The Machine Learning Market size was valued at USD 36.74 billion in 2023 and is expected to grow to USD 543.55 billion by 2031 and grow at a CAGR of 34.9% over the forecast period of 2024-2031.
The growing amount of data generated has led to a growth in the Machine Learning Market. There is a growing demand for effective analysis and extraction of information from this data due to the increasing volume of data generated in different sectors and companies. Machine learning algorithms are capable of processing and analysing large amounts of data, enabling businesses to make fast decisions based on the information they have available in order to gain competitive advantage.
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The growth of the machine learning market can be attributed to increasing use of technology of artificial intelligence (AI) and automation. Increasing adoption of cloud computing platforms, with their fundamental advantages, is aimed at driving growth in the market.
Key Drivers:
Rising demand of machine learning for Internet of Things
The demand for machine learning is increasing due to the increasing availability of large amounts of data and the growing awareness of the benefits of machine learning in decision making. The demand for machine learning solutions is also driven by the emergence of Internet of Things IoT devices and the need to analyse large amounts of data in a timely manner. Increasingly, businesses and organisations are using machine learning algorithms to gain important insight from their data with a view to making better decisions as they seek an edge over competitors.
Easy And Effective to Automate
Restraints:
Lack Of Accuracy
The ML platform has a number of advantages that can contribute to market growth. However, this technology does not have certain parameters that could hinder growth in the market. One of the major obstacles to a platform for machine learning is unreliable and incomplete algorithms. The accuracy of Big Data and machine learning, which can lead to incorrect algorithms resulting in faulty parts production, is crucial.
Opportunities:
Increasing growth of machine learning in healthcare industry
Growth in the market is likely to be stimulated by increasing applications in the healthcare sector in a variety of healthcare applications, ML technology is already being used. This technology assesses millions of data points and forecasts results, providing quick risk scores and accurate allocation of resources in this industry vertical. Diagnosis and detection of diseases, which may be difficult to detect, is one of the most important uses of this technology in healthcare.
Demand for pattern identification is increasing
Challenges:
Strict Regulatory Environments
Lack of funds
It is clear that the ongoing global economic slowdown has an impact on different sectors, but the machine learning market continues to show strong growth prospects. AI and machine learning have the potential to significantly contribute to global economic activity, with an estimated additional global economic activity of around. This implies a further increase in GDP of 1.2 % annually. The growing availability of big data sets, increased processing capacity and the development of more efficient algorithms are driving this increase. Machine learning is finding applications across various sectors, including advertising, finance, healthcare, and more, aiding in tasks ranging from consumer behavior prediction to medical diagnostics. The resilience and potential for growth of the Machine Learning market is apparent in spite of broader challenges. In addition to technological progress and the increase in digitisation of industries, industry's trajectory indicates a growing demand for artificial intelligence and machine learning capabilities. Machine learning and artificial intelligence technologies have emerged as the main drivers of innovation and efficiency in a global economy that is coping with slowdowns and uncertainties.
The Russia Ukraine crisis has shown that machine learning can be used to analyse and respond to crises, while also highlighting the vulnerabilities of global supply chains that the technology sector, including machine learning, relies on. This situation highlights the need to plan scenarios, assess operating risks and adapt quickly to rapidly changing world conditions. The crisis in Russia and Ukraine has had a multidisciplinary impact on different sectors, e.g. the market for computer aided programming as well as related areas. The conflict has had an impact on economic indexes and commodity prices, which have also affected sectors relying on technology and data analysis.
In addition, the use of machine learning and big data to find war damage infrastructure in Ukraine has demonstrated how these technologies are applied during crisis situations. In order to analyse reports and classify damaged infrastructure, the UNDP has developed models based on machine learning and natural language processing, which help to make timely decisions and allocate resources to rebuild efforts.
As Russia and Ukraine are major suppliers of essential commodities, such as wheat, sunflower seed oil or raw materials for the electronics industry, this broader economic impact includes disruption to supply chains and rising commodity prices. As a result of the crisis, industries worldwide, including those dependent on machine learning and artificial intelligence technologies for business and innovation, have been hit by increased prices and potential shortages.
