The Automated Machine Learning market is experiencing robust growth, projected to achieve a compound annual growth rate CAGR of 22.30% during the forecast period. Valued at 4.7 Billion, the market is expected to reach 13.6 Billion by 2033, with a year-on-year growth rate of N/A. This upward trajectory is driven by factors such as evolving consumer preferences, technological advancements, and increased investment in innovation, positioning the market for significant expansion in the coming years. Companies should strategically focus on enhancing their offerings and exploring new market opportunities to capitalize on this growth potential.

The automated machine learning (AutoML) market provides AI and machine learning solutions that enable non-experts to build and deploy predictive models without coding. As demand for AI-driven solutions rises across industries such as healthcare, retail, and finance, the market for AutoML is growing rapidly due to its ability to simplify and speed up the development of machine learning models.

Regulatory Landscape

• • Regulations focus on data privacy

The Information and Communications Technology (ICT) industry is primarily regulated by the Federal Communications Commission (FCC) in the United States, along with other national and international regulatory bodies. The FCC oversees the allocation of spectrum, ensures compliance with telecommunications laws, and fosters fair competition within the sector. It also establishes guidelines for data privacy, cybersecurity, and service accessibility, which are crucial for maintaining industry standards and protecting consumer interests.
Globally, various regulatory agencies, such as the European Telecommunications Standards Institute (ETSI) and the International Telecommunication Union (ITU), play significant roles in standardizing practices and facilitating international cooperation. These bodies work together to create a cohesive regulatory framework that addresses emerging technologies, cross-border data flow, and infrastructure development. Their regulations aim to ensure the ICT industry's growth is both innovative and compliant with global standards, promoting a secure and competitive market environment.

•    The Automated Machine Learning is growing at a CAGR of 22.30% during the forecasted period of 2020 to 2033
•    Year on Year growth for the market is N/A
•    Based on type, the market is bifurcated into AutoML Platforms, Hyperparameter Tuning Tools, Model Deployment Tools, Feature Engineering Solutions, Data Preprocessing Solutions
•    Based on application, the market is segmented into AI, Healthcare, Retail, Finance, Marketing
•    Global Import Export in terms of K Tons, K Units, and Metric Tons will be provided if Applicable based on industry best practice

• • AutoML Platforms
• • Hyperparameter Tuning Tools
• • Model Deployment Tools
• • Feature Engineering Solutions
• • Data Preprocessing Solutions

 

• • AI
• • Healthcare
• • Retail
• • Finance
• • Marketing

Several key players in the Automated Machine Learning market are strategically focusing on expanding their operations in developing regions to capture a larger market share, particularly as the year-on-year growth rate for the market stands at N/A. The companies featured in this profile were selected based on insights from primary experts, evaluating their market penetration, product offerings, and geographical reach. By targeting emerging markets, these companies aim to leverage new opportunities, enhance their competitive advantage, and drive revenue growth. This approach not only aligns with their overall business objectives but also positions them to respond effectively to the evolving demands of consumers in these regions.

• • Google (USA)
• • Microsoft (USA)
• • IBM (USA)
• • Amazon Web Services (USA)
• • H2O.ai (USA)
• • DataRobot (USA)
• • BigML (USA)
• • RapidMiner (Germany)
• • Alteryx (USA)
• • SAS Institute (USA)
• • TIBCO Software (USA)
• • KNIME (Switzerland)
• • Anaconda (USA)
• • Domino Data Lab (USA)
• • Peltarion (Sweden)
• • Cogito (USA)
• • SigOpt (USA)
• • Dataiku (USA)
• • OpenAI (USA)
• • Seldon (UK)

At HTF Market Intelligence, we pride ourselves on delivering comprehensive market research that combines both secondary and primary methodologies. Our secondary research involves rigorous analysis of existing data sources, such as industry reports, market databases, and competitive landscapes, to provide a robust foundation of market knowledge. This is complemented by our primary research services, where we gather firsthand data through surveys, interviews, and focus groups tailored specifically to your business needs. By integrating these approaches, we offer a thorough understanding of market trends, consumer behavior, and competitive dynamics, enabling you to make well-informed strategic decisions. We would welcome the opportunity to discuss how our research expertise can support your business objectives.

