How the Automated Machine Learning (AutoML) Market Will Grow: Key Trends, Market Size, and Opportunities Beyond 2025
2025 Market Reports Update: Market Size Forecasts to 2034, Key Trends, Leading Players, and Top Regions – Get Ahead of the Competition Today!
What Factors Are Propelling the Market Growth of theAutomated Machine Learning (AutoML) Market from 2025 to 2034?
The growing necessity for sophisticated fraud detection systems is projected to spur the expansion of the automated machine learning (AutoML) industry. Identifying and halting fraudulent activities within a system or institution are key aspects of fraud detection. AutoML’s ability to process and scrutinise massive amounts of data, recognise patterns, and find irregularities indicative of fraudulent activities allows it to serve as a powerful tool for fraud detection. For example, Allianz Insurance plc, a German firm offering insurance and wealth management services, reported in February 2024 that they had detected $95.2 million (£77.4 million) in claims fraud in 2023, an increase from $86.96 million (£70.7 million) in 2022. As a result, the augmented requirement for advanced fraud detection systems fuels the growth of the AutoML industry.
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#What Long-Term Growth Rate is Expected for theAutomated Machine Learning (AutoML) Market Between 2025 and 2034?
In recent years, the market size for automated machine learning (AutoML) has experienced significant growth. Projected growth indicates an increase from $1.64 billion in 2024 up to $2.35 billion in 2025, signifying a compound annual growth rate (CAGR) of 43.6%. The historical growth pattern is linked to the complexity of machine learning, the shortage of data science skills, the need for rapid solutions, advancements in artificial intelligence, and increased computing power along with cost efficiency.
In the coming years, the automated machine learning (AutoML) market is predicted to witness dramatic growth, with its market size escalating to $10.93 billion by 2029 with a compound annual growth rate (CAGR) of 46.8%. This upcoming expansion can be linked to AI integration across various sectors, the spread of IoT and big data, the emergence of edge computing, the use of hybrid cloud and on-premises solutions, and the demands of regulatory compliance. Key trends for the forecasted period include the automation of feature engineering, advancements in federated learning, the advent of explainable AI and model interpretability, AutoML’s application on unstructured data, and its use in autonomous systems.
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How Are Market Trends and Innovations Revolutionizing theAutomated Machine Learning (AutoML) Industry in Recent Times?
The advancement of technology is a prominent trend emerging in the automated machine learning (AutoML) industry. Many of the leading companies in the AutoML market are integrating these technological advancements to keep their market positions steady. A case in point is AND Solutions Pte Ltd., a Singaporean fintech firm providing AutoML platforms. In April 2023, they introduced the innovative NIKO AutoML platform. This state-of-the-art machine-learning tool has been designed to streamline and speed up the making of prediction models. It comes with a suite of tools and features, allowing users to build and launch first-rate machine learning models quickly and without needing coding or data science skills. The user-friendly interface of the platform guides users throughout each stage of the process, ensuring top-quality results in less time than traditional methods. The NIKO AutoML platform provides many advantages such as rapid and precise model development, streamlined operational flow, improved productivity, and cost efficiency.
Which Key Market Players Are Shaping the Future and Growth of theAutomated Machine Learning (AutoML) Market?
Major companies operating in the automated machine learning (AutoML) market include Google LLC, Microsoft Corporation, Amazon Web Services Inc., International Business Machines Corporation, Oracle Corporation, Salesforce Inc., Teradata Corporation, Alteryx, Altair Engineering Inc., EdgeVerve Systems Limited, TIBCO Software Inc., DataRobot Inc., Dataiku, BigPanda., H2O.ai Inc., KNIME, Cognitivescale, Anyscale Inc., RapidMiner, Squark AI Inc., Auger.AI, DotData Inc., BigML Inc., Valohai, DarwinAI, Aible Inc., SigOpt, Zerion, Xpanse AI, Neptune Labs
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The automated machine learning (AutoML) market covered in this report is segmented –
1) By Offering: Solutions, Services
2) By Deployment: Cloud, On-Premises
3) By Enterprise: Small And Medium Enterprise, Large Enterprise
4) By Application: Data Processing, Feature Engineering, Model Selection, Hyperparameter Optimization And Tuning, Model Assembling, Other Applications
5) By End User: Banking, Financial Services And Insurance (BFSI), Retail And E-Commerce, Healthcare, Manufacturing, Other End Users
Subsegments:
1) By Solutions: Cloud-Based Solutions, On-Premises Solutions, Integrated Development Environments (IDEs)
2) By Services: Consulting Services, Implementation Services, Training And Support Services
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What Regions Are Dominating the Automated Machine Learning (AutoML) Market Growth?
North America was the largest region in the automated machine learning (AutoML) market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the automated machine learning (AutoML) market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa
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