
North America Machine Learning (ML) Market Analysis 2025 and Forecasts 2033: Unveiling Growth Opportunities
North America Machine Learning (ML) Market by Enterprise Type (Small, Mid-Sized Enterprises (SMEs), by Deployment (Cloud, On-premise), by End-use Industry (Healthcare, Retail, IT, Telecommunication, BFSI, Automotive, Transportation, Advertising, Media, Manufacturing, Others), by Forecast 2025-2033
Key Insights
The North America Machine Learning (ML) Market size was valued at USD 19.20 USD billion in 2023 and is projected to reach USD 172.15 USD billion by 2032, exhibiting a CAGR of 36.8 % during the forecast period. The increase in demand for efficient data analytics solutions, the growth of cloud computing, and the proliferation of IoT devices are driving the market's growth. Machine learning (ML) is a discipline of artificial intelligence that provides machines with the ability to automatically learn from data and past experiences while identifying patterns to make predictions with minimal human intervention. Machine learning methods enable computers to operate autonomously without explicit programming. ML applications are fed with new data, and they can independently learn, grow, develop, and adapt. Machine learning derives insightful information from large volumes of data by leveraging algorithms to identify patterns and learn in an iterative process. ML algorithms use computation methods to learn directly from data instead of relying on any predetermined equation that may serve as a model. Machine learning is used today for a wide range of commercial purposes, including suggesting products to consumers based on their past purchases, predicting stock market fluctuations, and translating text from one language to another. The North America Machine Learning (ML) Market is primarily driven by the increasing adoption of essential services like security information and cloud applications.
-Market.png)
North America Machine Learning (ML) Trends
- Artificial Intelligence (AI)-powered solutions are fast evolving.
- Growing use of Machine Learning as a Service (MLaaS).
- Integration of Machine Learning (ML) with Blockchain Technology.
- Demand for data security and privacy is on the rise.
Driving Forces: What's Propelling the North America Machine Learning (ML) Market
- The rising demand for predictive and prescriptive analytics solutions is one of the main drivers of growth for the North America machine learning industry.
- The growing need for customer-centric solutions.
- Increase in government investments in research and development.
Challenges and Restraints in North America Machine Learning (ML) Market
- Data privacy and security concerns remain prevalent, requiring robust measures to safeguard sensitive information.
- The high cost of implementing and maintaining ML solutions can limit adoption, particularly for small and mid-scale organizations.
- The shortage of skilled professionals with expertise in ML technologies hinders successful implementation and utilization.
- Ethical considerations and potential biases in ML algorithms pose challenges that require careful evaluation and mitigation.
Emerging Trends in North America Machine Learning (ML)
- The use of ML in the healthcare sector is growing.
- The retail sector is using ML to improve the customer experience.
- The manufacturing industry is using ML to optimize production processes.
Growth Catalysts in North America Machine Learning (ML) Industry
The growth of the North American machine learning industry is fueled by several factors:
- Government initiatives and funding for ML research and development create a supportive environment for innovation.
- Growing adoption of ML solutions across industries, including healthcare, finance, and manufacturing, drives market demand.
- Advancements in cloud computing and artificial intelligence (AI) platforms provide accessible infrastructure and tools for ML development.
- Investment in education and training programs to培养 skilled ML professionals supports industry growth.
Market Segmentation: North America Machine Learning (ML) Analysis
By Enterprise Type
- Small and Mid-Sized Enterprises (SMEs)
- Large Enterprises
By Deployment
- Cloud
- On-premises
By End-use Industry
- Healthcare
- Retail
- IT and Telecommunication
- BFSI
- Automotive and Transportation
- Advertising and Media
- Manufacturing
- Others
Leading Players in the North America Machine Learning (ML) Market
- IBM Corporation (U.S.)
- Oracle Corporation (U.S.)
- Hewlett Packard Enterprise Company (U.S.)
- Microsoft Corporation (U.S.)
- Amazon, Inc. (U.S.)
- Fintelics Technology Inc. (Canada)
- Convergence (Canada)
- Veritone (U.S.)
- Gathr (U.S.)
- Standard Cognition (U.S)
Significant Developments in the North America Machine Learning (ML) Sector
- In 2022, IBM announced a partnership with NVIDIA to develop a new AI platform for healthcare.
- In 2021, Oracle acquired DataScience.com, a provider of ML training and certification programs.
- In 2020, Microsoft launched Azure Machine Learning, a cloud-based ML platform.
