Automated Machine Learning Market: Market Size & Forecast 2026

Automated machine learning refers to tools and platforms designed to automate repetitive tasks in the machine learning workflow, making AI development accessible to a broader range of users beyond specialized data scientists. The global market is estimated at approximately $2.85 billion in 2025, with projections ranging from $20 billion to over $90 billion by the early 2030s based on compound annual growth rates between 38 and 48 percent. It is worth noting that no government statistical agency publishes official market size figures for AutoML, as these estimates are calculated by industry research firms based on vendor revenues and enterprise adoption surveys.

• •Market valued at roughly $2.85 billion in 2025 with projected CAGR near 40.5 percent
• •U.S. market accounted for approximately $695 million or 14.9 percent of the global total in 2025
• •No official government statistical agency publishes dedicated AutoML market size data

The primary force behind AutoML market expansion is growing enterprise demand for artificial intelligence solutions combined with a global shortage of skilled machine learning practitioners, which has made automation essential for scaling AI initiatives. Organizations across industries are seeking to reduce the time and cost associated with developing and deploying machine learning models, with AutoML platforms offering significant efficiency gains by automating tasks that traditionally required expert data scientists. Additionally, the democratization of AI, enabling business analysts and software engineers without deep ML expertise to build predictive models, has opened a vast new user base beyond traditional data science teams.

• •Enterprise AI adoption accelerating while demand for skilled data scientists outpaces supply
• •Need to reduce time-to-market and operational costs for machine learning projects
• •Democratization of AI tools enabling broader organizational adoption beyond specialized teams

The AutoML market spans various deployment models including cloud-based solutions, on-premises deployments, and hybrid configurations, with cloud platforms gaining prominence due to their scalability and accessibility. North America dominates the global market, with the United States representing approximately 15 percent of worldwide AutoML revenue in 2025 and projected to grow at a compound annual rate of about 28 percent through 2033. Europe and Asia-Pacific are emerging as significant growth regions as enterprises in these markets increase their AI investments and digital transformation initiatives.

• •U.S. AutoML market recorded approximately $695 million in 2025 with projected CAGR of 28.2 percent through 2033
• •North America leads globally while Asia-Pacific and Europe show accelerating adoption rates
• •Enterprise segments span financial services, healthcare, retail, manufacturing, and technology industries

What are the recent trends and outlook?

The AutoML market is evolving toward more comprehensive platforms that extend beyond model building to cover the full machine learning lifecycle, including model deployment, monitoring, and governance in what is increasingly called MLOps. As the technology matures, AutoML tools are becoming more sophisticated in handling complex use cases such as deep learning, time-series forecasting, and natural language processing, while also incorporating explainability and fairness features to meet growing regulatory and ethical requirements. The overall outlook remains strongly positive, with continued investment in AI infrastructure, rising enterprise familiarity with automated tools, and expanding applications across industries suggesting sustained market expansion well beyond the current decade.

• •AutoML platforms expanding into full MLOps lifecycle management encompassing deployment, monitoring, and governance
• •Growing emphasis on model explainability, fairness, and regulatory compliance in automated solutions
• •Sustained market expansion expected as AI adoption spreads across industries and organizational maturity increases