Market dynamics refer to the forces that influence the supply and demand of products and services within a market. These forces include factors such as consumer preferences, technological advancements, regulatory changes, economic conditions, and competitive actions. Understanding market dynamics is crucial for businesses as it helps them anticipate changes, identify opportunities, and mitigate risks.
By analyzing market dynamics, companies can better understand market trends, predict potential shifts, and develop strategic responses. This analysis enables businesses to align their product offerings, pricing strategies, and marketing efforts with evolving market conditions, ultimately leading to more informed decision-making and a stronger competitive position in the marketplace.

Market Driver

• • Increasing demand for AI and machine learning applications
• • rise in adoption of automated solutions for non-experts
• • growing need for scalable AI models
• • advancements in deep learning
• • increasing interest in AI-driven data analysis.

Market Trend

• • Growth in demand for AI-powered predictive analytics
• • increasing use of AutoML in healthcare
• • rise in AI-based automation in retail
• • growing use of AutoML in finance and marketing
• • increasing accessibility of machine learning models.

Opportunity

• • Expansion into emerging AI markets
• • increasing demand for simplified machine learning workflows
• • rise in demand for self-service AutoML platforms
• • development of automated model monitoring systems
• • growth in AutoML in low-code/no-code environments.

Challenge

• • Complexity in model interpretability
• • high dependency on data quality
• • lack of skilled professionals
• • integration challenges with legacy systems
• • potential bias in models.

Regional Analysis

• • North America and Europe are key markets for AutoML

Market Entropy

• • June 2024 – Google Cloud and Microsoft Azure introduced advanced automated machine learning platforms

Merger & Acquisition

• • May

Regulatory Landscape

• • Regulations focus on data privacy

Patent Analysis

• • Patents focus on innovations in machine learning algorithms

Investment and Funding Scenario

• • Investment in the AutoML market is strong as demand for AI-driven solutions across industries grows. Companies are focusing on improving platform performance

The North America Region holds the largest market share in 2025 and is expected to grow at a good CAGR. The Europe Region is the fastest-growing region due to increasing development and disposable income.

North America remains a leader, driven by innovation hubs like Silicon Valley and a strong demand for advanced technologies such as AI and cloud computing. Europe is characterized by robust regulatory frameworks and significant investments in digital transformation across sectors. Asia-Pacific is experiencing rapid growth, led by major markets like China and India, where increasing digital adoption and governmental initiatives are propelling ICT advancements.

The Middle East and Africa are witnessing steady expansion, driven by infrastructure development and growing internet penetration. Latin America and South America present emerging opportunities, with rising investments in digital infrastructure, though challenges like economic instability can impact growth. These regional differences highlight the need for tailored strategies in the global ICT market.
 

• North America
• LATAM
• West Europe
• Central & Eastern Europe
• Northern Europe
• Southern Europe
• East Asia
• Southeast Asia
• South Asia
• Central Asia
• Oceania
• MEA

Report Features	Details
Base Year	2025
Based Year Market Size (2025)	4.7 Billion
Historical Period Market Size (2020)	USD Million ZZ
CAGR (2025 to 2033)	22.30%
Forecast Period	2025 to 2033
Forecasted Period Market Size (2033)	13.6 Billion
Scope of the Report	AutoML Platforms, Hyperparameter Tuning Tools, Model Deployment Tools, Feature Engineering Solutions, Data Preprocessing Solutions, AI, Healthcare, Retail, Finance, Marketing
Regions Covered	North America, Europe, Asia Pacific, South America, and MEA
Year on Year Growth	N/A
Companies Covered	Google (USA), Microsoft (USA), IBM (USA), Amazon Web Services (USA), H2O.ai (USA), DataRobot (USA), BigML (USA), RapidMiner (Germany), Alteryx (USA), SAS Institute (USA), TIBCO Software (USA), KNIME (Switzerland), Anaconda (USA), Domino Data Lab (USA), Peltarion (Sweden), Cogito (USA), SigOpt (USA), Dataiku (USA), OpenAI (USA), Seldon (UK)
Customization Scope	15% Free Customization (For EG)
Delivery Format	PDF and Excel through Email