Automated Machine Learning (AutoML) - Global Strategic Business Report

The global market for Automated Machine Learning (AutoML) was valued at US$1.5 Billion in 2024 and is projected to reach US$10.9 Billion by 2030, growing at a CAGR of 38.8% from 2024 to 2030. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions.

Global Automated Machine Learning (AutoML) Market - Key Trends and Drivers Summarized

Automated Machine Learning (AutoML) is emerging as a transformative force in the field of artificial intelligence, designed to automate and streamline the often complex and time-consuming tasks of developing machine learning models. The key appeal of AutoML lies in its ability to make machine learning more accessible to non-experts and to enhance the efficiency of model development, making it a critical tool as industries increasingly seek to leverage AI capabilities. By automating the labor-intensive processes of data preprocessing, model selection, and parameter tuning, AutoML enables a more rapid deployment of machine learning models. This not only democratizes AI by reducing the need for specialized knowledge but also significantly expedites the AI development cycle, allowing businesses to quickly adapt to market changes and new data.

The rapid adoption of AutoML is driven by several compelling factors, chief among them the growing complexity of machine learning models and the pressing shortage of skilled data scientists. As machine learning applications become more sophisticated, the expertise required to effectively develop and tune these models escalates. AutoML addresses this challenge by simplifying critical tasks such as feature and algorithm selection and hyperparameter tuning, substantially lowering the barrier to advanced machine learning for organizations without deep technical resources. Additionally, the shortage of data scientists has catalyzed the need for tools that empower users with minimal technical background to undertake tasks traditionally reserved for experts. This democratization is crucial for organizations striving to initiate or accelerate their AI strategies in a competitive business environment.

Moreover, the integration of AutoML with advancements in AI and computing power, along with its synergy with cloud computing platforms, is expanding its application across various industries. This integration provides scalable computing resources essential for running complex models and supports the burgeoning demand for predictive analytics in sectors like healthcare, finance, and retail. Despite these advantages, the deployment of AutoML brings challenges, including the need for ongoing oversight by experienced practitioners to ensure that models are applied correctly and ethically. Concerns around data privacy, potential biases in decision-making, and the overall transparency of AI systems also pose significant hurdles. As AutoML continues to evolve, addressing these ethical and practical challenges will be paramount to fully realizing its potential and ensuring its responsible use across industries.

Report Scope

The report analyzes the Automated Machine Learning (AutoML) market, presented in terms of market value (US$ Thousand). The analysis covers the key segments and geographic regions outlined below.

Segments

Component (Solutions, Services); Application (Data Processing, Feature Engineering, Model Selection, Model Ensembling, Other Applications); Vertical (BFSI, Retail & eCommerce, Healthcare & Life Sciences, IT & ITeS, Telecommunications, Manufacturing, Automotive & Transportation, Other Verticals).

Geographic Regions/Countries

World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Key Insights:

• Market Growth: Understand the significant growth trajectory of the AutoML Solutions segment, which is expected to reach US$5.6 Billion by 2030 with a CAGR of a 34.7%. The AutoML Services segment is also set to grow at 44.3% CAGR over the analysis period.
• Regional Analysis: Gain insights into the U.S. market, valued at $428.6 Million in 2024, and China, forecasted to grow at an impressive 36.2% CAGR to reach $1.5 Billion by 2030. Discover growth trends in other key regions, including Japan, Canada, Germany, and the Asia-Pacific.

Report Features:

• Comprehensive Market Data: Independent analysis of annual sales and market forecasts in US$ Million from 2024 to 2030.
• In-Depth Regional Analysis: Detailed insights into key markets, including the U.S., China, Japan, Canada, Europe, Asia-Pacific, Latin America, Middle East, and Africa.
• Company Profiles: Coverage of major players such as Alteryx, Inc., Amazon Web Services, Inc., Databricks, Inc., Dataiku SAS, DataRobot, Inc. and more.
• Complimentary Updates: Receive free report updates for one year to keep you informed of the latest market developments.

Why You Should Buy This Report:

• Detailed Market Analysis: Access a thorough analysis of the Global Automated Machine Learning (AutoML) Market, covering all major geographic regions and market segments.
• Competitive Insights: Get an overview of the competitive landscape, including the market presence of major players across different geographies.
• Future Trends and Drivers: Understand the key trends and drivers shaping the future of the Global Automated Machine Learning (AutoML) Market.
• Actionable Insights: Benefit from actionable insights that can help you identify new revenue opportunities and make strategic business decisions.

Key Questions Answered:

• How is the Global Automated Machine Learning (AutoML) Market expected to evolve by 2030?
• What are the main drivers and restraints affecting the market?
• Which market segments will grow the most over the forecast period?
• How will market shares for different regions and segments change by 2030?
• Who are the leading players in the market, and what are their prospects?

Some of the 23 major companies featured in this Automated Machine Learning (AutoML) market report include:

• Alteryx, Inc.
• Amazon Web Services, Inc.
• Databricks, Inc.
• Dataiku SAS
• DataRobot, Inc.
• dotData
• Google Cloud Platform
• IBM Corporation
• Microsoft Learn
• The MathWorks, Inc.