Automated Machine Learning (AutoML) Market Size to Reach USD 22,837.7 Million in 2032

KOLKATA, India - March 13, 2026 - PRLog -- Growing reliance on AI and data-driven decision making is a major driver of revenue growth in the Automated Machine Learning (AutoML) market. AutoML platforms simplify model development by automating tasks such as feature engineering, algorithm selection, hyperparameter tuning, and validation.

In September 2023, Fujitsu Limited, working with the Linux Foundation, introduced its automated machine learning and AI fairness technologies as open-source solutions. This move gives users access to tools that can automatically create code for new machine learning models and detect or reduce hidden biases in training datasets.

However, Limited transparency and model interpretability are restraining revenue growth in the Automated Machine Learning (AutoML) market because many organizations hesitate to deploy automated models they cannot fully understand or validate. AutoML tools sometimes generate complex algorithms through automated processes, making it difficult for users to trace how specific decisions or predictions are made.

Segments Market Overview and Growth Insights:
Based on algorithm type, the Automated Machine Learning (AutoML) market is segmented into supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, deep learning and others.

The supervised learning segment accounted for the largest share in 2024, driven by its expanding use across multiple industries and its straightforward implementation. These algorithms play a key role in classification, regression, and predictive tasks, supporting critical functions such as fraud detection, quality control, demand forecasting, and customer segmentation.

Regional Market Overview and Growth Insights:
North America held the largest revenue share in 2024, supported by strong uptake of artificial intelligence and data-centric technologies across major sectors such as healthcare, finance, retail, and manufacturing. In March 2025, Oracle and NVIDIA announced a significant partnership that combines NVIDIA's accelerated computing and inference capabilities with Oracle's AI infrastructure and generative AI services. This integration enables enterprises using Oracle Cloud and NVIDIA's computing stack to streamline and automate complex ML processes with higher efficiency and precision.

Competitive Landscape and Key Competitors
List of major players included in the market report are Microsoft Corporation, Google, DataRobot, H2O.ai, Amazon Web Services, IBM Corporation, Dataiku, BigML, Inc., dotData Inc., and others.

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