Automated Machine Learning (AutoML) Market
The world of automated machine learning (AutoML) is rapidly evolving and gaining attention from companies looking to leverage AI-driven insights without the need for extensive data science expertise. The AutoML market will see impressive growth in the coming years as companies increasingly look for ways to automate complex machine learning processes. Let’s explore the market size, key players, recent developments, emerging trends, and segmentation to understand where this technology is heading.
Forecast market size and growth outlook for automatic machine learning market
The automated machine learning market is poised for tremendous expansion, with its value expected to reach $16.06 billion by 2030. This growth represents an impressive compound annual growth rate (CAGR) of 47.0%. Factors driving this surge include increased adoption by small and medium-sized businesses, seamless integration with business intelligence platforms, increased use of automated decision-making systems, demand for real-time analytics, and growing AI-powered digital transformation initiatives. Key trends shaping the future of the market include simplified model development, automated feature engineering, rapid deployment of machine learning models, democratization of data science, and the rise of scalable, cloud-based AutoML platforms.
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Industry leader in automated machine learning
The AutoML market is shaped by a number of influential companies driving innovation and adoption. Notable organizations in this field include Google LLC, Microsoft Corporation, Amazon Web Services Inc., International Business Machines Corporation (IBM), 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, Square AI Inc., Auger.AI, DotData Inc., BigML Inc., Valohai, DarwinAI, Aible Inc., SigOpt, Xpanse AI, and Neptune Labs. These companies are at the forefront of developing AutoML solutions that meet diverse industry needs and accelerate AI adoption.
Strategic acquisition strengthens embedded AI capabilities
In May 2023, Germany-based semiconductor giant Infineon Technologies AG acquired Imagimob AB, a Swedish company specializing in edge AI and tiny machine learning (tinyML). Although financial details were not disclosed, the acquisition strengthens Infineon’s position in the growing embedded AI market. This leverages Imagimob’s expertise in creating intelligent products that operate with minimal power and high efficiency, strengthening its ability to deliver advanced, energy-efficient control solutions for Internet of Things (IoT) applications.
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Innovations driving the AutoML market forward
AutoML providers focus on creating cutting-edge solutions tailored to specific hardware, such as ARM processors. For example, in March 2023, Tokyo-based electronics solutions company TDK Corporation introduced “Qeexo AutoML.” The platform targets lightweight Cortex-M0 to -M4 class processors and supports a wide range of machine learning algorithms. It stands out for its ultra-low latency and power efficiency, allowing customers to rapidly develop and deploy machine learning models using sensor data. The platform’s small memory footprint makes it particularly suitable for deployment across industrial applications, IoT devices, wearables, automotive systems, mobile devices, and other environments with limited resources.
Detailed market segmentation and forecasting of the Automated Machine Learning industry
This report categorizes the AutoML market into several key segments to gain a deeper understanding of its structure and growth potential.
1) How we provide: solutions and services
2) By deployment: cloud-based vs. on-premises
3) By company size: SMEs, large companies
4) By application: data processing, feature engineering, model selection, hyperparameter optimization and tuning, model assembly, and other applications.
5) End User Sector: Banking, Financial Services and Insurance (BFSI), Retail and E-Commerce, Healthcare, Manufacturing, and Other Industries
Further subcategories include:
– Solutions: cloud-based solutions, on-premises solutions, integrated development environments (IDEs)
– Services: Consulting, implementation, training and support services
This segmentation focuses on a broad range of customized AutoML offerings designed to meet the diverse needs of different business sizes, deployment preferences, industries, and application types.
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