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PUBLISHER: Global Market Insights Inc. | PRODUCT CODE: 1517578

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PUBLISHER: Global Market Insights Inc. | PRODUCT CODE: 1517578

Automated Machine Learning (AutoML) Market Size - By Offering, By Deployment Mode, By Enterprise Size, By Application, By End-User & Forecast, 2024 - 2032

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Global Automated Machine Learning (AutoML) Market will observe a CAGR of over 30% from 2024 to 2032 due to rising strategic conversations between business leaders. These collaborations combine expertise in AI, data science, and cloud computing to innovate and deliver robust AutoML solutions. Through integration, leading companies are enhancing their platforms with automated model building, feature engineering, and hyperparameter optimization capabilities.

For instance, in September 2023, Fujitsu Limited, in collaboration with the Linux Foundation, officially launched its automated machine learning and AI fairness technologies as open-source software (OSS) ahead of the Open Source Summit Europe 2023 in Bilbao, Spain. These initiatives, named SapientML and Intersectional Fairness,aim to provide users with tools that automatically generate code for new machine learning models and address biases in training data.

This connectivity is accelerating the adoption of AI in industries such as healthcare, finance, and retail, where robust data analytics are essential. These partnerships also expand market reach, enabling solutions tailored to the needs of customers, from start-ups to enterprise-level organizations. As competition intensifies, alliances in the AutoML market support innovation in predictive analytics and machine learning, improving efficiency and scalability. Ultimately, these partnerships spur technological advancements and make AI-driven insights accessible.

Overall Automated Machine Learning (AutoML) Industry size is classified based on offering, deployment mode, enterprise size, application, end-user, and region.

The Automated Machine Learning (AutoML) market revenue from the service segment will register a commendable CAGR from 2024 to 2032. The services are popular due to the need for basic skills in implementing and managing machine learning models. Professionals provide consulting, modification, and implementation management to create customized AutoML solutions for various industries. Companies are using these services to speed up prototyping, improve accuracy, and better integrate AI into their operations. With an increasing emphasis on data-driven decision-making, companies increasingly rely on service providers to navigate the challenges of implementing AI, ensuring flexibility and compliance. As demand for sophisticated AI capabilities increases, the AutoML market service segment continues to expand.

The on-premises segment will witness an appreciable growth from 2024 to 2032. The demand for on-premises solutions addresses an organization's prioritization of data privacy, security, and compliance. AutoML platforms on campus give enterprises greater control over their data and workflow, ensuring critical information stays within their infrastructure. This deployment model is also attractive to industries such as healthcare, finance, and government, where strict rules are important. By adopting on-premise AutoML solutions, businesses increase operational efficiencies, reduce data processing time, and comply with local and international data protection regulations. While organizations reduce the risk required to leverage AI capabilities, the demand for location-based AutoML solutions continues to grow.

Asia Pacific automated machine learning (AutoML) market will exhibit a notable CAGR from 2024 to 2032. The demand in the region is driven by rapid digital transformation and increasing adoption of AI technologies. Businesses in manufacturing, healthcare, and retail use AutoML to streamline operations, improve decision-making processes, and gain competitive advantage. With a focus on scalability and efficiency, AutoML solutions meet business needs in a dynamic market environment. Governments' policies to promote AI innovation support partnerships and investments in AI capabilities, further stimulating market growth. As Asia Pacific economies embrace AI-powered insights, the demand for AutoML solutions continues to expand, shaping the future of new industries.

Product Code: 9033

Table of Contents

Chapter 1 Methodology & Scope

  • 1.1 Research design
    • 1.1.1 Research approach
    • 1.1.2 Data collection methods
  • 1.2 Base estimates and calculations
    • 1.2.1 Base year calculation
    • 1.2.2 Key trends for market estimates
  • 1.3 Forecast model
  • 1.4 Primary research & validation
    • 1.4.1 Primary sources
    • 1.4.2 Data mining sources
  • 1.5 Market definitions