Comprehensive Coverage North America Machine Learning (ML) Market Report
- Our report delves into a comprehensive analysis of the North American machine learning industry, providing insights into market size, growth drivers, challenges, and key trends.
- Granular market segmentation by enterprise type, deployment model (cloud, on-premises, hybrid), and end-use industry allows for a thorough understanding of market dynamics.
- Detailed profiles of key players in the market, including their business strategies, market share, and financial performance, provide a competitive landscape analysis.
- The report offers a comprehensive examination of recent industry developments, mergers and acquisitions, and the impact of regulatory changes on the market.
Regional Insight
Within North America, the United States dominates the machine learning market due to the concentration of tech giants, high adoption rates, and a robust ecosystem for ML development. Canada and Mexico are emerging markets with significant growth potential, driven by government support and increasing industrial adoption.
Recent Mergers & Acquisitions
- In 2022, Google acquired AI Platform, a provider of ML training and deployment services.
- In 2021, Amazon acquired a 100% stake in Signify Technology, a provider of ML cloud services.
- In 2020, Microsoft acquired ADRM, a provider of ML technology.
Regulation
The North American machine learning market is subject to various regulations, including data privacy and security laws. The U.S. government has enacted the Health Insurance Portability and Accountability Act (HIPAA) and the California Consumer Privacy Act (CCPA) to protect the privacy of individuals' health and personal information. The Canadian government has enacted the Personal Information Protection and Electronic Documents Act (PIPEDA) to protect the privacy of individuals' personal information. The Mexican government has enacted the Federal Law on the Protection of Personal Data Held by Private Parties (LFPDPPP) to protect the privacy of individuals' personal information.
Patent Analysis
The North American machine learning market is characterized by a high level of patent activity. Companies such as IBM, Microsoft, and Google hold a large number of patents related to ML technology. The number of patents filed for ML technology has increased significantly in recent years, indicating the growing importance of ML in the North American market.
Analyst Comment
- The North American machine-learning market is expected to continue to grow at a rapid pace in the coming years. The growth of the market is driven by several factors, including the increasing demand for predictive and prescriptive analytics solutions, the growing need for customer-centric solutions, and the increase in government investments in research and development.
- The market is expected to be characterized by a high level of competition in the coming years. Companies are investing heavily in research and development to develop new and innovative ML solutions. The market is also expected to see several mergers and acquisitions as companies seek to expand their market share.
North America Machine Learning (ML) Market REPORT HIGHLIGHTS
Aspects | Details |
---|---|
Study Period | 2019-2033 |
Base Year | 2024 |
Estimated Year | 2025 |
Forecast Period | 2025-2033 |
Historical Period | 2019-2024 |
Growth Rate | CAGR of 36.8% from 2019-2033 |
Segmentation |
|
Frequently Asked Questions
What are the notable trends driving market growth?
Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.
Can you provide details about the market size?
The market size is estimated to be USD 19.20 USD billion as of 2022.
What are the main segments of the North America Machine Learning (ML) Market?
The market segments include
Can you provide examples of recent developments in the market?
undefined
How do I determine which pricing option suits my needs best?
The pricing options vary based on user requirements and access needs. Individual users may opt for single-user licenses, while businesses requiring broader access may choose multi-user or enterprise licenses for cost-effective access to the report.
What is the projected Compound Annual Growth Rate (CAGR) of the North America Machine Learning (ML) Market ?
The projected CAGR is approximately 36.8%.
What pricing options are available for accessing the report?
Pricing options include single-user, multi-user, and enterprise licenses priced at USD 3850 , USD 4850, and USD 5850 respectively.
Which companies are prominent players in the North America Machine Learning (ML) Market?
