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Automated Machine Learning (AutoML) Market Value Analysis: What Growth Is Expected Over The Forecast Period?
The automated machine learning (automl) market size has expanded exponentially in recent years. It is forecast to increase from $2.34 billion in 2025 to $3.43 billion in 2026, achieving a compound annual growth rate (CAGR) of 46.5%. This historic growth can be attributed to a shortage of skilled data scientists, the growth of enterprise data volumes, the adoption of cloud computing, the demand for faster analytics, and the expansion of AI applications across industries.
The automated machine learning (automl) market size is anticipated to expand substantially in the upcoming years, with projections indicating it will attain $16.06 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 47.0%. This projected increase is largely due to factors such as growing adoption by small and medium enterprises, its integration with business intelligence tools, the proliferation of automated decision-making systems, the demand for real-time analytics, and the broader expansion of AI-driven digital transformation. Noteworthy trends expected during this period include simplified model development, automated feature engineering, rapid deployment of ML models, the democratization of data science, and the availability of scalable cloud-based automl platforms.
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#Automated Machine Learning (AutoML) Market Demand Drivers Creating New Revenue Opportunities
The increasing demand for sophisticated fraud detection solutions is projected to fuel the expansion of the automated machine learning (AutoML) market moving forward. Fraud detection involves recognizing and preventing deceptive activities or behaviors within a system or organization. Automated machine learning (AutoML) can be effectively utilized for fraud detection by harnessing its capacity to process and analyze large quantities of data, identify patterns, and detect anomalies that could point to fraudulent actions. For example, in February 2024, Allianz Insurance plc, a Germany-based company providing insurance and asset management services, reported that $95.2 million (£77.4 million) worth of claims fraud was identified in 2023, an increase from $86.96 million (£70.7 million) in 2022. Thus, the growing requirement for advanced fraud detection solutions propels the growth of the automated machine learning (AutoML) market.
Automated Machine Learning (AutoML) Market Segment Outlook: Which Categories Are Expanding The Fastest?
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 Driving Strategic Industry Expansion
Leading companies in the automated machine learning (AutoML) market are concentrating on developing innovative solutions, such as AutoML platforms designed for ARM compilers. AutoML for the Arm compiler typically refers to the integration of automated machine learning (AutoML) capabilities with the Arm compiler, a tool engineered to generate machine code for Arm processors. For example, in March 2023, TDK Corporation, an electronic solutions manufacturer from Tokyo, revealed the introduction of ‘Qeexo AutoML’. This Qeexo AutoML platform is specifically crafted for lightweight Cortex-M0 to -M4 class processors and offers support for a wide range of machine learning algorithms. It stands out for delivering extremely low latency and power consumption. The platform allows customers to swiftly create and implement machine learning solutions by leveraging sensor data. Boasting an exceptionally small memory footprint, it is an optimal choice for deployment across industrial, IoT, wearables, automotive, mobile, and other resource-limited environments.
Automated Machine Learning (AutoML) Market Key Companies And Competitive Benchmarking
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 Leading Geography: Which Region Generates The Most Revenue?
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.