Report Scope & Overview:

The Machine Learning Market size was valued at US$ 27.11 Bn in 2022 and is expected to reach US$ 472.25 Bn by 2030, and grow at a CAGR of 42.93% over the forecast period 2023-2030.

Machine learning is described as the application of artificial intelligence (AI) to give the system the capacity to automatically learn and improve from experience without being explicitly programmed. This technology is primarily concerned with creating software that can access data and utilize it to learn for itself.

Machine Learning Market Revenue Analysis

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Machine learning is an artificial intelligence discipline that allows machines to learn directly from data, experience, and examples. Machine learning enables computers to carry out complicated operations by learning from examples or data rather than following pre-programmed rules by allowing computers to execute certain jobs intelligently. The increasing volume of data collected across industrial verticals offers an extensive reservoir for machines to learn from, which is further supported by significant advances in computer processing power, which improves the analytical skills of machine learning systems.

The primary objective of machine learning is to enable computers to learn autonomously and change their actions without the need for human intervention. The machine learning process employs a variety of methodologies, including supervised machine learning algorithms, unsupervised machine learning algorithms, semi-supervised machine learning algorithms, and reinforcement machine learning algorithms.



  • Development Of technology.

  • Data Generation Proliferation.


  • Employee Skill Scarcity.


  • Demand for Intelligent Business Processes is Growing.

  • Adoption in Modern Applications is Growing.


  • Security of Sensitive Data.

  • The Ethical Implications of the Algorithms Used.


The preceding 19 scenarios, like those in other sectors, have had an impact on the Machine Learning Industry. Despite the harsh conditions and unpredictable collapse, certain sectors thrive during pandemics. At the time of covid 19, the Machine Learning Market was steady, with strong development and prospects. In comparison to other industries, the worldwide market for machine learning has had limited influence.

Because of automation breakthroughs and technical advancements, the worldwide Machine Learning Market saw sluggish growth. The availability of old machines and cell phones for remote work has resulted in good market development. Several industries applied machine learning systems in new technologies to advance the market.


The market is separated into three components: hardware, software, and services. The hardware category is predicted to grow at the fastest rate over the projection period. This might be attributable to the increasing deployment of machine learning-optimized hardware. The development of customized silicon chips with AI and ML capabilities is propelling hardware adoption. The software category is estimated to account for a small portion of the market. Cloud-based software use is expected to increase as cloud infrastructure and hosting factors improve. Cloud-based software enables customers to go from machine learning to deep learning, increasing acceptance. In recent years, there has been an increase in demand for machine learning services.

The machine learning market is divided into two segments based on company size: small and medium enterprises (SMEs) and big organizations. In 2022, the big enterprise sector held the largest market share. This is because technologies such as artificial intelligence and data science are increasingly being used to inject predictive insights into corporate processes. Machine learning is becoming increasingly popular among small and medium-sized businesses. This is due to machine learning's simple and cost-effective implementation. The availability of cloud, on-premise, and hybrid deployment options enables SMEs to rapidly scale up their expanding pilot projects and artificial intelligence efforts, avoiding the need for huge upfront expenditures.

The market is divided into BFSI, healthcare, retail, legal, advertising and media, agricultural, manufacturing, automotive and transportation, and others based on end-use. While advertising and media retained the highest share in 2022, the healthcare sector is predicted to overtake this area by the end of the projection period. This is owing to the increasing use of this technology in developing healthcare fields. Over the projection period, the legal segment is predicted to have the greatest CAGR. This is owing to the increasing use of machine learning algorithms in a variety of legal applications. In the context of litigation, ML is employed for continual active learning during the document review process.

The market is divided into two segments depending on the deployment model: cloud-based and on-premise. During the forecast period, the cloud deployment option is predicted to have the biggest market share and grow at the fastest CAGR in the machine learning market. Some of the critical benefits that have resulted in the adoption of cloud-based delivery models for machine learning software solutions and services include flexibility, automated software updates, disaster recovery via cloud-based backup systems, increased collaboration, monitoring document version control, and data loss prevention via robust cloud storage facilities.