Chapter 2 Executive Summary

  • 2.1 Industry 360 degree synopsis, 2021 - 2032

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
  • 3.2 Supplier landscape
    • 3.2.1 Technology providers
    • 3.2.2 Service providers
    • 3.2.3 Platform providers
    • 3.2.4 End users
  • 3.3 Profit margin analysis
  • 3.4 Technology & innovation landscape
  • 3.5 Patent analysis
  • 3.6 Key news & initiatives
  • 3.7 Regulatory landscape
  • 3.8 Impact forces
    • 3.8.1 Growth drivers
      • 3.8.1.1 Growing demand for ai solutions
      • 3.8.1.2 Shortage of skilled data scientists
      • 3.8.1.3 Rise in the integration with cloud services
      • 3.8.1.4 Rise in the customization options and flexibility
    • 3.8.2 Industry pitfalls & challenges
      • 3.8.2.1 Raising concerns about data privacy
      • 3.8.2.2 Complexity of data and models
  • 3.9 Growth potential analysis
  • 3.10 Porter's analysis
  • 3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

  • 4.1 Introduction
  • 4.2 Company market share analysis
  • 4.3 Competitive positioning matrix
  • 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Offering 2021 - 2032 ($Mn)

  • 5.1 Key trends
  • 5.2 Solution
  • 5.3 Service
    • 5.3.1 Consulting
    • 5.3.2 Integration
    • 5.3.3 Deployment

Chapter 6 Market Estimates & Forecast, By Deployment Mode, 2021 - 2032 ($Mn)

  • 6.1 Key trends
  • 6.2 Cloud
  • 6.3 On-premises

Chapter 7 Market Estimates & Forecast, By Enterprise size, 2021 - 2032 ($Mn)

  • 7.1 Key trends
  • 7.2 SMEs
    • 7.2.1 Solution
    • 7.2.2 Service
      • 7.2.2.1 Consulting
      • 7.2.2.2 Integration
      • 7.2.2.3 Deployment
  • 7.3 Large enterprises
    • 7.3.1 Solution
    • 7.3.2 Service
      • 7.3.2.1 Consulting
      • 7.3.2.2 Integration
      • 7.3.2.3 Deployment

Chapter 8 Market Estimates & Forecast, By Application, 2021 - 2032 ($Mn)

  • 8.1 Key trends
  • 8.2 Data processing
  • 8.3 Feature engineering
  • 8.4 Model selection
  • 8.5 Hyperparameter optimization & tuning
  • 8.6 Model ensemble
  • 8.7 Others

Chapter 9 Market Estimates & Forecast, By End-User, 2021 - 2032 ($Mn)

  • 9.1 Key trends
  • 9.2 IT & telecommunications
  • 9.3 BFSI
  • 9.4 Retail
  • 9.5 Automotive
  • 9.6 Media & entertainment
  • 9.7 Others

Chapter 10 Market Estimates & Forecast, By Region, 2021 - 2032 ($Mn)

  • 10.1 Key trends
  • 10.2 North America
    • 10.2.1 U.S.
    • 10.2.2 Canada
  • 10.3 Europe
    • 10.3.1 UK
    • 10.3.2 Germany
    • 10.3.3 France
    • 10.3.4 Italy
    • 10.3.5 Russia
    • 10.3.6 Spain
    • 10.3.7 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 China
    • 10.4.2 Japan
    • 10.4.3 India
    • 10.4.4 South Korea
    • 10.4.5 Australia
    • 10.4.6 Southeast Asia
    • 10.4.7 Rest of Asia Pacific
  • 10.5 Latin America
    • 10.5.1 Brazil
    • 10.5.2 Mexico
    • 10.5.3 Argentina
    • 10.5.4 Rest of Latin America
  • 10.6 MEA
    • 10.6.1 UAE
    • 10.6.2 South Africa
    • 10.6.3 Saudi Arabia
    • 10.6.4 Rest of MEA

Chapter 11 Company Profiles

  • 11.1 Alphabet Inc.
  • 11.2 Alteryx
  • 11.3 Amazon Web Services, Inc.
  • 11.4 Auger.AI
  • 11.5 BigML
  • 11.6 DarwinAI
  • 11.7 Databricks AutoML
  • 11.8 Dataiku
  • 11.9 DataRobot MLOps
  • 11.10 DataRobot Paxata
  • 11.11 DataRobot, Inc.
  • 11.12 DotData
  • 11.13 Feature Labs
  • 11.14 H2O.ai
  • 11.15 HPE Haven OnDemand
  • 11.16 IBM Corporation
  • 11.17 KNIME
  • 11.18 Microsoft
  • 11.19 RapidMiner Auto Model
  • 11.20 TIBCO Software Inc.
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