Global Machine Learning Operations Market Insights, Revenue Analysis, and Future Outlook | Valuates Reports
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What Is the Forecasted Market Size of the Machine Learning Operations Market by 2029?
The machine learning operations market size has grown exponentially in recent years. It will grow from $2.16 billion in 2024 to $2.97 billion in 2025 at a compound annual growth rate (CAGR) of 37.5%. The growth in the historic period can be attributed to increasing complexity of ml models, rapid evolution of edge computing, increasing adoption of federated learning, continuous integration of devops and mlops, surge in automl adoption.
The machine learning operations market size is expected to see exponential growth in the next few years. It will grow to $10.71 billion in 2029 at a compound annual growth rate (CAGR) of 37.8%. The growth in the forecast period can be attributed to rise of cloud computing, increased adoption of machine learning in industries, development of model deployment technologies, adoption of agile development practices, increased complexity of machine learning models. Major trends in the forecast period include augmented analytics integration, democratization of machine learning, exponential growth in edge ai applications, automated hyperparameter tuning, enhanced security in mlops pipelines.
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What Are the Major Drivers Influencing the Machine Learning Operations Market?
The rising demand for self-driving cars is expected to propel the growth of the machine-learning operations market going forward. Self-driving cars are automobiles equipped with advanced sensors, cameras, radar, lidar, and artificial intelligence (AI) systems that enable them to navigate, operate, and make decisions on the road without direct human intervention. Machine learning operations (MLOps) in self-driving cars involve the continuous integration, deployment, and management of machine learning models within the vehicles, enabling them to adapt and improve their driving capabilities based on real-time data from sensors and diverse driving scenarios. For instance, in December 2022, according to a report published by the Insurance Institute for Highway Safety, a US-based non-profit organization, it is projected that there will be an estimated 3.5 million autonomous vehicles on American roads by 2025, with expectations for this number to increase to 4.5 million by the year 2030. Therefore, the rising demand for self-driving cars is driving the growth of the machine-learning operations market.
Which Are the Leading Segments in the Machine Learning Operations Market by Revenue?
The machine learning operationsmarket covered in this report is segmented –
1) By Deployment Type: On-Premise, Cloud, Other Type Of Deployment
2) By Organization Size: Large Enterprises, Small And Medium-sized Enterprises
3) By Industry Vertical: BFSI (Banking, Financial Services, And Insurance), Manufacturing, IT And Telecom, Retail And E-commerce, Energy And Utility, Healthcare, Media And Entertainment, Other Industry Verticals
Subsegments:
1) By On-Premise: Private Data Centers, Local Servers
2) By Cloud: Public Cloud Services, Hybrid Cloud Solutions, Multi-Cloud Environments
3) By Other Type Of Deployment: Edge Deployment, Hybrid On-Premise Or Cloud Solutions
Which Trends Are Positively Affecting the Machine Learning Operations Market Expansion?
Major companies operating in the machine learning operations market are developing new innovative solutions such as GPT Monitoring for MLOps to enable real-time monitoring and cost tracking of GPT models, optimizing performance and operational efficiency for engineering teams. GPT Monitoring for MLOps involves using generative pre-trained transformers to enhance the monitoring and management of machine learning operations, improving model performance tracking and decision-making. For instance, in March 2023, New Relic, a US-based digital intelligence company, launched New Relic Machine Learning Operations (MLOps) for real-time monitoring of applications built with OpenAI’s GPT series APIs. This new capability allows engineering teams to track performance and costs with just two lines of code, providing instant observability and insights into GPT usage. It supports all current OpenAI GPT versions, enabling companies to optimize AI-driven applications while reducing operational expenses.
Who Are the Leading Players in the Machine Learning Operations Market?
Major companies operating in the machine learning operations market report are Amazon.com Inc., Alphabet Inc., Microsoft Corporation, International Business Machines Corporation, Hewlett Packard Enterprise, Statistical Analysis System (SAS ), Databricks Inc., Cloudera Inc., Alteryx Inc., Comet, GAVS Technologies, DataRobot Inc., Veritone, Dataiku, Parallel LLC, Neptune Labs, SparkCognition, Weights & Biases, Kensho Technologies Inc., Akira.Al, Iguazio, Domino Data Lab, Symphony Solutions, Valohai, Blaize, Neptune.ai, H2O.ai, Paperspace, OctoML
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What Are the Opportunities and Challenges for Machine Learning Operations Market Across Regions?
North America was the largest region in the machine learning operations market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the machine learning operations market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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