Key companies in the market include IBM Corporation (U.S.),Oracle Corporation (U.S.),Hewlett Packard Enterprise Company (U.S.),Microsoft Corporation (U.S.),Amazon, Inc. (U.S.),Fintelics Technology Inc. (Canada),Convergence (Canada),Veritone (U.S.),Gathr (U.S.),Standard Cognition (U.S)
- 1. Introduction
- 1.1. Research Scope
- 1.2. Market Segmentation
- 1.3. Research Methodology
- 1.4. Definitions and Assumptions
- 2. Executive Summary
- 2.1. Introduction
- 3. Market Dynamics
- 3.1. Introduction
- 3.2. Market Drivers
- 3.2.1. Growing Adoption of Mobile Commerce to Augment the Demand for Virtual Fitting Room Tool
- 3.3. Market Restrains
- 3.3.1. Lack of Privacy and Privacy Violations in AI and ML Applications to Restrain Market Growth
- 3.4. Market Trends
- 3.4.1. Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars
- 4. Market Factor Analysis
- 4.1. Porters Five Forces
- 4.2. Supply/Value Chain
- 4.3. PESTEL analysis
- 4.4. Market Entropy
- 4.5. Patent/Trademark Analysis
- 5. North America Machine Learning (ML) Market Analysis, Insights and Forecast, 2019-2031
- 5.1. Market Analysis, Insights and Forecast - by Enterprise Type
- 5.1.1. Small
- 5.1.2. Mid-Sized Enterprises (SMEs
- 5.2. Market Analysis, Insights and Forecast - by Deployment
- 5.2.1. Cloud
- 5.2.2. On-premise
- 5.3. Market Analysis, Insights and Forecast - by End-use Industry
- 5.3.1. Healthcare
- 5.3.2. Retail
- 5.3.3. IT
- 5.3.4. Telecommunication
- 5.3.5. BFSI
- 5.3.6. Automotive
- 5.3.7. Transportation
- 5.3.8. Advertising
- 5.3.9. Media
- 5.3.10. Manufacturing
- 5.3.11. Others
- 5.4. Market Analysis, Insights and Forecast - by Region
- 5.4.1.
- 5.1. Market Analysis, Insights and Forecast - by Enterprise Type
- 6. U.S. North America Machine Learning (ML) Market Analysis, Insights and Forecast, 2019-2031
- 7. Canada North America Machine Learning (ML) Market Analysis, Insights and Forecast, 2019-2031
- 8. Mexico North America Machine Learning (ML) Market Analysis, Insights and Forecast, 2019-2031
- 9. Competitive Analysis
- 9.1. Market Share Analysis 2024
- 9.2. Company Profiles
- 9.2.1 IBM Corporation (U.S.)
- 9.2.1.1. Overview
- 9.2.1.2. Products
- 9.2.1.3. SWOT Analysis
- 9.2.1.4. Recent Developments
- 9.2.1.5. Financials (Based on Availability)
- 9.2.2 Oracle Corporation (U.S.)
- 9.2.2.1. Overview
- 9.2.2.2. Products
- 9.2.2.3. SWOT Analysis
- 9.2.2.4. Recent Developments
- 9.2.2.5. Financials (Based on Availability)
- 9.2.3 Hewlett Packard Enterprise Company (U.S.)
- 9.2.3.1. Overview
- 9.2.3.2. Products
- 9.2.3.3. SWOT Analysis
- 9.2.3.4. Recent Developments
- 9.2.3.5. Financials (Based on Availability)
- 9.2.4 Microsoft Corporation (U.S.)
- 9.2.4.1. Overview
- 9.2.4.2. Products
- 9.2.4.3. SWOT Analysis
- 9.2.4.4. Recent Developments
- 9.2.4.5. Financials (Based on Availability)
- 9.2.5 Amazon Inc. (U.S.)
- 9.2.5.1. Overview
- 9.2.5.2. Products
- 9.2.5.3. SWOT Analysis
- 9.2.5.4. Recent Developments
- 9.2.5.5. Financials (Based on Availability)
- 9.2.6 Fintelics Technology Inc. (Canada)
- 9.2.6.1. Overview
- 9.2.6.2. Products
- 9.2.6.3. SWOT Analysis
- 9.2.6.4. Recent Developments
- 9.2.6.5. Financials (Based on Availability)
- 9.2.7 Convergence (Canada)
- 9.2.7.1. Overview
- 9.2.7.2. Products
- 9.2.7.3. SWOT Analysis
- 9.2.7.4. Recent Developments
- 9.2.7.5. Financials (Based on Availability)
- 9.2.8 Veritone (U.S.)
- 9.2.8.1. Overview
- 9.2.8.2. Products
- 9.2.8.3. SWOT Analysis
- 9.2.8.4. Recent Developments
- 9.2.8.5. Financials (Based on Availability)
- 9.2.9 Gathr (U.S.)