By Component
Hardware
Software
Services
In 2023, the service sector accounted for 51.8% of the market share. The market is divided into hardware, software and services based on the component. The hardware segment is expected to increase at the highest compound annual growth rate over the forecast period. The growing use of machine learning optimized hardware may be associated with this. The adoption of hardware is supported by the creation of specialised silicon processors that have AI and ML capabilities.
By Enterprise Size
SMEs
Large Enterprises
In 2023, the market was dominated by large enterprises accounting for 66.2% of revenue. The market for machine learning is divided into SMEs and large enterprises, on the basis of business size. More and more large companies are using cloud computing platforms and services for the purpose of machine learning. The ability to train and deploy machine learning models is made possible by the scale and economic infrastructure of cloud platforms.
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By End-Use
Healthcare
BFSI
Law
Retail
Advertising & Media
Automotive & Transportation
Agriculture
Manufacturing
Others
In 2023, North America led the market with a revenue share of 29.7%. Ethical Artificial Intelligence and Responsible AI practices in North America are becoming increasingly important due to the increasing impacts of machine learning on society. In machine learning models and algorithms, organisations place a high priority on fairness, transparency as well as accountability. Efforts are being made to reduce bias, provide for privacy protection and consider ethics in the use of artificial intelligence.
In the Asia Pacific countries, such as China, India and South Korea, machine learning and artificial intelligence technologies are rapidly becoming widespread. AI is being used in emerging economies to boost productivity, support economic growth and tackle societal challenges. Due to government efforts, investments in research and development and a strong technological ecosystem, the region's machine learning industry is expanding.
REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
The major key players are Google, Amazon.com, Intel Corporation, Facebook Inc, Microsoft Corporation, IBM Corporation, Wipro Limited, Nuance Communications, Apple Inc, Cisco Systems, Inc and Other Players.
January 2022 Acquia has introduced advanced retail machine learning models for its customer data platform in order to improve the lifetime value of customers. With this launch, the company aimed to help retailers gain a holistic view of their business. Acquia is helping retailers understand the levers of their marketing and sales efforts.
January 2022 (Collaboration): Stellantis and Amazon collaborated in order to introduce customer-centric connected experiences across millions of vehicles, thereby helping accelerate Stellantis’ software transformation. This agreement will transform the experience of Stellantis customers in their vehicles and advance the transition of the automotive industry towards a software defined
| Report Attributes | Details |
| Market Size in 2024 | US$ 36.74 Bn |
| Market Size by 2031 | US$ 543.55 Bn |
| CAGR | CAGR of 34.9% From 2024 to 2031 |
| Base Year | 2023 |
| Forecast Period | 2024-2031 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Component (Hardware, Software, Services) • By Enterprise Size (SMEs, Large Enterprises) • By End-use (Healthcare, BFSI, Law, Retail, Advertising & Media, Automotive & Transportation, Agriculture, Manufacturing, Others) |
| Regional Analysis/Coverage | North America (USA, Canada, Mexico), Europe (Germany, UK, France, Italy, Spain, Netherlands, Rest of Europe), Asia-Pacific (Japan, South Korea, China, India, Australia, Rest of Asia-Pacific), The Middle East & Africa (Israel, UAE, South Africa, Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America) |
| Company Profiles | Google, Amazon.com, Intel Corporation, Facebook Inc, Microsoft Corporation, IBM Corporation, Wipro Limited, Nuance Communications, Apple Inc, Cisco Systems, Inc |
| Key Drivers | • Development Of technology • Data Generation Proliferation |
| Challenges | • Security of Sensitive Data • The Ethical Implications of the Algorithms Used |
Ans: The Machine Learning Market was valued at USD 36.74 billion in 2023.
Ans: - The Machine Learning Market is growing at a CAGR of 34.9% over the forecast period 2024-2031
Ans: - During the projected period, North America is expected to be the most dominant area.
