The global machine learning market was surpassed at USD 21.45 billion in 2022 and is expected to hit around USD 573.29 billion by 2032, growing at a CAGR of 38.9% from 2023 to 2032.
Key Pointers
Report Scope of the Machine Learning Market
| Report Coverage | Details |
| Market Size in 2022 | USD 21.45 billion |
| Revenue Forecast by 2032 | USD 573.29 billion |
| Growth rate from 2023 to 2032 | CAGR of 38.9% |
| Base Year | 2022 |
| Forecast Period | 2023 to 2032 |
| Market Analysis (Terms Used) | Value (US$ Million/Billion) or (Volume/Units) |
| Regions Covered | North America, Europe, Asia Pacific, Latin America, Middle East & Africa |
| Companies Covered | Amazon Web Services, Inc.; Baidu Inc.; Google Inc.; H2O.ai; Intel Corporation; International Business Machines Corporation; Hewlett Packard Enterprise Development LP; Microsoft Corporation; SAS Institute Inc.; and SAP SE. |
Emerging technologies such as artificial intelligence are changing the way industries and humans work. These technologies have optimized supply chains, launched various digital products and services, and transformed the overall customer experience. Various tech firms are investing in this field to develop AI platforms, while various startups are focusing on niche domain solutions. With this rapid development, AI techniques such as machine learning are gaining significant traction in the market.
Machine learning is a subset of artificial intelligence. The concept has evolved from computational learning and pattern recognition in artificial intelligence. It explores the construction and study of algorithms and carries out forecasts on data. The applications of machine learning include e-mail filtering, Optical Character Recognition (OCR), detection of network intruders, computer vision, and learning to rank.
The technology has paved the way across various applications. In advertising, this technology is used to predict the behavior of a customer and helps in improving advertising campaigns. AI-driven marketing uses various models to optimize, automate, and augment the data into actions. In the case of banking and finance, loan approval, assets management, and other processes are carried out using machine learning. Other applications, such as security, document management, and publishing, are also using this technology, thereby driving the market.
Recently, machine learning has made its way into new aspects. For instance, the U.S. Army is planning to use this technology in combat vehicles for predictive maintenance. It will help in determining the repair and service required in these vehicles with details such as when and where the repair is required. The stock market is also making use of this technology in market prediction with an accuracy level of approximately 60%.
Regional Insights
The market in North America held the dominant share in 2022, thanks to numerous banking organizations in the region investing in ML-based firms. For instance, in November 2019, JPMorgan Chase & Co. announced its investment in Limeglass, a provider of AI, ML, and NLP to analyze institutional research. The latter company is expected to assist emerging technology companies in developing various products required for banking.
Asia Pacific is anticipated to register the highest CAGR over the forecast period. This is due to the growing adoption of machine learning in emerging markets with a massive talent base, such as India. Greater access to consumers who are willing to try AI-enabled services and products is further driving the regional market. In May 2018, NITI Aayog, a policy think tank of the Government of India, collaborated with Google LLC, a multinational technology company. Through this collaboration, the former company will incubate and train start-ups based on AI in India.
Machine Learning Market Segmentations:
| By Component | By Enterprise Size | By End-use |
|
Hardware Software Services |
SMEs Large Enterprises |
Healthcare BFSI Law Retail Advertising & Media Automotive & Transportation Agriculture Manufacturing Others |
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Component Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Machine Learning Market
5.1. COVID-19 Landscape: Machine Learning Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Machine Learning Market, By Component
8.1. Machine Learning Market, by Component, 2023-2032
8.1.1 Hardware
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Software
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Services
8.1.3.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Machine Learning Market, By Enterprise Size
9.1. Machine Learning Market, by Enterprise Size, 2023-2032
9.1.1. SMEs
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Large Enterprises
9.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Machine Learning Market, By End-use
10.1. Machine Learning Market, by End-use, 2023-2032
10.1.1. Healthcare
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. BFSI
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Law
10.1.3.1. Market Revenue and Forecast (2020-2032)
10.1.4. Retail
10.1.4.1. Market Revenue and Forecast (2020-2032)
10.1.5. Advertising & Media
10.1.5.1. Market Revenue and Forecast (2020-2032)
10.1.6. Automotive & Transportation
10.1.6.1. Market Revenue and Forecast (2020-2032)
10.1.7. Agriculture
10.1.7.1. Market Revenue and Forecast (2020-2032)
10.1.8. Manufacturing
10.1.8.1. Market Revenue and Forecast (2020-2032)
10.1.9. Others
10.1.9.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Machine Learning Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Component (2020-2032)
11.1.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.1.3. Market Revenue and Forecast, by End-use (2020-2032)
