Global Automated Machine Learning AutoML
Market Report
2025
Automated Machine Learning (AutoML) market size is USD 989.95 million in 2024 and will expand at a compound annual growth rate (CAGR) of 28.1% from 2024 to 2031.
The base year for the calculation is 2024. The historical will be 2021 to 2024. The year 2025 will be estimated one while the forecasted data will be from year 2025 to 2033. When we deliver the report that time we updated report data till the purchase date.
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According to Cognitive Market Research, the global Automated Machine Learning (AutoML) market size is USD 989.95 million in 2024 and will expand at a compound annual growth rate (CAGR) of 28.1% from 2024 to 2031.
2024 | 2025 | 2032 | 2033 | CAGR | |
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Global Automated Machine Learning AutoML Market Sales Revenue | $ 989.95 Million | 121212 | 121212 | 121212 | 28.1% |
Base Year | 2024 |
Historical Data Time Period | 2021-2024 |
Forecast Period | 2025-2033 |
Market Split by Offering |
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Market Split by Application |
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Market Split by End User |
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List of Competitors |
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Regional Analysis |
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Country Analysis |
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Automated Machine Learning AutoML Market is Segmented as below. Particular segment of your interest can be provided without any additional cost. Download the Sample Pages!
The automated machine learning (AutoML) market is a rapidly evolving sector at the intersection of artificial intelligence (AI) and data science, revolutionizing the way organizations develop machine learning models. AutoML solutions streamline the machine learning pipeline, automating tasks such as data preprocessing, feature engineering, model selection, hyperparameter tuning, and model deployment. This democratization of machine learning enables users with varying levels of expertise to harness the power of AI without extensive programming or data science knowledge. The market offers a diverse range of AutoML platforms, tools, and services tailored to different use cases and industries, catering to the growing demand for scalable, efficient, and accessible AI solutions. With the exponential growth of data and the increasing importance of AI in business operations, the AutoML market is poised for substantial growth, empowering organizations to unlock valuable insights, optimize processes, and drive innovation through automated machine learning technologies.
Democratization of Machine Learning to Increase the Demand Globally - One key driver in the Automated Machine Learning (AutoML) market is the democratization of ML. Automated Machine Learning (AutoML) enables non-experts to leverage machine learning techniques without requiring extensive technical expertise. By automating the process of model selection, hyperparameter tuning, and feature engineering, AutoML platforms empower a broader range of users, including business analysts and domain experts, to build and deploy machine learning models effectively. Scalability and Efficiency- AutoML streamlines and accelerates the machine learning workflow, reducing the time and resources needed to develop and deploy models. This scalability and efficiency drive adoption across industries, allowing organizations to rapidly innovate, iterate, and scale their machine-learning initiatives to address diverse business challenges.
Complexity- The complexity of implementing and integrating AutoML solutions into existing workflows can limit market growth, as it requires significant expertise and resources to deploy and manage these technologies effectively. Data Quality and Availability- The availability of high-quality training data and the need for large, diverse datasets pose challenges for AutoML adoption, as inadequate or biased data can lead to suboptimal model performance and hinder market expansion.
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In February 2023, IBM integrated StepZen's technology into its portfolio, focusing on offering its clients an end-to-end solution for building, connecting, and managing APIs and data sources, allowing them to innovate faster and generate more value from their data.
(Source: https://www.ibm.com/in-en/about)
Top Companies Market Share in Automated Machine Learning AutoML Industry: (In no particular order of Rank)
If any Company(ies) of your interest has/have not been disclosed in the above list then please let us know the same so that we will check the data availability in our database and provide you the confirmation or include it in the final deliverables.
According to Cognitive Market Research, North America dominated the market in 2024. It accounted for around 40% of the global revenue as the region is home to a large number of technology companies, research institutions, and startups at the forefront of AI and machine learning innovation. Additionally, North America boasts a robust ecosystem of venture capital funding, providing ample investment opportunities for AutoML startups. Moreover, the presence of mature industries such as finance, healthcare, and technology fuels the demand for AI solutions, driving the widespread adoption of AutoML technologies across various sectors.
Asia-Pacific stands out as the fastest-growing region in the Automated Machine Learning (AutoML) market due to the rapid technological advancements, increasing adoption of AI and machine learning solutions across various industries, and the region's burgeoning startup ecosystem contributing to this growth. Additionally, the rising demand for automation to streamline business processes and the presence of a large untapped market with a growing number of enterprises seeking to enhance their analytics capabilities further fuel the expansion of the AutoML market in Asia Pacific.