Ans: - The major key players are Google, Amazon.com, Intel Corporation, Facebook Inc, Microsoft Corporation, IBM Corporation, Wipro Limited, Nuance Communications, Apple Inc, Cisco Systems, Inc
Ans: - Key Stakeholders Considered in the study are Raw material vendors, Regulatory authorities, including government agencies and NGOs, Commercial research, and development (R&D) institutions, Importers and exporters, etc.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact of Russia-Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. Machine Learning Market Segmentation, By Component
9.1 Introduction
9.2 Trend Analysis
9.3 Hardware
9.4 Software
9.5 Services
10. Machine Learning Market Segmentation, By Enterprise Size
10.1 Introduction
10.2 Trend Analysis
10.3 SMEs
10.4 Large Enterprises
11. Machine Learning Market Segmentation, By End-use
11.1 Introduction
11.2 Trend Analysis
11.3 Healthcare
11.4 BFSI
11.5 Law
11.6 Retail
11.7 Advertising & Media
11.8 Automotive & Transportation
11.9 Agriculture
11.10 Manufacturing
11.11 Others
12. Regional Analysis
12.1 Introduction
12.2 North America
12.2.1 USA
12.2.2 Canada
12.2.3 Mexico
12.3 Europe
12.3.1 Eastern Europe
12.3.1.1 Poland
12.3.1.2 Romania
12.3.1.3 Hungary
12.3.1.4 Turkey
12.3.1.5 Rest of Eastern Europe
12.3.2 Western Europe
12.3.2.1 Germany
12.3.2.2 France
12.3.2.3 UK
12.3.2.4 Italy
12.3.2.5 Spain
12.3.2.6 Netherlands
12.3.2.7 Switzerland
12.3.2.8 Austria
12.3.2.9 Rest of Western Europe
12.4 Asia-Pacific
12.4.1 China
12.4.2 India
12.4.3 Japan
12.4.4 South Korea
12.4.5 Vietnam
12.4.6 Singapore
12.4.7 Australia
12.4.8 Rest of Asia Pacific
12.5 The Middle East & Africa
12.5.1 Middle East
12.5.1.1 UAE
12.5.1.2 Egypt
12.5.1.3 Saudi Arabia
12.5.1.4 Qatar
12.5.1.5 Rest of the Middle East
11.5.2 Africa
12.5.2.1 Nigeria
12.5.2.2 South Africa
12.5.2.3 Rest of Africa
12.6 Latin America
12.6.1 Brazil
12.6.2 Argentina
12.6.3 Colombia
12.6.4 Rest of Latin America
13. Company Profiles
13.1 Google
13.1.1 Company Overview
13.1.2 Financial
13.1.3 Products/ Services Offered
13.1.4 SWOT Analysis
13.1.5 The SNS View
13.2 Amazon.com
13.2.1 Company Overview
13.2.2 Financial
13.2.3 Products/ Services Offered
13.2.4 SWOT Analysis
13.2.5 The SNS View
13.3 Intel Corporation
13.3.1 Company Overview
13.3.2 Financial
13.3.3 Products/ Services Offered
13.3.4 SWOT Analysis
13.3.5 The SNS View
13.4 Facebook Inc
13.4.1 Company Overview
13.4.2 Financial
13.4.3 Products/ Services Offered
13.4.4 SWOT Analysis
13.4.5 The SNS View
13.5 Microsoft Corporation
13.5.1 Company Overview
13.5.2 Financial
13.5.3 Products/ Services Offered
13.5.4 SWOT Analysis
13.5.5 The SNS View
13.6 IBM Corporation
13.6.1 Company Overview
13.6.2 Financial
13.6.3 Products/ Services Offered
13.6.4 SWOT Analysis
13.6.5 The SNS View
13.7 Wipro Limited
13.7.1 Company Overview
13.7.2 Financial
13.7.3 Products/ Services Offered
13.7.4 SWOT Analysis
13.7.5 The SNS View
13.8 Nuance Communications
13.8.1 Company Overview
13.8.2 Financial
13.8.3 Products/ Services Offered
13.8.4 SWOT Analysis
13.8.5 The SNS View
13.9 Apple Inc,
13.9.1 Company Overview
13.9.2 Financial
13.9.3 Products/ Services Offered
13.9.4 SWOT Analysis
13.9.5 The SNS View
13.10 Cisco Systems, Inc.
13.10.1 Company Overview
13.10.2 Financial
13.10.3 Products/ Services Offered
13.10.4 SWOT Analysis
13.10.5 The SNS View
14. Competitive Landscape
14.1 Competitive Benchmarking
14.2 Market Share Analysis
14.3 Recent Developments
14.3.1 Industry News
14.3.2 Company News
14.3.3 Mergers & Acquisitions
15. Use Case and Best Practices
16. Conclusion
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