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Automated Machine Learning (AutoML) Market Growth Potential: How Will Market Size Shift Through 2030?
The automated machine learning (automl) market has seen a rapid expansion in its size over recent years. This market is projected to expand from $2.34 billion in 2025 to $3.43 billion in 2026, showing a compound annual growth rate (CAGR) of 46.5%. The historical expansion of this market was primarily driven by factors like the scarcity of skilled data scientists, the increasing volumes of enterprise data, the widespread adoption of cloud computing, a rising demand for faster analytics, and the broader application of AI across various industries.
The automated machine learning (automl) market size is projected to undergo significant expansion in the upcoming years. It will grow to $16.06 billion in 2030 at a compound annual growth rate (CAGR) of 47.0%. This projected growth within the forecast period is fueled by increasing adoption among small and medium enterprises, integration with business intelligence tools, the advancement of automated decision-making systems, a rising need for real-time analytics, and the broader application of AI-driven digital transformation. Prominent trends expected during this period include the simplification of model development, automated feature engineering, rapid deployment of ML models, the democratization of data science, and the emergence of scalable cloud-based automl platforms.
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Automated Machine Learning (AutoML) Market Demand Drivers Opening New Revenue Streams
The future expansion of the automated machine learning (AutoML) market is anticipated due to the increasing demand for sophisticated fraud detection methods. Fraud detection focuses on identifying and stopping illicit actions or patterns within an organization or system. Automated machine learning (AutoML) assists in this process through its ability to handle and scrutinize vast datasets, pinpointing patterns and anomalies that suggest fraud. For example, Allianz Insurance plc, a Germany-based firm providing insurance and asset management services, reported in February 2024 that claims fraud amounted to $95.2 million (£77.4 million) in 2023, an increase from $86.96 million (£70.7 million) in 2022. Consequently, the growing requirement for advanced fraud detection solutions fuels the expansion of the automated machine learning (AutoML) market.
Automated Machine Learning (AutoML) Market Segment Landscape And Growth Outlook
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
Automated Machine Learning (AutoML) Market Trends Powering Strategic Industry Growth
Leading companies in the automated machine learning (AutoML) market are focusing on developing innovative solutions, including an AutoML platform for ARM compilers. AutoML for the Arm compiler typically refers to the integration of automated machine learning (AutoML) capabilities with the Arm compiler, which is designed to generate machine code for Arm processors. For example, in March 2023, TDK Corporation, a Tokyo-based electronic solutions manufacturer, announced the introduction of ‘Qeexo AutoML’. This Qeexo AutoML platform is specifically designed for lightweight Cortex-M0 to -M4 class processors, offering support for a diverse range of machine learning algorithms. Notably, it is highly effective in providing ultra-low latency and power consumption. The platform enables customers to quickly develop and implement machine learning solutions by utilizing sensor data. Its exceptionally small memory footprint makes it ideal for deployment in industrial, IoT, wearables, automotive, mobile, and other resource-constrained environments.
Automated Machine Learning (AutoML) Market Competitive Landscape: Who Leads The Industry?
Major companies operating in the automated machine learning (automl) market are 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; H2O.AI Inc.; KNIME; Cognitivescale; Anyscale Inc.; RapidMiner; Squark AI Inc.; Auger.AI; DotData Inc.; BigML Inc.; Valohai; DarwinAI; Aible Inc.; SigOpt; Xpanse AI; Neptune Labs
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Automated Machine Learning (AutoML) Market Largest Region: Which Geography Holds The Biggest Share?
North America was the largest region in the automated machine learning (AutoML) market in 2025. 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, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
