Automated Machine Learning Market Size, Share & Trends Analysis Report By Offering (Solution, Services), By Deployment, By Enterprise Size, By Application, By Vertical, By Region, And Segment Forecasts, 2025 - 2033

Automated Machine Learning Market Summary

The global automated machine learning market size was valued at USD 3.50 billion in 2024 and is projected to reach USD 61.23 billion by 2033, growing at a CAGR of 38.0% from 2025 to 2033. This growth is attributed to Automated machine learning (AutoML’s) capability to identify discrepancies, errors, and other issues within the data, and present the user with choices, suggestions, as well as suggest outliers. Once the expert is presented with all this information, they can seamlessly curate multiple models, saving them time and effort.

Currently, AutoML open-source and commercial tools such as TPOT, H2O.ai, Google AutoML, and DataRobot are some of the best suited for streamlining the development of tasks wherein the goal is to predict an outcome/ result. These popular solutions tend to automate some or all the ML pipelines. For instance, DataRobot, the enterprise AI platform, makes data science accessible to everyone and automates the entire process of creating, deploying, and managing AI solutions at scale. It eliminates the reliance on manual workflows, automates repetitive and time-intensive steps, enables new users to build highly accurate models, and provides a fast-path for getting AI into production.

Automated machine learning is an essential process of automating iterative and time-consuming tasks. It enables developers, analysts, and data scientists to build ML models with productivity, efficiency, and high scale. AutoML has gained traction to minimize the knowledge-based resources needed to implement and train machine learning models. Moreover, Bullish demand for AutoML is mainly attributed to its ability to help enterprises boost insights and enhance model accuracy by minimizing chances for error or bias. End-users, including BFSI, healthcare, IT & telecom, and retail, are expected to inject funds into AutoML to rev up their AI efforts to create a valuable pipeline to automate data preprocessing, model selection, and pre-trained models.

Innovation in automated machine learning has led to significant advancements in various industries, transforming the way businesses operate and interact with their customers. Automation of complex processes enables organizations to speedily analyze network behavior and automatically execute required steps, enhancing processing speeds and performance. In addition, predictive maintenance using machine learning helps companies identify potential risks and predict failures, thereby increasing productivity and saving costs. Real-time business decision making is also facilitated through machine learning, allowing businesses to extract valuable insights from large datasets and make informed decisions. TinyML, a type of machine learning that runs on smaller devices, is ideal for battery-operated devices and IoT applications, reducing power consumption, latency, and bandwidth while maintaining user privacy and efficiency.

Global Automated Machine Learning Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented global automated machine learning market report based on offering, enterprise size, deployment, application, vertical, and region.

• Offering Outlook (Revenue, USD Billion, 2021 - 2033)
• Solution
• Services
• Deployment Outlook (Revenue, USD Billion, 2021 - 2033)
• On-Premises
• Cloud
• Enterprise Size Outlook (Revenue, USD Billion, 2021 - 2033)
• Large Enterprises
• SMEs
• Application Outlook (Revenue, USD Billion, 2021 - 2033)
• Data Processing
• Feature Engineering
• Model Selection
• Hyperparameter Optimization Tuning
• Model Ensembling
• Others
• Vertical Outlook (Revenue, USD Billion, 2021 - 2033)
• BFSI
• Retail & E-Commerce
• Healthcare
• Government & Defense
• Manufacturing
• Media & Entertainment
• Automotive & Transportation
• IT & Telecommunications
• Others
• Regional Outlook (Revenue, USD Billion, 2021 - 2033)
• North America
• U.S.
• Canada
• Mexico
• Europe
• Germany
• UK
• France
• Asia Pacific
• China
• Japan
• India
• South Korea
• Australia
• Latin America
• Brazil
• Middle East and Africa (MEA)
• UAE
• KSA
• South Africa

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