Global Automated Machine Learning (AutoML) Market Research Report 2025(Status and Outlook)

Report Overview

Automated Machine Learning (AutoML) refers to the process of automating the end-to-end process of applying machine learning to real-world problems. It involves automating the tasks of data preprocessing, feature engineering, model selection, and hyperparameter tuning, thereby enabling users with limited machine learning expertise to build high-performing models efficiently. AutoML platforms typically utilize techniques such as neural architecture search, reinforcement learning, and Bayesian optimization to automate the model building process. By democratizing machine learning, AutoML aims to make it more accessible to a broader audience, including business analysts, domain experts, and non-expert users.

The market for Automated Machine Learning (AutoML) is experiencing significant growth driven by several key factors. Firstly, the increasing demand for machine learning solutions across industries is fueling the adoption of AutoML platforms as they offer a faster and more cost-effective way to develop machine learning models. Secondly, the shortage of skilled data scientists and machine learning experts is driving organizations to turn to AutoML tools to bridge the talent gap and accelerate their machine learning initiatives. Additionally, the advancements in artificial intelligence and automation technologies are further propelling the development and adoption of AutoML solutions, making it easier for organizations to leverage the power of machine learning in their operations.

At the same time, the market for AutoML is witnessing a shift towards more specialized and industry-specific solutions to cater to the unique needs and requirements of different sectors. This trend is driven by the recognition that one-size-fits-all AutoML platforms may not always deliver optimal results for specific use cases or industries. As a result, vendors are increasingly focusing on developing industry-specific AutoML solutions tailored to domains such as healthcare, finance, retail, and manufacturing. This trend is expected to continue as organizations seek more customized and effective machine learning solutions to address their specific business challenges and opportunities.

The global Automated Machine Learning (AutoML) market size was estimated at USD 56.27 million in 2024 and is projected to reach USD 78.20 million by 2033, exhibiting a CAGR of 4.20% during the forecast period.

This report provides a deep insight into the global Automated Machine Learning (AutoML) market covering all its essential aspects. This ranges from a macro overview of the market to micro details of the market size, competitive landscape, development trend, niche market, key market drivers and challenges, SWOT analysis, Porter's five forces analysis, value chain analysis, PEST analysis, etc.

The analysis helps the reader to shape the competition within the industries and strategies for the competitive environment to enhance the potential profit. Furthermore, it provides a simple framework for evaluating and accessing the position of the business organization. The report structure also focuses on the competitive landscape of the Global Automated Machine Learning (AutoML) Market, this report introduces in detail the market share, market performance, product situation, operation situation, etc. of the main players, which helps the readers in the industry to identify the main competitors and deeply understand the competition pattern of the market.

In a word, this report is a must-read for industry players, investors, researchers, consultants, business strategists, and all those who have any kind of stake or are planning to foray into the Automated Machine Learning (AutoML) market in any manner.

Global Automated Machine Learning (AutoML) Market: Market Segmentation Analysis

The research report includes specific segments by region (country), manufacturers, Type, and Application. Market segmentation creates subsets of a market based on product type, end-user or application, Geographic, and other factors. By understanding the market segments, the decision-maker can leverage this targeting in the product, sales, and marketing strategies. Market segments can power your product development cycles by informing how you create product offerings for different segments.

Key Company

Amazon Web Services Inc.

DataRobot

EdgeVerve Systems Limited

H20.ai Inc.

IBM

JADBio - Gnosis DA S.A.

QlikTech International AB

Auger

Google

Microsoft

SAS Institute lnc.

Market Segmentation (by Type)

Platform

Service

Market Segmentation (by Application)

Large Enterprise

SMEs

Geographic Segmentation

North America (USA, Canada, Mexico)

Europe (Germany, UK, France, Russia, Italy, Rest of Europe)

Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Rest of Asia-Pacific)

South America (Brazil, Argentina, Columbia, Rest of South America)

The Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, South Africa, Rest of MEA)

Key Benefits of This Market Research:

Industry drivers, restraints, and opportunities covered in the study

Neutral perspective on the market performance

Recent industry trends and developments

Competitive landscape & strategies of key players

Potential & niche segments and regions exhibiting promising growth covered

Historical, current, and projected market size, in terms of value

In-depth analysis of the Automated Machine Learning (AutoML) Market

Overview of the regional outlook of the Automated Machine Learning (AutoML) Market:

Key Reasons to Buy this Report:

Access to date statistics compiled by our researchers. These provide you with historical and forecast data, which is analyzed to tell you why your market is set to change

This enables you to anticipate market changes to remain ahead of your competitors

You will be able to copy data from the Excel spreadsheet straight into your marketing plans, business presentations, or other strategic documents

The concise analysis, clear graph, and table format will enable you to pinpoint the information you require quickly

Provision of market value data for each segment and sub-segment

Indicates the region and segment that is expected to witness the fastest growth as well as to dominate the market

Analysis by geography highlighting the consumption of the product/service in the region as well as indicating the factors that are affecting the market within each region

Competitive landscape which incorporates the market ranking of the major players, along with new service/product launches, partnerships, business expansions, and acquisitions in the past five years of companies profiled

Extensive company profiles comprising of company overview, company insights, product benchmarking, and SWOT analysis for the major market players

The current as well as the future market outlook of the industry concerning recent developments which involve growth opportunities and drivers as well as challenges and restraints of both emerging as well as developed regions

Includes in-depth analysis of the market from various perspectives through Porter’s five forces analysis

Provides insight into the market through Value Chain

Market dynamics scenario, along with growth opportunities of the market in the years to come

Chapter Outline

Chapter 1 mainly introduces the statistical scope of the report, market division standards, and market research methods.

Chapter 2 is an executive summary of different market segments (by region, product type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the Automated Machine Learning (AutoML) Market and its likely evolution in the short to mid-term, and long term.

Chapter 3 makes a detailed analysis of the market's competitive landscape of the market and provides the market share, capacity, output, price, latest development plan, merger, and acquisition information of the main manufacturers in the market.

Chapter 4 is the analysis of the whole market industrial chain, including the upstream and downstream of the industry, as well as Porter's five forces analysis.

Chapter 5 introduces the latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.

Chapter 6 provides the analysis of various market segments according to product types, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.

Chapter 7 provides the analysis of various market segments according to application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.

Chapter 8 provides a quantitative analysis of the market size and development potential of each region from the consumer side and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.

Chapter 9 shares the main producing countries of Automated Machine Learning (AutoML), their output value, profit level, regional supply, production capacity layout, etc. from the supply side.

Chapter 10 introduces the basic situation of the main companies in the market in detail, including product sales revenue, sales volume, price, gross profit margin, market share, product introduction, recent development, etc.

Chapter 11 provides a quantitative analysis of the market size and development potential of each region during the forecast period.

Chapter 12 provides a quantitative analysis of the market size and development potential of each market segment during the forecast period.

Chapter 13 is the main points and conclusions of the report.