Global Machine Learning Operations Market Projected to Grow at 37.8% CAGR, Reaching $10.71 Billion by 2029

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Machine Learning Operations Market Size Growth Forecast: What to Expect by 2025?
The market size for machine learning operations has experienced explosive growth in the past few years. It is projected to expand from $2.16 billion in 2024 to $2.97 billion in 2025, representing a compound annual growth rate (CAGR) of 37.5%. This significant growth in the historical period can be traced back to factors such as the escalating complexity of machine learning models, the swift advancement of edge computing, the increasing embrace of federated learning, the ongoing integration of DevOps and MLOps, and a spike in the adoption of AutoML.

How Will the Machine Learning Operations Market Size Evolve and Grow by 2029?
The predicted expansion of the machine learning operations market size is expected to be exponential in the upcoming years, reaching a value of $10.71 billion in 2029, growing at a compound annual growth rate (CAGR) of 37.8%. Factors contributing to this growth through the projection period include the ongoing rise of cloud computing, escalating engagement of machine learning across various industries, the emergence of model deployment technologies, the practice of agile development model, and the growing intricacy of machine learning models. In the estimated period, key trends encompass the incorporation of augmented analytics, the popularization of machine learning, a significant surge in edge AI applications, automated adjustments in hyperparameters, and advanced security measures in MLOps pipelines.

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What Drivers Are Propelling the Growth of Machine Learning Operations Market Forward?
The anticipated increase in the need for autonomous vehicles is projected to boost the expansion of the machine-learning operations market. Autonomous cars are vehicles fitted with cutting-edge sensors, cameras, radar, lidar, and artificial intelligence (AI) systems that allow them to navigate, function, and make decisions on the road, all without the need for human intervention. Regarding self-driving cars, machine learning operations (MLOps) entail the constant integration, deployment, and supervision of machine learning models within these vehicles. This allows them to enhance and adapt their driving skills based on actual data received from sensors and a variety of driving situations. For example, according to a December 2022 report by the Insurance Institute for Highway Safety, a non-profit organization based in the US, it is forecasted that by 2025, approximately 3.5 million self-driving cars will be seen on American highways. This number is expected to rise to 4.5 million by 2030. Consequently, the increased demand for autonomous cars is fueling the expansion of the machine-learning operations market.

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Which Emerging Trends Are Transforming the Machine Learning Operations Market in 2025?
Major corporations in the machine learning operations sector are spearheading the creation of cutting-edge solutions such as GPT Monitoring for MLOps. This tool allows for the real-time tracking and cost management of GPT models, thereby maximizing performance and operational effectiveness for engineering groups. GPT monitoring for MLOps employs generative pre-trained transformers to advance the observation and control of machine learning operations, which ultimately betters the tracking of model performance and decision-making. For example, in March of 2023, the US-based digital intelligence firm, New Relic, introduced the New Relic Machine Learning Operations (MLOps) which is designed for real-time monitoring of applications constructed with OpenAI's GPT series APIs. This new functionality enables engineering groups to monitor performance and expenses with minimal code, offering immediate insight and observability into GPT usage. Compatibility with all present OpenAI GPT versions is a key feature, allowing businesses to optimize AI-powered applications whilst minimizing operational costs.

What Are the Key Segments in the Machine Learning Operations Market?
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

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Who Are the Key Players Shaping the Machine Learning Operations Market's Competitive Landscape?
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

What Geographic Markets Are Powering Growth in the Machine Learning Operations Market?
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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