The Global Deep Learning Market Size accounted for USD 10.3 Billion in 2021 and is estimated to garner a market size of USD 415.4 Billion by 2030 rising at a CAGR of 51.1% from 2022 to 2030. Improvement in deep learning algorithm is one of the primary factors boosting the global deep learning market size. In addition, growing penetration of big data analytics is a popular deep learning market trend that is strengthening the industry growth from 2022 to 2030.
Deep Learning Market Report Key Highlights
- Global deep learning market revenue is estimated to reach USD 415.4 Billion by 2030 with a CAGR of 51.1% from 2022 to 2030
- North America deep learning market share accounted for over 39% regional shares in 2021
- According to recent findings, global data creation is projected to grow to more than 180 zettabytes by 2025
- Asia-Pacific deep learning market growth will record fastest CAGR from 2022 to 2030
- Based on component segment, software accounted for approx 50% of the overall market share in 2021
- Introduction of new hardware propels the deep learning market value in coming years
Deep learning is a subdivision of machine learning in artificial intelligence (AI) concerned with the algorithm inspired by the functioning of the human brain termed artificial neural networks. It is also termed deep neural learning or deep neural network. Deep learning is evolved with the increasing amount of unstructured data due to digitalization. The available amount of data is utilized in deep learning to process or understand that data for effective decision-making in various industry verticals including healthcare, manufacturing, automotive, agriculture, retail, security, human resources, marketing, law, and fintech.
Global Deep Learning Market Dynamics
Market Drivers
- Improving computing power
- Growing adoption of cloud-based technology
- Increasing application in big data analytics
- Rising AI adoption in customer-centric services
Market Restraints
- Rising complexity in hardware
- Shortage of technical expertise
Market Opportunities
- Growing demand for deep learning solutions in numerous industries
- Tremendous investments in deep learning technology
Deep Learning Market Report Coverage
| Market |
Deep Learning Market |
| Deep Learning Market Size 2021 |
USD 10.3 Billion |
| Deep Learning Market Forecast 2030 |
USD 415.4 Billion |
| Deep Learning Market CAGR During 2022 - 2030 |
51.1% |
| Deep Learning Market Analysis Period |
2018 - 2030 |
| Deep Learning Market Base Year |
2021 |
| Deep Learning Market Forecast Data |
2022 - 2030 |
| Segments Covered |
By Component, By Application, By End-User, And By Geography
|
| Regional Scope |
North America, Europe, Asia Pacific, Latin America, and Middle East & Africa |
| Key Companies Profiled |
Amazon Web Services (AWS), Google, IBM, Intel, Micron Technology, Microsoft, Nvidia, Qualcomm, Samsung Electronics, Sensory Inc., Skymind, Xilinx, AMD, General Vision, Graphcore, Mellanox Technologies, Huawei Technologies, Fujitsu, Baidu, Mythic, Adapteva, Inc., and Koniku. |
Report Coverage
|
Market Trends, Drivers, Restraints, Competitive Analysis, Player Profiling, Regulation Analysis |
Deep Learning Market Dynamics
Improving computing power and declining hardware costs coupled with the rapidly growing electronics industry. The increasing adoption of cloud-based technology due to the evolution of big data is supporting the deep learning market growth. The increasing adoption of artificial intelligence (AI) based customer-centric services are further propelling the market value. The rising security issues in almost every industry vertical due to online platform usage are further accelerating market growth. In addition, the presence of fewer amounts of structured data and increasing spending in healthcare, travel, tourism, and hospitality industries is anticipated to create potential opportunities in the deep learning market.
On the flip side, increasing complexity in hardware due to the complex algorithms used in technology-based applications is projected to hamper growth over the forecast period. Additionally, the absence of standards and protocols is further expected to hinder the growth to some extent during the estimated period.
Deep Learning Market Segmentation
The worldwide deep learning market is split based on component, application, end-user, and geography.
Deep Learning Market By Component
- Hardware
- Software
- Solution (Software Framework/SDK)
- Platform/API
- Services
- Installation
- Training
- Support & Maintenance
.png "Deep Learning Market Share By ARC")
According to our deep learning industry analysis, the hardware segment is one of the important components because of the increasing need for hardware platforms with high computing power to execute deep learning algorithms. The hardware segment consists of processors such as GPU, FPGA, and CPU among others, memory, and network. The rapidly evolving R&D activities for the expansion of better processing hardware for deep learning is also accelerating the market value. Additionally, the best suitable hardware to support deep learning technology can amplify the results.
Deep Learning Market By Application
- Image Recognition
- Signal Recognition
- Data Mining
- Others
As per our deep learning market forecast, the image recognition segment dominated the global deep learning market with maximum share from 2022 to 2030. The increasing demand for optical character recognition, object recognition, pattern recognition, code recognition, facial recognition, and digital image processing is particularly propelling market growth.
