Automated Machine Learning (AutoML) Market

Automated Machine Learning Market Share & Size: Outlook & Growth

At a compound annual growth rate (CAGR) of 44.6%, the market for automated machine learning is projected to expand from USD 1.0 billion in 2023 to USD 6.4 billion by 2028. Under the umbrella of artificial intelligence (AI), automated machine learning (AutoML) allows users to develop machine learning applications without needing to have a deep understanding of machine learning and statistics. It streamlines the process of developing high-performance machine learning applications, which in the past required domain specialists and professional data scientists. AutoML has advanced significantly in the last several years as a result of advances in data science and AI.

Growth Factors for the Automated Machine Learning Market:

  • Increasing Demand for AI Solutions
  • Shortage of Data Science Skills
  • Advancements in AI and Machine Learning Technologies
  • Democratization of AI
  • Integration with Business Processes
  • Cost and Time Savings
  • Scalability and Flexibility

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Increasing Demand for AI Solutions:

  • The rising demand across industries for AI-driven insights and automation fuels the adoption of Automated Machine Learning (AutoML) solutions. Businesses seek to leverage AI to enhance decision-making, operational efficiency, and customer experiences.

Shortage of Data Science Skills:

  • The scarcity of skilled data scientists and machine learning engineers drives the need for AutoML platforms that automate complex tasks such as model selection, hyperparameter tuning, and feature engineering. This enables organizations to utilize AI capabilities without extensive expertise.

Advancements in AI and Machine Learning Technologies:

  • Continuous advancements in AI and machine learning algorithms, coupled with improvements in computing power, facilitate the development of more efficient and accurate AutoML models. Enhanced algorithms enable automated feature extraction, model training, and optimization.

Democratization of AI:

  • AutoML platforms democratize AI by making machine learning accessible to a broader range of users, including business analysts and domain experts. User-friendly interfaces and automated workflows empower non-technical users to build and deploy machine learning models independently.

Integration with Business Processes:

  • Integration of AutoML capabilities into existing business intelligence (BI) tools and workflows enhances data-driven decision-making. Seamless integration enables organizations to derive actionable insights from data more efficiently and effectively.

Cost and Time Savings:

  • AutoML platforms reduce the time and resources required for developing machine learning models manually. Automated processes for data preprocessing, model selection, and deployment accelerate time-to-insight, enabling faster innovation and time-sensitive decision-making.

Scalability and Flexibility:

  • Cloud-based AutoML solutions offer scalability and flexibility, allowing organizations to handle large datasets and fluctuating workloads. Cloud infrastructure supports the deployment of AI models at scale, accommodating growing business needs and operational demands.

Automated Machine Learning Market Share - Global Industry Landscape

The leading companies in the Automated Machine Learning industry and their key offerings include:

  • Teradata (US)
  • ai (US)
  • DataRobot (US)
  • BigML (US)
  • Databricks (US)

The Automated Machine Learning (AutoML) space is rapidly evolving, with several key players. Top contenders include DataRobot, Google Cloud AutoML,, and Databricks. These companies offer tools that automate various stages of the machine learning workflow, making it easier for businesses to build and deploy models without needing a team of data scientists. This democratizes machine learning, allowing even non-experts to harness its power.

Teradata (US)

Market Share:

  • Teradata is a significant player in the data analytics and cloud data warehousing market, known for its enterprise-grade solutions and global presence.

Key Offerings:

  • Vantage Platform: Teradata Vantage is a cloud-based analytics platform that integrates data analytics, data lakes, and data warehousing capabilities. It supports advanced analytics, machine learning, and AI-driven insights.
  • Data Warehousing: Teradata offers scalable data warehousing solutions for managing large-scale data environments and enabling real-time analytics.
  • Analytics Solutions: Advanced analytics solutions for predictive modeling, customer segmentation, and operational analytics across various industries including finance, healthcare, and retail. (US)

Market Share:

  • ai is a leading provider of open-source machine learning and AI platforms, recognized for its innovations in AI-driven solutions and predictive analytics.

Key Offerings:

  • H2O Driverless AI: Automated machine learning platform that accelerates data science workflows, including feature engineering, model selection, and hyperparameter optimization.
  • H2O-3: Open-source machine learning platform for building and deploying machine learning models at scale, integrating with popular programming languages and frameworks.
  • AI Applications: Industry-specific AI applications and solutions for sectors such as financial services, healthcare, insurance, and telecommunications.

DataRobot (US)

Market Share:

  • DataRobot is a prominent player in the AutoML and AI-driven decision intelligence market, offering automated machine learning solutions for enterprises.

Key Offerings

  • Automated Machine Learning: DataRobot provides a comprehensive AutoML platform for automating data preparation, feature engineering, model training, and deployment.
  • AI Cloud: DataRobot AI Cloud offers scalable and secure cloud-based AI solutions, enabling organizations to deploy and manage machine learning models in production.
  • Industry Solutions: AI-driven solutions tailored for various industries, including retail, healthcare, financial services, and manufacturing, to optimize business processes and decision-making.

BigML (US)

Market Share:

  • BigML is known for its cloud-based machine learning platform that emphasizes ease of use and accessibility for businesses of all sizes.

Key Offerings:

  • Machine Learning Platform: BigML offers a user-friendly machine learning platform for building and deploying predictive models without requiring extensive programming skills.
  • Automated Model Optimization: Tools for automated model selection, hyperparameter tuning, and ensemble learning techniques to improve model accuracy and performance.
  • Integration and Customization: APIs and integrations with other data platforms and tools, enabling seamless data flow and integration with existing workflows.

Databricks (US)

Market Share:

  • Databricks is a leading provider of unified data analytics and AI platforms, based on Apache Spark, known for its scalability and real-time data processing capabilities.

Key Offerings:

  • Unified Analytics Platform: Databricks offers a unified platform for data engineering, data science, and machine learning, leveraging Apache Spark for scalable data processing and analytics.
  • Delta Lake: Open-source storage layer for data lakes that ensures reliability, data consistency, and ACID transactions for big data analytics.
  • AI and Machine Learning: Tools and libraries for developing and deploying AI and machine learning models at scale, supporting AutoML, deep learning, and real-time analytics.

These companies represent leading innovators in the data analytics, machine learning, and AI markets, providing advanced solutions to meet diverse business needs and industry challenges globally.

Related Reports:

Automated Machine Learning (AutoML) Market by Offering (Solutions & Services), Application (Data Processing, Model Selection, Hyperparameter Optimization & Tuning, Feature Engineering, Model Ensembling), Vertical and Region - Global Forecast to 2028

Automated Machine Learning (AutoML) Market Size,  Share & Growth Report
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