What Is The Current and Historic Market Size Analysis Of The Machine Learning Operations Market?
The machine learning operations market has seen considerable growth due to a variety of factors.
• The scale of the machine learning operations market has been expanding significantly in the past few years. It is predicted to increase from $2.16 billion in 2024 to $2.99 billion in 2025, witnessing a compound annual growth rate (CAGR) of 38.4%.
The historical growth can be associated with the escalating complexity of machine learning models, swift advancement of edge computing, the widespread adoption of federated learning, unbroken integration of devops and mlops, and a growth in automl adoption.
What are the Market Size and Expected Growth Rates for the Machine Learning Operations Market?
The machine learning operations market is expected to maintain its strong growth trajectory in upcoming years.
• In the coming years, the market size for machine learning operations is predicted to experience substantial growth. The market is projected to expand to $10.84 billion by 2029, with a CAGR of 38.0%.
The growth during the forecasted period can be linked to the rise of cloud computing, growing use of machine learning across various sectors, the advent of model deployment technologies, the embracing of agile development techniques, and the increased intricacy of machine learning models. Major emerging trends during the estimated period include the integration of augmented analytics, the democratization of machine learning, a rapid increase in edge ai applications, automated adjustments in hyperparameter tuning, and improved security features in MLOps pipelines.
Which Key Drivers Are Propelling The Machine Learning Operations Market's Growth?
The machine-learning operations market is set to flourish due to the growing interest in autonomous vehicles. These vehicles use cutting-edge sensors, cameras, radar, lidar, and artificial intelligence (AI) technologies to move, operate, and make independent decisions on the road without any human input. Machine learning operations (MLOps) within these vehicles include the ongoing integration, deployment, and administration of machine learning algorithms, allowing them to refine their driving skills based on real-time sensor data and various on-road situations. For example, a report by the US-based non-profit organization, the Insurance Institute for Highway Safety, in December 2022, suggests an anticipated 3.5 million self-driving vehicles on US roads by the year 2025. This projection suggests growth to 4.5 million by 2030. Consequently, the escalating demand for autonomous vehicles is fuelling the expansion of the machine-learning operations market.
What Are The Key Segments Within The Global Machine Learning Operations Market?
The machine learning operations market 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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What Emerging Trends Are Influencing The Growth Of The Machine Learning Operations Market?
Leading firms in the machine learning operations market are creating novel solutions like GPT Monitoring for MLOps, which allow for real-time scrutiny and expense tracking of GPT models, thereby maximizing performance and operational effectiveness for technology teams. GPT Monitoring for MLOps includes crafting pre-trained transformers for better supervision and control of machine learning operations, enhancing model performance assessment and decision-making processes. For example, New Relic, an American digital intelligence business, introduced New Relic Machine Learning Operations (MLOps) in March 2023, designed for real-time surveillance of applications crafted with OpenAI's GPT series APIs. This fresh feature enables tech teams to monitor performance and expenses with a mere two lines of code, offering immediate observability and understanding into GPT usage. It is compatible with all existing OpenAI GPT versions, thus allowing corporations to optimize AI-powered applications and lessen operational costs.
Who Are the Key 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
What Are The Regional Insights Into 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.