The current report Scope analyzes Automated Machine Learning AutoML Market on 5 major region Split (In case you wish to acquire a specific region edition (more granular data) or any country Edition data then please write us on info@cognitivemarketresearch.com
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Global Automated Machine Learning AutoML Market Report 2025 Edition talks about crucial market insights with the help of segments and sub-segments analysis. In this section, we reveal an in-depth analysis of the key factors influencing Automated Machine Learning AutoML Industry growth. Automated Machine Learning AutoML market has been segmented with the help of its Offering, Application End User, and others. Automated Machine Learning AutoML market analysis helps to understand key industry segments, and their global, regional, and country-level insights. Furthermore, this analysis also provides information pertaining to segments that are going to be most lucrative in the near future and their expected growth rate and future market opportunities. The report also provides detailed insights into factors responsible for the positive or negative growth of each industry segment.
According to Cognitive Market Research, solution is the dominating category due to their ability to offer comprehensive, user-friendly platforms that streamline the machine learning process. Leading solutions excel in providing intuitive interfaces, automation of model selection and hyperparameter tuning, and seamless integration with existing data workflows. Moreover, solutions that offer scalability, robust performance across diverse datasets, and support for various machine learning algorithms gain a competitive edge. By empowering users with accessible tools to build and deploy machine learning models efficiently, these solutions drive market dominance, catering to the growing demand for AI capabilities across industries with minimal expertise required.
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Market segmentation by Application is another crucial element in understanding the dynamics of the Automated Machine Learning AutoML industry. Applications refer to the specific uses or end-user industries that drive demand for the Automated Machine Learning AutoML products or services. These can vary widely, depending on the nature of the market, ranging from healthcare, manufacturing, and retail to more specialized sectors like aerospace, automotive, and telecommunications. By breaking down the market according to its applications, businesses can gain insight into which industries are adopting Automated Machine Learning AutoML-related solutions most effectively, and where new opportunities are emerging.
Moreover, analyzing application trends helps in recognizing which industries are growing faster, where innovations are occurring, and which markets are saturated, allowing businesses to strategically position themselves in the most promising areas of the market. Get in touch with us to receive industry-specific insights tailored to your needs
Some of the key Application of Automated Machine Learning AutoML are:
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Research associate at Cognitive Market Research
Swasti Dharmadhikari, an agile and achievement-focused market researcher with an innate ardor for deciphering the intricacies of the Service & Software sector. Backed by a profound insight into technology trends and consumer dynamics, she has committed herself to meticulously navigating the ever-evolving terrain of digital Services and software solutions.
Swasti an agile and achievement-focused market researcher with an innate ardor for deciphering the intricacies of the Service & Software sector. Backed by a profound insight into technology trends and consumer dynamics, she has committed herself to meticulously navigating the ever-evolving terrain of digital Services and software solutions.
In her current role, Swasti manages research for service and software category, leading initiatives to uncover market opportunities and enhance competitive positioning. Her strong analytical skills and ability to provide clear, impactful findings have been crucial to her team’s success. With an expertise in market research analysis, She is adept at dissecting complex problems, extracting meaningful insights, and translating them into actionable recommendations, Swasti remains an invaluable asset in the dynamic landscape of market research.
Our study will explain complete manufacturing process along with major raw materials required to manufacture end-product. This report helps to make effective decisions determining product position and will assist you to understand opportunities and threats around the globe.
The Global Automated Machine Learning AutoML Market is witnessing significant growth in the near future.
In 2023, the Solutions segment accounted for noticeable share of global Automated Machine Learning AutoML Market and is projected to experience significant growth in the near future.
The Data Processing segment is expected to expand at the significant CAGR retaining position throughout the forecast period.
Some of the key companies IBM , Microsoft and others are focusing on its strategy building model to strengthen its product portfolio and expand its business in the global market.
Please note, we have not disclose, all the sources consulted/referred during a market study due to confidentiality and paid service concern. However, rest assured that upon purchasing the service or paid report version, we will release the comprehensive list of sources along with the complete report and we also provide the data support where you can intract with the team of analysts who worked on the report.
Disclaimer:
Offering | Solutions, Services |
Application | Data Processing, Feature Engineering, Model Selection, Hyperparameter Optimization & Tuning, Model Ensembling, Others |
End User | IT & Telecommunications, BFSI, Retail, Automotive, Media & Entertainment, Others |
List of Competitors | IBM, Oracle, Microsoft, ServiceNow, Google, Baidu, AWS (Amazon Web Services), Alteryx, Salesforce, Altair, Teradata, H2O.ai, DataRobot, BigML, Databricks, Dataiku, Alibaba Cloud, Appier, Squark, Aible, Datafold |
This chapter will help you gain GLOBAL Market Analysis of Automated Machine Learning AutoML. Further deep in this chapter, you will be able to review Global Automated Machine Learning AutoML Market Split by various segments and Geographical Split.
