The market for automated machine learning was valued at US$ 0.7 billion in 2023 and is projected to grow at a steady CAGR of 44.9% between 2024 and 2034 to reach a worldwide market size of US$ 42.2 billion. It is anticipated that the automated machine learning industry would be valued at $1 billion by 2024.
One of the key drivers is the increasing need for data-based insights, which is being driven by advancements in AI technology. The dearth of trained data scientists and the rapid growth of complicated information are driving the demand for automated solutions to streamline processes and fully use data analytics.
The potential for automated machine learning to democratize artificial intelligence and make it available to companies of all sizes presents opportunities. The industry has opportunities for innovation in specialized sectors like predictive maintenance and tailored healthcare. Growing applications in industries like retail and finance offer chances for expansion and diversification.
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Key Takeaways from the Market Analysis
- The global demand for automated machine learning reached US$ 100 million in 2019.
- The standalone segment is anticipated to develop at a 44.7% CAGR during the projection period.
- It is anticipated that the feature engineering category would reach a 52.4% global market share by 2024.
- It is projected that automated machine learning in the United States will advance at a CAGR of 45% by 2034.
- The market in the United Kingdom is anticipated to rise through 2034 at a 46.1% CAGR.
- China’s automated machine learning ecosystem will evolve at a 45.4% CAGR between 2024 and 2034.
“The growing need for data-driven decision-making, the development of AI technology, the scarcity of qualified data scientists, and the volume and complexity of data produced by companies are the factors propelling the automated machine learning market,” says an FMI analyst.
Competitive Landscape
Companies in the automated machine learning market concentrate on providing advisory services, subscription-based licensing models, and specialized solutions made to meet the demands of particular industries in order to increase income. In order to broaden their market reach and improve their product offerings, they participate in strategic alliances, mergers, and acquisitions.
Companies also spend money on marketing campaigns to spread the word about the advantages of automated machine learning and showcase their knowledge through training courses, conferences, and thought leadership.
Companies with minimal data science skills might benefit from the innovative user-friendly platforms that automated machine learning startups are creating to democratize AI. They set themselves apart by providing customized solutions for certain markets or use cases, such financial forecasts or medical diagnostics.
Key Developments
- In 2023, DataRobot updated its platform for developing machine learning applications, including AI accelerators and additional partner interfaces- DataRobot AI Platform 9.0. The platform serves as the core center of AI endeavors, providing tools for all of the essential coding and software deployment responsibilities associated with machine learning applications.
In November 2023, Amazon Web Services Inc. launched Amazon Q, a new form of generative AI-powered assistant designed exclusively for work and customizable to a customer’s needs. Based on their knowledge repositories, code, and corporate systems, customers may develop content, take action, and receive prompt, pertinent responses to urgent issues.
Key Segments Profiled in the Automated Machine Learning Market
By Solution:
- Standalone
- On-Premises
By Automation Type:
- Feature Engineering
- Data Processing
- Data Modelling
- Visualization
- Others
By End User:
- BFSI
- Retail and E-Commerce
- Healthcare
- Manufacturing
- Others
By Region:
- North America
- Latin America
- Western Europe
- Eastern Europe
- South Asia and Pacific
- East Asia
- Middle East & Africa
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