11.1.4. U.S.
11.1.4.1. Market Revenue and Forecast, by Component (2020-2032)
11.1.4.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.1.4.3. Market Revenue and Forecast, by End-use (2020-2032)
11.1.5. Rest of North America
11.1.5.1. Market Revenue and Forecast, by Component (2020-2032)
11.1.5.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.1.5.3. Market Revenue and Forecast, by End-use (2020-2032)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Component (2020-2032)
11.2.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.2.3. Market Revenue and Forecast, by End-use (2020-2032)
11.2.4. UK
11.2.4.1. Market Revenue and Forecast, by Component (2020-2032)
11.2.4.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.2.4.3. Market Revenue and Forecast, by End-use (2020-2032)
11.2.5. Germany
11.2.5.1. Market Revenue and Forecast, by Component (2020-2032)
11.2.5.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.2.5.3. Market Revenue and Forecast, by End-use (2020-2032)
11.2.6. France
11.2.6.1. Market Revenue and Forecast, by Component (2020-2032)
11.2.6.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.2.6.3. Market Revenue and Forecast, by End-use (2020-2032)
11.2.7. Rest of Europe
11.2.7.1. Market Revenue and Forecast, by Component (2020-2032)
11.2.7.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.2.7.3. Market Revenue and Forecast, by End-use (2020-2032)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Component (2020-2032)
11.3.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.3.3. Market Revenue and Forecast, by End-use (2020-2032)
11.3.4. India
11.3.4.1. Market Revenue and Forecast, by Component (2020-2032)
11.3.4.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.3.4.3. Market Revenue and Forecast, by End-use (2020-2032)
11.3.5. China
11.3.5.1. Market Revenue and Forecast, by Component (2020-2032)
11.3.5.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.3.5.3. Market Revenue and Forecast, by End-use (2020-2032)
11.3.6. Japan
11.3.6.1. Market Revenue and Forecast, by Component (2020-2032)
11.3.6.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.3.6.3. Market Revenue and Forecast, by End-use (2020-2032)
11.3.7. Rest of APAC
11.3.7.1. Market Revenue and Forecast, by Component (2020-2032)
11.3.7.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.3.7.3. Market Revenue and Forecast, by End-use (2020-2032)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Component (2020-2032)
11.4.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.4.3. Market Revenue and Forecast, by End-use (2020-2032)
11.4.4. GCC
11.4.4.1. Market Revenue and Forecast, by Component (2020-2032)
11.4.4.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.4.4.3. Market Revenue and Forecast, by End-use (2020-2032)
11.4.5. North Africa
11.4.5.1. Market Revenue and Forecast, by Component (2020-2032)
11.4.5.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.4.5.3. Market Revenue and Forecast, by End-use (2020-2032)
11.4.6. South Africa
11.4.6.1. Market Revenue and Forecast, by Component (2020-2032)
11.4.6.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.4.6.3. Market Revenue and Forecast, by End-use (2020-2032)
11.4.7. Rest of MEA
11.4.7.1. Market Revenue and Forecast, by Component (2020-2032)
11.4.7.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.4.7.3. Market Revenue and Forecast, by End-use (2020-2032)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Component (2020-2032)
11.5.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.5.3. Market Revenue and Forecast, by End-use (2020-2032)
11.5.4. Brazil
11.5.4.1. Market Revenue and Forecast, by Component (2020-2032)
11.5.4.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.5.4.3. Market Revenue and Forecast, by End-use (2020-2032)
11.5.5. Rest of LATAM
11.5.5.1. Market Revenue and Forecast, by Component (2020-2032)
11.5.5.2. Market Revenue and Forecast, by Enterprise Size (2020-2032)
11.5.5.3. Market Revenue and Forecast, by End-use (2020-2032)
Chapter 12. Company Profiles
12.1. Amazon Web Services, Inc.
12.1.1. Company Overview
12.1.2. Product Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. Baidu Inc.
12.2.1. Company Overview
12.2.2. Product Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. Google Inc.
12.3.1. Company Overview
12.3.2. Product Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. H2O.ai
12.4.1. Company Overview
12.4.2. Product Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. Intel Corporation
12.5.1. Company Overview
12.5.2. Product Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
12.6. International Business Machines Corporation
12.6.1. Company Overview
12.6.2. Product Offerings
12.6.3. Financial Performance
12.6.4. Recent Initiatives
12.7. Hewlett Packard Enterprise Development LP
12.7.1. Company Overview
12.7.2. Product Offerings
12.7.3. Financial Performance
12.7.4. Recent Initiatives
12.8. Microsoft Corporation
12.8.1. Company Overview
12.8.2. Product Offerings
12.8.3. Financial Performance
12.8.4. Recent Initiatives
12.9. SAS Institute Inc.
12.9.1. Company Overview
12.9.2. Product Offerings
12.9.3. Financial Performance
12.9.4. Recent Initiatives
12.10. SAP SE.
12.10.1. Company Overview
12.10.2. Product Offerings
12.10.3. Financial Performance
12.10.4. Recent Initiatives
Chapter 13. Research Methodology
13.1. Primary Research
13.2. Secondary Research
13.3. Assumptions
Chapter 14. Appendix
14.1. About Us
14.2. Glossary of Terms
Cross-segment Market Size and Analysis for
Mentioned Segments
Additional Company Profiles (Upto 5 With No Cost)
Additional Countries (Apart From Mentioned Countries)
Country/Region-specific Report
Go To Market Strategy
Region Specific Market DynamicsRegion Level Market Share Import Export AnalysisProduction AnalysisOthers