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

Description

The U.S. automated machine learning (AutoML) market is on a dynamic growth path, with its value projected to increase from USD 428.6 million in 2024 to USD 2,696.8 million by 2032, translating to a robust compound annual growth rate (CAGR) of 26%. This surge is propelled by the rising demand for AI-driven insights across various industries seeking to enhance operational efficiency and decision-making accuracy.

AutoML platforms are revolutionizing how businesses use machine learning by simplifying model development for users with minimal technical expertise. The massive influx of data across sectors is driving organizations to adopt AutoML solutions to efficiently analyze information and generate actionable insights without the need for extensive programming skills.

Key Insights

The market caters to both large enterprises and small & medium-sized enterprises (SMEs), with increasing adoption across the board as companies look to optimize processes and remain competitive.

AutoML is being applied in a range of areas including fraud detection, marketing optimization, medical diagnostics, and transportation logistics, delivering faster and more accurate results.

Key industries embracing AutoML include BFSI, IT & telecom, healthcare, government, retail, and manufacturing, each leveraging the technology to automate complex processes and minimize human error.

Cloud-based deployment models are gaining popularity due to their scalability, cost-efficiency, and ease of access, though on-premises solutions still hold relevance for data-sensitive operations.

The West region currently holds the largest market share, bolstered by the presence of leading tech firms and early adoption of AI technologies, while the Northeast is expected to witness the fastest growth due to increased regional investments.

A notable trend is the rise of no-code and low-code AutoML platforms that enable broader user participation by simplifying machine learning model development through intuitive interfaces.

Government support, such as substantial funding allocations for AI research, is accelerating AutoML innovation and adoption across public and private sectors.

In healthcare, AutoML is enhancing diagnostic accuracy and treatment personalization by enabling rapid and data-driven analysis of patient records and medical images.

The financial services industry uses AutoML for real-time fraud detection and risk assessment, helping to identify suspicious transactions with high precision.

Retail companies are deploying AutoML for personalized customer engagement, inventory forecasting, and dynamic pricing strategies, improving customer satisfaction and operational efficiency.

Manufacturing firms benefit from AutoML through predictive maintenance, defect detection, and supply chain optimization, resulting in reduced downtime and improved productivity.

Educational institutions are exploring AutoML to power adaptive learning platforms that personalize instruction based on individual student progress and needs.

Data privacy concerns and the necessity for high-quality, labeled data are ongoing challenges, but these are being addressed through advanced preprocessing tools and data governance frameworks.

The competitive environment is marked by continuous innovation, with major players pursuing strategic alliances, acquisitions, and product expansions to strengthen their market presence.

Improvements in AI algorithms and computing capabilities are expected to further advance AutoML solutions, making them even more powerful and accessible to a broader range of users.

As a key component of the AI ecosystem, AutoML is set to drive significant transformation in data analysis and decision-making across nearly every sector of the U.S. economy.

Product Code: 13481

Chapter 1. Research Scope

1.1. Research Objectives
1.2. Market Definition
1.3. Analysis Period
1.4. Market Size Breakdown by Segments
- 1.4.1. Market Size Breakdown, by Enterprise Size
- 1.4.2. Market Size Breakdown, by Application
- 1.4.3. Market Size Breakdown, by Industry
- 1.4.4. Market Size Breakdown, by Deployment Type
1.5. Market Data Reporting Unit
- 1.5.1. Revenue
1.6. Key Stakeholders

Chapter 2. Research Methodology

2.1. Secondary Research
- 2.1.1. Paid
- 2.1.2. Unpaid
- 2.1.3. P&S Intelligence Database
2.2. Primary Research
2.3. Market Size Estimation
2.4. Data Triangulation
2.5. Currency Conversion Rates
2.6. Assumptions for the Study
2.7. Notes and Caveats