Deep Learning Market By End-User
- Healthcare
- Manufacturing
- Automotive
- Agriculture Retail
- Security
- Human Resources
- Marketing
- Law
- Fintech
On the basis of end-user, the security segment held the dominating share by end-user in the deep learning market. The rising security concern due to the changing cybersecurity ecosystem is supporting the segment growth. The new types of cyberattacks are found in the organization for the concern organizations are investing in preventive measures where deep learning helps in protecting their crucial information without data loss is also positively supporting the deep learning market value.
Deep Learning Market Regional Outlook
North America
Europe
- U.K.
- Germany
- France
- Spain
- Rest of Europe
Latin America
- Mexico
- Brazil
- Rest of Latin America
Asia-Pacific
- India
- Japan
- China
- Australia
- South Korea
- Rest of Asia-Pacific
The Middle East & Africa (MEA)
- Gulf Cooperation Council (GCC)
- South Africa
- Rest of the Middle East & Africa
In 2021, North America held the major share of the global deep learning market
North America dominated the global market with a major share in 2021 due to the presence of advanced technology infrastructure. The major economy of the region including the US and Canada is particularly contributing to the major share of the regional market. The high demand for deep learning applications from industry verticals including healthcare, IT, aerospace & defense, automotive, and telecommunications is additionally supporting the regional market growth.
Deep Learning Market Players
The global deep learning companies profiled in the report include Amazon Web Services (AWS), Google, IBM, Intel, Micron Technology, Microsoft, Nvidia, Qualcomm, Samsung Electronics, Sensory Inc., Skymind, Xilinx, AMD, General Vision, Graphcore, Mellanox Technologies, Huawei Technologies, Fujitsu, Baidu, Mythic, Adapteva, Inc., and Koniku. The major players involved in mergers, acquisitions and strategic partnerships for the expansion of market share.