On The Basis of Component

  • Hardware

  • Software

  • Services

On The Basis of Enterprise Size

  • SMEs

  • Large Enterprises

On The Basis of By Deployment Model

  • Cloud-based

  • On-premise

On The Basis of End-use

  • Healthcare

  • BFSI

  • Law

  • Retail

  • Advertising & Media

  • Automotive & Transportation

  • Agriculture

  • Manufacturing

  • Others

Machine Learning Market Segmentation Analysis

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During the projected period, North America is expected to be the most dominant area. This is due to the engagement of more developed nations in the R&D industry, as well as their fresh ideas and modern technology. The compound annual growth rate in the Asia Pacific areas is expected to rise, according to the prediction. The main explanation for this rising CAGR estimate is increased corporate productivity awareness in Asia Pacific sectors. The Asian Machine Learning Market provides seasoned machine learning expertise and is the most promising area in the world.


  • North America

    • USA

    • Canada

    • Mexico

  • Europe

    • Germany

    • UK

    • France

    • Italy

    • Spain

    • The 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


The major key players are Google,, Intel Corporation, Facebook Inc, Microsoft Corporation, IBM Corporation, Wipro Limited, Nuance Communications, Apple Inc, Cisco Systems, Inc and Other Players

Machine Learning Market Report Scope:
Report Attributes Details
 Market Size in 2022  US$ 27.11 Bn
 Market Size by 2030  US$ 472.25 Bn
 CAGR   CAGR of 42.93% From 2023 to 2030
 Base Year  2022
 Forecast Period  2023-2030
 Historical Data  2020-2021
 Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
 Key Segments • By Component (Hardware, Software, and Services)
• By Enterprise Size (SMEs and Large Enterprises)
• By Deployment Model (Cloud-based and On-premise)
• 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,, 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


Frequently Asked Questions

Ans: - The Machine Learning market size was valued at USD 27.11 Bn in 2022.

Ans: - The Machine Learning Market is growing at a CAGR of 42.93% over the forecast period 2023-2030.

Ans: - During the projected period, North America is expected to be the most dominant area.

Ans: - The major key players are Google,, 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. Research Methodology


3. Market Dynamics

3.1 Drivers

3.2 Restraints

3.3 Opportunities

3.4 Challenges


4. Impact Analysis

4.1 COVID-19 Impact Analysis

4.2 Impact of Ukraine- Russia war

4.3 Impact of ongoing Recession

4.3.1 Introduction

4.3.2 Impact on major economies US Canada Germany France United Kingdom China Japan South Korea Rest of the World


5. Value Chain Analysis


6. Porter’s 5 forces model


7. PEST Analysis


8. Machine Learning Market Segmentation, by Component

8.1 Hardware

8.2 Software

8.3 Services


9. Machine Learning Market Segmentation, by Enterprise Size

9.1 SMEs

9.2 Large Enterprises


10. Machine Learning Market Segmentation, by Deployment Model

10.1 Cloud-based

10.2 On-premise


11. Machine Learning Market Segmentation, by End-use

11.1 Healthcare

11.2 BFSI

11.3 Law

11.4 Retail

11.5 Advertising & Media

11.6 Automotive & Transportation

11.7 Agriculture

11.8 Manufacturing

11.9 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 Germany

12.3.2 UK

12.3.3 France

12.3.4 Italy

12.3.5 Spain

12.3.6 The Netherlands

12.3.7 Rest of Europe

12.4 Asia-Pacific

12.4.1 Japan

12.4.2 South Korea

12.4.3 China

12.4.4 India

12.4.5 Australia

12.4.6 Rest of Asia-Pacific

12.5 The Middle East & Africa

12.5.1 Israel

12.5.2 UAE

12.5.3 South Africa

12.5.4 Rest

12.6 Latin America

12.6.1 Brazil

12.6.2 Argentina

12.6.3 Rest of Latin America


13. Company Profiles

13.1 Google  

13.1.1 Financial

13.1.2 Products/ Services Offered

13.1.3 SWOT Analysis

13.1.4 The SNS view


13.3 Intel Corporation

13.4 Facebook Inc

13.5 Microsoft Corporation

13.6 IBM Corporation

13.7 Wipro Limited

13.8 Nuance Communications

13.9 Apple Inc

13.10 Cisco Systems, Inc


14. Competitive Landscape

14.1 Competitive Benchmarking

14.2 Market Share Analysis

14.3 Recent Developments


15. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

Step 3: Data Bank Validation

Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.

Data Bank Validation

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