U.S. AutoML Market Size & Opportunities Analysis - Growth Strategies, Competitiveness, and Forecasts (2025 - 2032)

U.S. AutoML Market Growth Factors

No-Code and Low-Code Platforms Are Key Trend

• No- and low-code platforms let non-technical individuals construct and train machine learning models and deploy them without programming skills.
• Low-code tools are expected to account for over 70% of the software development, enabling non-technical users to contribute to app creation.
• The user-friendly interfaces of these platforms reduce the complexity of ML programming tasks, so individuals without technical skills can make models.
• In December 2024, BigML deployed Association Discovery on the cloud.
• The tool unearths unknown associations between the variables of large-dimensional datasets in a single click.
• The platform has easy drag-and-drop functions that do not require complex programming, thus making the platform user-friendly for business analysts, marketers, and even non-data scientists.
• In June 2024, Creatio closed a funding round of USD 200 million, which brought its valuation to USD 1.2 billion.
• The investment is being used for the further development of the company’s product and the automation of marketing and sales processes with generative AI.
• No-code and low-code AutoML platforms allow for the automated processing of the traditionally time-consuming ML operations, such as data preprocessing, model choice, and hyperparameter optimization. This increases productivity across departments and expedites projects.
• These platforms provide pre-built models and templates ready to use for common applications, so users can easily apply ML to their data source without having to build models from scratch.
• The platforms train and assess the performance ML models in the background, to keep the best algorithms and optimize performance.

Increasing Demand for AI and ML across Industries Is Major Growth Driver

• The market is expanding because of the escalating demand for the AI and ML technologies.
• Various industries are adopting AI tools to simplify and automate ML, in order to improve decision-making, optimize operations, and enhance overall efficiency.
• The NSF spends about USD 700 million a year on AI research, which covers basic research on ML and related fields that make up the foundation of AutoML.
• Earlier, developers with the knowledge of data science, programming, and advanced mathematics were needed for developing ML models; however, this restricts many organizations from leveraging this technology.
• In February 2024, TMF made a call for proposals to aid government agencies implementing the Executive Order on AI.
• With AutoML tools, firms have the opportunity to apply ML models without non-specialized technical skills.
• In October 2023, the president of the U.S. signed a new decree on AI that says that corporations building powerful AI and cloud tools must publicize vital safety reports and other important information, to keep it safe and trustworthy.

U.S. AutoML Market Segmentation Analysis

Enterprise Size Analysis

The large enterprise category held the dominant market share, of 75%, in 2024. This is because these businesses have greater access to large datasets and money to use to deploy advanced technologies, including AutoML. They need to analyze this information to obtain actionable insights for business growth, which can be cumbersome if done manually. By using AutoML and other AI technologies, these firms can lessen the requirement for humans in mundane and repetitive tasks and direct them to more-important processes.

The SME category will grow at the higher CAGR, during the forecast period. This is because of the expanding availability of the low-cost, cloud-based AutoML systems with easy-to-use interfaces. AutoML platforms provide SMEs with AI functionalities at affordable prices, without requiring any specialized technical know-how. This allows smaller organizations to compete effectively with their larger players in their respective industries.

The enterprise sizes analyzed here are:

• Large Enterprise (Larger Category)
• SMEs (Faster-Growing Category)

Application Analysis

The sales & marketing management category held the largest market share, of 60%, in 2024, and it will grow at the highest CAGR, during the forecast period. This is because these departments are actively implementing ML to enhance operations and business decisions. AutoML allows sales & marketing departments to automate such processes as customer segmentation, demand forecasting, personalization, and campaign optimization.

Businesses across all industries are seeking ways of incorporating AI into their marketing activities in a bid to remain competitive in a data-driven economy. Companies need high-tech tools to analyze the increasing amount of customer information, in order to successfully optimize marketing processes.

The applications analyzed here are:

• Fraud Detection
• Sales & Marketing Management (Largest and Fastest-Growing Category)
• Medical Testing
• Transport Optimization
• Others

Industry Analysis

The BFSI category held the largest market share, of 40%, in 2024. This is because banks, insurance companies, and investment firms analyze and use massive amounts of data to make decisions. AutoML tools enable automated data analysis, which augments and simplifies central operations such as fraud detection, credit evaluation, risk determination, and customer services.

The healthcare category will grow at the highest CAGR, during the forecast period. This is because of the rising use of AutoML tools to process medical data, such as patient records, medical imaging, and genetic information. Effective data analysis helps make clinical decisions for improved patient results. AutoML tools are also applied in healthcare to develop personalized treatments, diagnose diseases, and forecast epidemics.

The industries analyzed here are:

• BFSI (Largest Category)
• IT & Telecom
• Healthcare (Fastest-Growing Category)
• Government
• Retail
• Manufacturing
• Others

Deployment Type Analysis

The cloud category held the larger market share, of 80%, in 2024, and it will grow at the higher CAGR, during the forecast period. This is because cloud-based AutoML provides flexible, scalable, and cost-effective solutions. These solutions are attractive to businesses because they eliminate hardware and infrastructure costs. Google Cloud AutoML, Amazon AWS SageMaker, and Microsoft Azure Machine Learning offer comprehensive solutions ranging from data storage to preprocessing and model deployment to monitoring.

The deployment types analyzed here are:

• Cloud (Larger and Faster-Growing Category)
• On-Premises

U.S. AutoML Market Regional Outlook

The Western region held the largest market share, of 65%, in 2024 because of the technology hubs of Silicon Valley, San Francisco, and Seattle, where the tech companies receive heavy venture capital investments. The region is also home to a large number of AI technicians, and it possesses a strong culture of innovation, which make it a key hub for early and large-scale implementation of ML technologies.

The Northeast region will grow at the highest CAGR, during the forecast period, driven by the rapid adoption of AutoML in the finance, healthcare, and education sectors. The large financial institutions based in New York and Boston use AI for fraud detection, portfolio management, and risk analytics. The presence of prestigious universities, such as MIT and Harvard, which employ numerous AI researchers and data scientists, leads to extensive efforts for innovation and consistent project pipelines. Furthermore, the vibrant startup ecosystem with a particular emphasis on AI-driven business transformation drives the market in the region.

The regions analyzed in this report are:

• Northeast (Fastest-Growing Region)
• Midwest
• West (Largest Region)
• South

U.S. AutoML Market Competitive Landscape

The market is fragmented in nature because it comprises various companies that provide various kinds of solutions. This diversity is due to the wide variety of business requirements and user competence from non-technical users to competent data scientists. The players cater to various industries, such as finance, healthcare, and manufacturing, with individual needs, which leads to the need for customized individual solutions. Additionally, a large number of companies from Asia and Europe offer AutoML solutions in the U.S., which fragments the market and augments competition.

U.S. AutoML Market News & Updates

• In November 2024, H2O.ai launched its beacon flagship H2O World event from the NASDAQ building in New York City. Over 200 executives and professionals from the BFSI, telecommunications, and healthcare industries discussed the latest in generative AI and its applications in various fields.
• In May 2024, Qlik acquired Talend to advance its data management and analytics offerings.