healthcare, finance, retail, and manufacturing. Even in this competition, global players outperform the local vendors due to their deep pockets, broad MLOps portfolios, and capability to integrate, scale and automate the deployment of machine learning models.
Thanks to tremendous innovation efforts in automated pipelines creation, model monitoring, and data protection, they have achieved unquestionable leadership in these markets where AI and advanced infrastructure is well adopted. Moreover, they achieve even greater market dominance by acquiring medium-to-large independent firms.
MLOps Industry News
The MLOps market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue ($ Mn) from 2021 to 2034, for the following segments:
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Market By Component
Market By Deployment Mode
Market By End Use
Market By Vertical
The above information is provided for the following regions and countries: