Automated Machine Learning Market

Automated Machine Learning Market Snapshot from 2024 to 2034

The automated machine learning market had an estimated market share worth USD 700 million in 2023, and it is predicted to reach a global market valuation of USD 42.2 billion by 2034, growing at a steady CAGR of 44.9% from 2024 to 2034.

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Automated Machine Learning Demand Outlook

• By streamlining the process of developing models, automated machine learning reduces the amount of time and money spent on activities like feature engineering, data preparation, and hyperparameter tuning.
• It democratizes AI, allowing non-experts to use resilient machine learning models to make data-driven decisions.
• These systems facilitate the smooth scaling of AI projects for enterprises by effectively managing different and big datasets.
• Automated machine learning promotes innovation and maintains an organization's competitiveness in ever-changing markets by enabling quick testing and iteration.

Report Attribute	Details
Estimated Market Value for 2023	USD 700 million
Expected Market Value for 2024	USD 1 billion
Projected Forecast Value for 2034	USD 42.2 billion
Anticipated Growth Rate from 2024 to 2034	44.9% CAGR

Automated Machine Learning Market Historical Analysis from 2019 to 2023 vs. Forecast Outlook from 2024 to 2034

The global demand for automated machine learning market was estimated to reach a valuation of USD 0.1 billion in 2019, according to a report from Future Market Insights (FMI). From 2019 to 2023, sales witnessed significant growth in the automated machine learning market, registering a CAGR of 48.2%.

Historical CAGR from 2019 to 2023	48.2%
Forecast CAGR from 2024 to 2034	44.9%

A driving factor is the growing intricacy of datasets, which calls for sophisticated analytics methods. Organizations may effectively extract important insights by using automated machine learning to handle a variety of data types, including unstructured, semi-structured, and structured data. This expertise is essential for being competitive in data-rich contexts across sectors.

Some important factors that will boost the market growth through 2034 are:

• Continuous advancements in AI algorithms and processing capacity will increase the capabilities and efficiency of automated machine learning.
• Better access to a wide range of quality datasets will accelerate the creation and uptake of automated machine learning solutions.
• Automated machine learning technology will be more widely invested in and used when there are clear and supportive regulatory environments.
• Enhanced cooperation between industries and technology suppliers will result in customized solutions and quicken market expansion.

Key Factors Driving the Automated Machine Learning Market

Shortage of Skilled Data Scientists to Push Companies towards Automated Machine Learning

The need to address the scarcity of qualified data scientists as well as machine learning specialists is a significant factor driving the market for automated machine learning. With the exponential expansion of data, the need for data-driven insights is outpacing the availability of expertise to meet that demand.

Automated machine learning platforms democratize AI by allowing non-experts to successfully design and deploy machine learning models. These platforms enable organizations to exploit AI technology without depending only on expensive and limited knowledge by automating repetitive jobs and simplifying complicated procedures. This accelerates the adoption of machine learning across multiple sectors.

Increasing Need for Data Driven Processes to Enhance the Global Demand

The growing need for data-driven decision-making across sectors is one of the factors driving the market for automated machine learning. Automated machine learning streamlines the model development process, which helps firms get useful insights from large datasets.

Organizations may gain a competitive advantage and accelerate the deployment of machine learning models by automating processes like feature engineering, data preparation, and model selection. The increased understanding of AI's ability to promote innovation and improve operational efficiency is another factor driving this need.

Factors that can impede the Market Growth

Data Privacy and Decoding Complicated Data to Impede Market Growth

The market for automated machine learning is constrained by issues with data privacy, the difficulty of interpreting complicated models, and the lack of qualified workers who can use AI technology efficiently. Widespread adoption is further hampered by difficulties integrating automated machine learning into current workflows and the requirement for open regulatory frameworks.

To fully realize the potential of automated machine learning across companies, overcoming these obstacles will require resolving ethical issues, improving model interpretability, and funding educational and training programs.

Category-wise Insights

This section focuses on providing detailed analysis of two particular market segments for automated machine learning, the dominant solution type and the significant automation type. The two main segments discussed below are standalone solution and feature engineering type.

Standalone Automated Machine Learning to Gain Popularity in the Next Decade

Solution Type	Standalone
CAGR from 2024 to 2034	44.7%

During the forecast period, the standalone segment is likely to garner a 44.7% CAGR. Standalone automated machine learning will gain popularity as firms seek simplified AI solutions that do not require large infrastructure. With their intuitive interfaces and comprehensive automation, these stand-alone systems let companies quickly implement machine learning models with no technical knowledge.

These technologies, which emphasize the democratization of AI, enable users from all industries to take use of sophisticated analytics, promoting efficiency and creativity. Standalone solutions are flexible and scalable, meeting a range of business requirements and hastening the global adoption of AI technology.

By Automation Type, Feature Engineering to gain Popularity in 2024

Automation Type	Feature Engineering
Market Share in 2024	44.5%

In 2024, the feature engineering segment is likely to acquire a 52.4% global market share. Feature engineering will gain popularity in the global automated machine learning market owing to its importance in improving model performance and interpretability. With organizations placing a growing emphasis on gleaning insightful information from intricate datasets, automated feature engineering techniques will become indispensable.

These tools allow speedier model building and deployment by automating the process of choosing, manipulating, and producing features. This helps firms stay competitive in a data-driven environment and extract actionable insights more quickly.

Region-wise Analysis

The markets for automated machine learning in a few significant countries, including the United States, the United Kingdom, China, Japan, and South Korea, will be covered in detail in this section. The section will focus on the primary reasons driving up demand for automated machine learning in these countries.

Countries	CAGR from 2024 to 2034
The United States	45%
The United Kingdom	46.1%
China	45.4%
Japan	46%
South Korea	47.2%

Government Funding in the United States to Enhance Demand for Automated Machine Learning Solutions

The United States automated machine learning is anticipated to gain a CAGR of 45% through 2034. Factors that are bolstering the growth are:

• As a center of the world's technology, the United States significantly advances AI research and development by promoting the application of automated machine learning in sectors such as Silicon Valley.
• American businesses boost efficiency and competitiveness in a changing market by incorporating automated machine learning within their operations for supply chain optimization, customer analytics, and predictive maintenance.
• In an effort to strengthen national security and enhance citizen services, the United States also utilizes automated machine learning applications in public services, healthcare, and military with government funding and assistance.

Prevalence of a Robust Financial Sector in the United Kingdom to encourage Automated Machine Learning Uptake

The market in the United Kingdom is expected to expand with a 46.1% CAGR through 2034. The factors pushing the growth are:

• The financial services sector in the United Kingdom uses automated machine learning to improve operational efficiency and regulatory compliance through fraud detection, risk management, and algorithmic trading.
• In order to improve healthcare outcomes and efficiency while alleviating demand on healthcare systems, the United Kingdom is adopting automated machine learning to assist with patient evaluation, therapy optimization, and resource allocation.
• From retail to energy, the various sectors of the country use automated machine learning for predictive analytics, consumer segmentation, and process optimization to boost productivity and competitiveness.

A Robust Digital Economy to Spur Industry Growth in China

The automated machine learning ecosystem in China is anticipated to develop with a 45.4% CAGR from 2024 to 2034. The drivers behind this growth are:

• China's enormous population and digital economy create massive amounts of data on a daily basis. In order to effectively analyze this data and derive insights for company improvement and innovation, automated machine learning is essential.
• The government actively encourages the development of AI, creating an atmosphere that is favorable to the adoption of automated machine learning. Companies are encouraged to use AI technology for competitiveness and economic growth through investments and policies.
• The rapidly expanding e-commerce industry in China mostly relies on data-driven decision-making. E-commerce systems may customize suggestions, improve user experiences, and optimize marketing campaigns with automated machine learning, which increases revenue and establishes a dominant market position.

Precision and Efficiency in Manufacturing in Japan to bolster Demand

The automated machine learning industry in Japan is anticipated to reach a 46% CAGR from 2024 to 2034. The drivers propelling growth forward are:

• Precision and efficiency are highly valued in the manufacturing industry in Japan, which fuels the need for automated machine learning to streamline workflows, improve product quality, and save expenses.
• Japan is looking for automated machine learning solutions for analyzing healthcare data more effectively due to its aging population. These solutions would help with illness prediction, individualized therapies, and better healthcare outcomes.
• Japan is a robotics pioneer that uses automated machine learning to improve robotic capabilities. This allows robots to make intelligent decisions and adapt to changing settings in both the industrial and service sectors.

Increasing Amount of Complicated Data in South Korea to Enhance Demand

The automated machine learning ecosystem in South Korea is likely to attain a 47.2% CAGR during the forecast period. The factors bolstering the growth are:

• The various sectors in South Korea are dealing with growing amounts of complicated data, which calls for automated machine learning to effectively manage processes like model selection, data pretreatment, and optimization to produce insights that can be put to use.
• Due to the lack of qualified data scientists in the nation, there is a demand for automated machine learning systems that let non-experts use AI for creativity and decision-making.
• South Korean businesses look for effective ways to use their data in order to stay competitive. With expedited procedures provided by automated machine learning, businesses may swiftly use predictive models and obtain a competitive advantage.

