Automated machine learning uses artificial intelligence techniques to automatically select, optimize, and combine algorithms, models, and features to solve a machine learning problem. It reduces human involvement by automating the time-consuming and repetitive tasks related to data preprocessing, model building, evaluation, and parameter tuning. Automated ML streamlines the workflow and enables domain experts or data scientists with limited ML expertise to leverage machine learning models. The technology analyzes and extracts insights from large and complex datasets and helps organizations gain strong predictive accuracy with minimal manual effort.

The global automated machine learning market is estimated to be valued at USD 3.13 billion in 2024 and is expected to exhibit a CAGR of 48.2% over the forecast period 2024-2031.

Automated Machine Learning Demand data-driven decisions is one of the key factors fueling the growth of the global automated machine learning market. Automated ML helps organizations gain predictive insights from massive volumes of structured and unstructured data. It is witnessing rising adoption across industries such as BFSI, healthcare, retail, government, and telecommunications to improve operations and customer experiences.

The market is also expanding rapidly in Asia Pacific owing to increasing investments by technology companies in developing automated ML platforms. Countries like China, India, and Japan are showing significant potential for market growth. Moreover, growing digitization and need for real-time automated decision making present a lucrative growth opportunity for market participants worldwide.

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