- 9.2.9.1. Overview
- 9.2.9.2. Products
- 9.2.9.3. SWOT Analysis
- 9.2.9.4. Recent Developments
- 9.2.9.5. Financials (Based on Availability)
- 9.2.10 Standard Cognition (U.S)
- 9.2.10.1. Overview
- 9.2.10.2. Products
- 9.2.10.3. SWOT Analysis
- 9.2.10.4. Recent Developments
- 9.2.10.5. Financials (Based on Availability)
- 9.2.1 IBM Corporation (U.S.)
- Figure 1: North America Machine Learning (ML) Market Revenue Breakdown (USD billion, %) by Product 2024 & 2032
- Figure 2: North America Machine Learning (ML) Market Share (%) by Company 2024
- Table 1: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Region 2019 & 2032
- Table 2: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Enterprise Type 2019 & 2032
- Table 3: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Deployment 2019 & 2032
- Table 4: North America Machine Learning (ML) Market Revenue USD billion Forecast, by End-use Industry 2019 & 2032
- Table 5: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Region 2019 & 2032
- Table 6: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Country 2019 & 2032
- Table 7: U.S. North America Machine Learning (ML) Market Revenue (USD billion) Forecast, by Application 2019 & 2032
- Table 8: Canada North America Machine Learning (ML) Market Revenue (USD billion) Forecast, by Application 2019 & 2032
- Table 9: Mexico North America Machine Learning (ML) Market Revenue (USD billion) Forecast, by Application 2019 & 2032
- Table 10: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Enterprise Type 2019 & 2032
- Table 11: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Deployment 2019 & 2032
- Table 12: North America Machine Learning (ML) Market Revenue USD billion Forecast, by End-use Industry 2019 & 2032
- Table 13: North America Machine Learning (ML) Market Revenue USD billion Forecast, by Country 2019 & 2032
Aspects | Details |
---|---|
Study Period | 2019-2033 |
Base Year | 2024 |
Estimated Year | 2025 |
Forecast Period | 2025-2033 |
Historical Period | 2019-2024 |
Growth Rate | CAGR of 36.8% from 2019-2033 |
Segmentation |
|
STEP 1 - Identification of Relevant Samples Size from Population Database



STEP 2 - Approaches for Defining Global Market Size (Value, Volume* & Price*)

Note* : In applicable scenarios
STEP 3 - Data Sources
Primary Research
- Web Analytics
- Survey Reports
- Research Institute
- Latest Research Reports
- Opinion Leaders
Secondary Research
- Annual Reports
- White Paper
- Latest Press Release
- Industry Association
- Paid Database
- Investor Presentations

STEP 4 - Data Triangulation
Involves using different sources of information in order to increase the validity of a study
These sources are likely to be stakeholders in a program - participants, other researchers, program staff, other community members, and so on.
Then we put all data in single framework & apply various statistical tools to find out the dynamic on the market.
During the analysis stage, feedback from the stakeholder groups would be compared to determine areas of agreement as well as areas of divergence
Related Reports
About Market Research Forecast
MR Forecast provides premium market intelligence on deep technologies that can cause a high level of disruption in the market within the next few years. When it comes to doing market viability analyses for technologies at very early phases of development, MR Forecast is second to none. What sets us apart is our set of market estimates based on secondary research data, which in turn gets validated through primary research by key companies in the target market and other stakeholders. It only covers technologies pertaining to Healthcare, IT, big data analysis, block chain technology, Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Energy & Power, Automobile, Agriculture, Electronics, Chemical & Materials, Machinery & Equipment's, Consumer Goods, and many others at MR Forecast. Market: The market section introduces the industry to readers, including an overview, business dynamics, competitive benchmarking, and firms' profiles. This enables readers to make decisions on market entry, expansion, and exit in certain nations, regions, or worldwide. Application: We give painstaking attention to the study of every product and technology, along with its use case and user categories, under our research solutions. From here on, the process delivers accurate market estimates and forecasts apart from the best and most meaningful insights.
Products generically come under this phrase and may imply any number of goods, components, materials, technology, or any combination thereof. Any business that wants to push an innovative agenda needs data on product definitions, pricing analysis, benchmarking and roadmaps on technology, demand analysis, and patents. Our research papers contain all that and much more in a depth that makes them incredibly actionable. Products broadly encompass a wide range of goods, components, materials, technologies, or any combination thereof. For businesses aiming to advance an innovative agenda, access to comprehensive data on product definitions, pricing analysis, benchmarking, technological roadmaps, demand analysis, and patents is essential. Our research papers provide in-depth insights into these areas and more, equipping organizations with actionable information that can drive strategic decision-making and enhance competitive positioning in the market.