Chapter 1 Global Market Analysis
Global Market has been segmented on the basis 5 major regions such as North America, Europe, Asia-Pacific, Middle East & Africa, and Latin America.
You can purchase only the Executive Summary of Global Market (2019 vs 2024 vs 2031)
Global Market Dynamics, Trends, Drivers, Restraints, Opportunities, Only Pointers will be deliverable
This chapter will help you gain North America Market Analysis of Automated Machine Learning AutoML. Further deep in this chapter, you will be able to review North America Automated Machine Learning AutoML Market Split by various segments and Country Split.
Chapter 2 North America Market Analysis
This chapter will help you gain Europe Market Analysis of Automated Machine Learning AutoML. Further deep in this chapter, you will be able to review Europe Automated Machine Learning AutoML Market Split by various segments and Country Split.
Chapter 3 Europe Market Analysis
This chapter will help you gain Asia Pacific Market Analysis of Automated Machine Learning AutoML. Further deep in this chapter, you will be able to review Asia Pacific Automated Machine Learning AutoML Market Split by various segments and Country Split.
Chapter 4 Asia Pacific Market Analysis
This chapter will help you gain South America Market Analysis of Automated Machine Learning AutoML. Further deep in this chapter, you will be able to review South America Automated Machine Learning AutoML Market Split by various segments and Country Split.
Chapter 5 South America Market Analysis
This chapter will help you gain Middle East Market Analysis of Automated Machine Learning AutoML. Further deep in this chapter, you will be able to review Middle East Automated Machine Learning AutoML Market Split by various segments and Country Split.
Chapter 6 Middle East Market Analysis
This chapter will help you gain Middle East Market Analysis of Automated Machine Learning AutoML. Further deep in this chapter, you will be able to review Middle East Automated Machine Learning AutoML Market Split by various segments and Country Split.
Chapter 7 Africa Market Analysis
This chapter provides an in-depth analysis of the market share among key competitors of Automated Machine Learning AutoML. The analysis highlights each competitor's position in the market, growth trends, and financial performance, offering insights into competitive dynamics, and emerging players.
Chapter 8 Competitor Analysis (Subject to Data Availability (Private Players))
(Subject to Data Availability (Private Players))
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
This chapter would comprehensively cover market drivers, trends, restraints, opportunities, and various in-depth analyses like industrial chain, PESTEL, Porter’s Five Forces, and ESG, among others. It would also include product life cycle, technological advancements, and patent insights.
Chapter 9 Qualitative Analysis (Subject to Data Availability)
Segmentation Offering Analysis 2019 -2031, will provide market size split by Offering. This Information is provided at Global Level, Regional Level and Top Countries Level The report with the segmentation perspective mentioned under this chapters will be delivered to you On Demand. So please let us know if you would like to receive this additional data as well. No additional cost will be applicable for the same.
Chapter 10 Market Split by Offering Analysis 2021 - 2033
The report with the segmentation perspective mentioned under this chapters will be delivered to you On Demand. So please let us know if you would like to receive this additional data as well. No additional cost will be applicable for the same.
Chapter 11 Market Split by Application Analysis 2021 - 2033
The report with the segmentation perspective mentioned under this chapters will be delivered to you On Demand. So please let us know if you would like to receive this additional data as well. No additional cost will be applicable for the same.
Chapter 12 Market Split by End User Analysis 2021 - 2033
This chapter helps you understand the Key Takeaways and Analyst Point of View of the global Automated Machine Learning AutoML market
Chapter 13 Research Findings
Here the analyst will summarize the content of entire report and will share his view point on the current industry scenario and how the market is expected to perform in the near future. The points shared by the analyst are based on his/her detailed in-depth understanding of the market during the course of this report study. You will be provided exclusive rights to interact with the concerned analyst for unlimited time pre purchase as well as post purchase of the report.
Chapter 14 Research Methodology and Sources
Why Solutions have a significant impact on Automated Machine Learning AutoML market? |
What are the key factors affecting the Solutions and Services of Automated Machine Learning AutoML Market? |
What is the CAGR/Growth Rate of Data Processing during the forecast period? |
By type, which segment accounted for largest share of the global Automated Machine Learning AutoML Market? |
Which region is expected to dominate the global Automated Machine Learning AutoML Market within the forecast period? |
Segmentation Level Customization |
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Global level Data Customization |
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Region level Data Customization |
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Country level Data Customization |
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Company Level |
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Additional Data Analysis |
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Additional Qualitative Data |
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Additional Quantitative Data |
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Service Level Customization |
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Report Format Alteration |
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