Chapter 3. Executive Summary

Chapter 4. Market Indicators

Chapter 5. Industry Outlook

5.1. Industry Background
5.2. Market Dynamics
- 5.2.1. Trends
- 5.2.2. Drivers
- 5.2.3. Restraints/Challenges
- 5.2.4. Emerging Economies and Key Opportunities
- 5.2.5. Impact Analysis of Drivers/Restraints
5.3. Impact of COVID-19
5.4. Sociopolitical Impact
5.5. Porter's Five Forces Analysis
- 5.5.1. Bargaining Power of Buyers
- 5.5.2. Bargaining Power of Suppliers
- 5.5.3. Threat of New Entrants
- 5.5.4. Intensity of Rivalry
- 5.5.5. Threat of Substitutes
5.6. Innovation and Technology Trends
5.7. Economic and Regulatory Impact
5.8. Market Entry Strategies

Chapter 6. Competitive Landscape

6.1. List of Market Players and their Offerings
6.2. Market Share of Key Players (2024)
6.3. Competitive Benchmarking of Key Players
6.4. Product Benchmarking of Key Players
6.5. Recent Strategic Developments by Key Players
6.6. Company Leadership Matrix

Chapter 7. U.S. Market

7.1. Overview
7.2. Market Revenue, by Enterprise Size (2019-2032)
7.3. Market Revenue, by Application (2019-2032)
7.4. Market Revenue, by Industry (2019-2032)
7.5. Market Revenue, by Deployment Type (2019-2032)
7.6. Market Revenue, by Country (2019-2032)

Chapter 8. Northeast Market

8.1. Overview
8.2. Economic Indicators
8.3. Demographics and Population Insights
8.4. Regional Hotspots
8.5. Growth Drivers
8.6. Challenges and Barriers
8.7. Competitive Strategies
8.8. Emerging Players
8.9. Import/Export Policies
8.10. Compliance Requirements
8.11. Emerging Investment Areas
8.12. Major Ongoing Projects
8.13. Market Size and Forecast
- 8.13.1. Market Revenue, by Enterprise Size (2019-2032)
- 8.13.2. Market Revenue, by Application (2019-2032)
- 8.13.3. Market Revenue, by Industry (2019-2032)
- 8.13.4. Market Revenue, by Deployment Type (2019-2032)

Chapter 9. Midwest Market

9.1. Overview
9.2. Economic Indicators
9.3. Demographics and Population Insights
9.4. Regional Hotspots
9.5. Growth Drivers
9.6. Challenges and Barriers
9.7. Competitive Strategies
9.8. Emerging Players
9.9. Import/Export Policies
9.10. Compliance Requirements
9.11. Emerging Investment Areas
9.12. Major Ongoing Projects
9.13. Market Size and Forecast
- 9.13.1. Market Revenue, by Enterprise Size (2019-2032)
- 9.13.2. Market Revenue, by Application (2019-2032)
- 9.13.3. Market Revenue, by Industry (2019-2032)
- 9.13.4. Market Revenue, by Deployment Type (2019-2032)

Chapter 10. West Market

10.1. Overview
10.2. Economic Indicators
10.3. Demographics and Population Insights
10.4. Regional Hotspots
10.5. Growth Drivers
10.6. Challenges and Barriers
10.7. Competitive Strategies
10.8. Emerging Players
10.9. Import/Export Policies
10.10. Compliance Requirements
10.11. Emerging Investment Areas
10.12. Major Ongoing Projects
10.13. Market Size and Forecast
- 10.13.1. Market Revenue, by Enterprise Size (2019-2032)
- 10.13.2. Market Revenue, by Application (2019-2032)
- 10.13.3. Market Revenue, by Industry (2019-2032)
- 10.13.4. Market Revenue, by Deployment Type (2019-2032)

Chapter 11. South Market

11.1. Overview
11.2. Economic Indicators
11.3. Demographics and Population Insights
11.4. Regional Hotspots
11.5. Growth Drivers
11.6. Challenges and Barriers
11.7. Competitive Strategies
11.8. Emerging Players
11.9. Import/Export Policies
11.10. Compliance Requirements
11.11. Emerging Investment Areas
11.12. Major Ongoing Projects
11.13. Market Size and Forecast
- 11.13.1. Market Revenue, by Enterprise Size (2019-2032)
- 11.13.2. Market Revenue, by Application (2019-2032)
- 11.13.3. Market Revenue, by Industry (2019-2032)
- 11.13.4. Market Revenue, by Deployment Type (2019-2032)

Chapter 12. Company Profiles

Chapter 13. Appendix

13.1. Sources and References
13.2. Related Reports

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