Market Competition

Companies are concentrating on creating platforms and solutions to democratize and simplify the machine learning process in the global automated machine learning market. Their goal is to enable companies with less data science experience to take full advantage of artificial intelligence (AI). These companies provide tools for automating a range of processes, including as feature engineering, model selection, hyperparameter tweaking, and data preparation.

They provide services to a range of sectors, including manufacturing, healthcare, retail, and finance, allowing them to effectively gather insights and make data-driven choices. These companies offer adaptable solutions designed to meet particular company requirements, placing a strong emphasis on user-friendly interfaces and reliable performance to increase accessibility and adoption. The key players in this market include:

• Datarobot Inc.
• Amazon web services Inc.
• dotData Inc.
• IBM Corporation
• Dataiku
• SAS Institute Inc.
• Microsoft Corporation
• Google LLC
• H2O.ai
• Aible Inc.

Significant advancements in the automated machine learning sector are being made by key market participants, and these include:

• In 2023, the pioneer of value-driven artificial intelligence, DataRobot, unveiled new end-to-end capabilities meant to reduce the uncertainty gap in generative AI, speed the development of AI solutions, and increase their practical use. The DataRobot AI Platform has been enhanced to enable enterprises to govern with complete transparency, operate with accuracy and control, and grow quickly and optionally.
• In 2023, DotData, an innovation leader and top supplier of feature discovery platforms, made dotData Feature Factory available to the general public. With the help of reusable feature discovery assets that were previously unavailable, the recently released platform offers data scientists expanded capability that enables them to approach feature engineering from a data-centric perspective. DotData Py, a Python-based data science automation engine that was initially released in 2018, will be replaced by dotData Feature Factory, which allows a paradigm change in business data solutions.

Report Scope

Report Attribute	Details
Growth Rate	CAGR of 44.9% from 2024 to 2034
Market value in 2024	USD 1 billion
Market value in 2034	USD 42.2 billion
Base Year for Estimation	2023
Historical Data	2019 to 2023
Forecast Period	2024 to 2034
Quantitative Units	USD billion for value
Report Coverage	Revenue Forecast, Company Ranking, Competitive Landscape, Growth Factors, Trends, and Pricing Analysis
Segments Covered	Solution, Automation Type, End User, Region
Regions Covered	North America; Latin America; Western Europe; Eastern Europe; South Asia and Pacific; East Asia; The Middle East & Africa
Countries Profiled	The United States, Canada, Brazil, Mexico, Germany, The United Kingdom, France, Spain, Italy, Poland, Russia, Czech Republic, Romania, India, Bangladesh, Australia, New Zealand, China, Japan, South Korea, GCC Countries, South Africa, Israel
Key Companies Profiled	Datarobot Inc.; Amazon Web Services Inc.; dotData Inc.; IBM Corporation; Dataiku; SAS Institute Inc.; Microsoft Corporation; Google LLC; H2O.ai; Aible Inc.
Customization Scope	Available on Request

Table of Content

• 1. Executive Summary
• 2. Market Overview
• 3. Market Background
• 4. Global Market Analysis 2019 to 2023 and Forecast, 2024 to 2034
• 5. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Solution
  • 5.1. Standalone
  • 5.2. On-Premises
• 6. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Automation Type
  • 6.1. Feature Engineering
  • 6.2. Data Processing
  • 6.3. Data Modelling
  • 6.4. Visualization
  • 6.5. Others
• 7. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By End-User
  • 7.1. BFSI
  • 7.2. Retail and E-Commerce
  • 7.3. Healthcare
  • 7.4. Manufacturing
  • 7.5. Others
• 8. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Region
  • 8.1. North America
  • 8.2. Latin America
  • 8.3. Western Europe
  • 8.4. Eastern Europe
  • 8.5. South Asia and Pacific
  • 8.6. East Asia
  • 8.7. Middle East and Africa
• 9. North America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 10. Latin America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 11. Western Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 12. Eastern Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 13. South Asia and Pacific Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 14. East Asia Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 15. Middle East and Africa Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country
• 16. Key Countries Market Analysis
• 17. Market Structure Analysis
• 18. Competition Analysis
  • 18.1. Datarobot Inc.
  • 18.2. Amazon Web Services Inc.
  • 18.3. dotData Inc.
  • 18.4. IBM Corporation
  • 18.5. Dataiku
  • 18.6. SAS Institute Inc.
  • 18.7. Microsoft Corporation
  • 18.8. Google LLC
  • 18.9. H2O.ai
  • 18.10. Aible Inc.
• 19. Assumptions & Acronyms Used
• 20. Research Methodology