Report Id: SNS/ICT/2206 | July 2022 | Region: Global | 128 Pages
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 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.
IMPACT OF COVID-19:
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 2021, 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 2021, 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.
KEY MARKET SEGMENTS:
On The Basis of Component
On The Basis of Enterprise Size
On The Basis of By Deployment Model
On The Basis of End-use
Advertising & Media
Automotive & Transportation
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.
Rest of Europe
Rest of Asia-Pacific
The Middle East & Africa
Rest of Middle East & Africa
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
|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|
|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, 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
Frequently Asked Questions (FAQ) :
Ans: - The Machine Learning market size was valued at USD18.97Bn in 2021.
Ans: - Demand for Intelligent Business Processes is Growing. and adoption in Modern Applications is Growing.
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
1.1 Market Definition
1.3 Research Assumptions
2. Research Methodology
3. Market Dynamics
4. Impact Analysis
4.1 COVID-19 Impact Analysis
4.2 Impact of Ukraine- Russia war
4.3 Impact of ongoing Recession
4.3.2 Impact on major economies
184.108.40.206 United Kingdom
220.127.116.11 South Korea
18.104.22.168 Rest of the World
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. Machine Learning Market Segmentation, by Component
9. Machine Learning Market Segmentation, by Enterprise Size
9.2 Large Enterprises
10. Machine Learning Market Segmentation, by Deployment Model
11. Machine Learning Market Segmentation, by End-use
11.5 Advertising & Media
11.6 Automotive & Transportation
12. Regional Analysis
12.2 North America
12.3.6 The Netherlands
12.3.7 Rest of Europe
12.4.2 South Korea
12.4.6 Rest of Asia-Pacific
12.5 The Middle East & Africa
12.5.3 South Africa
12.6 Latin America
12.6.3 Rest of Latin America
13. Company Profiles
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
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of the good and accurate research report and selecting the best methodology to complete 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.
Step 2: Primary Research
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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.
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.
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