CHAPTER 1. Industry Overview of Deep Learning Market
1.1. Definition and Scope
1.1.1. Definition of Deep Learning
1.1.2. Market Segmentation
1.1.3. Years Considered for the Study
1.1.4. Assumptions and Acronyms Used
1.1.4.1. Market Assumptions and Market Forecast
1.1.4.2. Acronyms Used in Global Deep Learning Market
1.2. Summary
1.2.1. Executive Summary
1.2.2. Deep Learning Market By Component
1.2.3. Deep Learning Market By Application
1.2.4. Deep Learning Market By End-User
1.2.5. Deep Learning Market By Region
CHAPTER 2. Research Approach
2.1. Methodology
2.1.1. Research Programs
2.1.2. Market Size Estimation
2.1.3. Market Breakdown and Data Triangulation
2.2. Data Source
2.2.1. Secondary Sources
2.2.2. Primary Sources
CHAPTER 3. Market Dynamics And Competition Analysis
3.1. Market Drivers
3.1.1. Driver 1
3.1.2. Driver 2
3.2. Restraints and Challenges
3.2.1. Restraint 1
3.2.2. Restraint 2
3.3. Growth Opportunities
3.3.1. Opportunity 1
3.3.2. Opportunity 2
3.4. Porter’s Five Forces Analysis
3.4.1. Bargaining Power of Suppliers
3.4.2. Bargaining Power of Buyers
3.4.3. Threat of Substitute
3.4.4. Threat of New Entrants
3.4.5. Degree of Competition
3.5. Market Concentration Ratio and Market Maturity Analysis of Deep Learning Market
3.5.1. Go To Market Strategy
3.5.1.1. Introduction
3.5.1.2. Growth
3.5.1.3. Maturity
3.5.1.4. Saturation
3.5.1.5. Possible Development
3.6. Technological Roadmap for Deep Learning Market
3.7. Value Chain Analysis
3.7.1. List of Key Manufacturers
3.7.2. List of Customers
3.7.3. Level of Integration
3.8. Regulatory Compliance
3.9. Competitive Landscape, 2021
3.9.1. Player Positioning Analysis
3.9.2. Key Strategies Adopted By Leading Players
CHAPTER 4. Deep Learning Market By Component
4.1. Introduction
4.2. Deep Learning Revenue By Component
4.2.1. Deep Learning Revenue (USD Million) and Forecast, By Component, 2018-2030
4.2.2. Hardware
4.2.2.1. Hardware Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.2.2. Processor
4.2.2.2.1. Processor Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.2.2.2. GPU
4.2.2.2.2.1. GPU Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.2.2.3. FPGA
4.2.2.2.3.1. FPGA Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.2.2.4. CPU
4.2.2.2.4.1. CPU Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.2.3. Memory
4.2.2.3.1. Memory Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.2.4. Network
4.2.2.4.1. Network Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.3. Software
4.2.3.1. Software Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.3.2. Solution (Software Framework/SDK)
4.2.3.2.1. Solution (Software Framework/SDK) Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.3.3. Platform/API
4.2.3.3.1. Platform/API Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.4. Services
4.2.4.1. Services Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.4.2. Installation
4.2.4.2.1. Installation Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.4.3. Training
4.2.4.3.1. Training Market Revenue (USD Million) and Growth Rate (%), 2018-2030
4.2.4.4. Support & Maintenance
4.2.4.4.1. Support & Maintenance Market Revenue (USD Million) and Growth Rate (%), 2018-2030
CHAPTER 5. Deep Learning Market By End-User
5.1. Introduction
5.2. Deep Learning Revenue By End-User
5.2.1. Deep Learning Revenue (USD Million) and Forecast, By End-User, 2018-2030
5.2.2. Healthcare
5.2.2.1. Healthcare Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.3. Manufacturing
5.2.3.1. Manufacturing Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.4. Automotive
5.2.4.1. Automotive Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.5. Agriculture
5.2.5.1. Agriculture Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.6. Retail
5.2.6.1. Retail Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.7. Security
5.2.7.1. Security Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.8. Human Resources
5.2.8.1. Human Resources Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.9. Marketing
5.2.9.1. Marketing Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.10. Law
5.2.10.1. Law Market Revenue (USD Million) and Growth Rate (%), 2018-2030
5.2.11. Fintech
5.2.11.1. Fintech Market Revenue (USD Million) and Growth Rate (%), 2018-2030
CHAPTER 6. North America Deep Learning Market By Country
6.1. North America Deep Learning Market Overview
6.2. U.S.
6.2.1. U.S. Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
6.2.2. U.S. Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
6.2.3. U.S. Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
6.3. Canada
6.3.1. Canada Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
6.3.2. Canada Deep Learning Revenue (USD Million) and Forecast By Applicaton, 2018-2030
6.3.3. Canada Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
6.4. North America PEST Analysis
CHAPTER 7. Europe Deep Learning Market By Country
7.1. Europe Deep Learning Market Overview
7.2. U.K.
7.2.1. U.K. Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
7.2.2. U.K. Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
7.2.3. U.K. Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
7.3. Germany
7.3.1. Germany Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
7.3.2. Germany Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
7.3.3. Germany Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
7.4. France
7.4.1. France Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
7.4.2. France Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
7.4.3. France Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
7.5. Spain
7.5.1. Spain Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
7.5.2. Spain Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
7.5.3. Spain Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
7.6. Rest of Europe
7.6.1. Rest of Europe Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
7.6.2. Rest of Europe Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
7.6.3. Rest of Europe Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
7.7. Europe PEST Analysis
CHAPTER 8. Asia Pacific Deep Learning Market By Country
8.1. Asia Pacific Deep Learning Market Overview
8.2. China
8.2.1. China Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
8.2.2. China Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
8.2.3. China Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
8.3. Japan
8.3.1. Japan Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
8.3.2. Japan Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
8.3.3. Japan Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
8.4. India
8.4.1. India Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
8.4.2. India Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
8.4.3. India Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
8.5. Australia
8.5.1. Australia Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
8.5.2. Australia Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
8.5.3. Australia Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
8.6. South Korea
8.6.1. South Korea Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
8.6.2. South Korea Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
8.6.3. South Korea Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
8.7. Rest of Asia-Pacific
8.7.1. Rest of Asia-Pacific Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
8.7.2. Rest of Asia-Pacific Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
8.7.3. Rest of Asia-Pacific Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
8.8. Asia Pacific PEST Analysis
CHAPTER 9. Latin America Deep Learning Market By Country
9.1. Latin America Deep Learning Market Overview
9.2. Brazil
9.2.1. Brazil Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
9.2.2. Brazil Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
9.2.3. Brazil Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
9.3. Mexico
9.3.1. Mexico Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
9.3.2. Mexico Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
9.3.3. Mexico Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
9.4. Rest of Latin America
9.4.1. Rest of Latin America Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
9.4.2. Rest of Latin America Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
9.4.3. Rest of Latin America Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
9.5. Latin America PEST Analysis
CHAPTER 10. Middle East & Africa Deep Learning Market By Country
10.1. Middle East & Africa Deep Learning Market Overview
10.2. GCC
10.2.1. GCC Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
10.2.2. GCC Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
10.2.3. GCC Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
10.3. South Africa
10.3.1. South Africa Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
10.3.2. South Africa Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
10.3.3. South Africa Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
10.4. Rest of Middle East & Africa
10.4.1. Rest of Middle East & Africa Deep Learning Revenue (USD Million) and Forecast By Component, 2018-2030
10.4.2. Rest of Middle East & Africa Deep Learning Revenue (USD Million) and Forecast By Application, 2018-2030
10.4.3. Rest of Middle East & Africa Deep Learning Revenue (USD Million) and Forecast By End-User, 2018-2030
10.5. Middle East & Africa PEST Analysis
CHAPTER 11. Player Analysis Of Deep Learning Market
11.1. Deep Learning Market Company Share Analysis
11.2. Competition Matrix
11.2.1. Competitive Benchmarking of key players by price, presence, market share, and R&D investment
11.2.2. New Product Launches and Product Enhancements
11.2.3. Mergers And Acquisition In Global Deep Learning Market
11.2.4. Partnership, Joint Ventures and Strategic Alliances/ Sales Agreements
CHAPTER 12. Company Profile
12.1. Amazon Web Services (AWS)
12.1.1. Company Snapshot
12.1.2. Business Overview
12.1.3. Financial Overview
12.1.3.1. Revenue (USD Million), 2021
12.1.3.2. Amazon Web Services (AWS) 2021 Deep Learning Business Regional Distribution
12.1.4. Product /Service and Specification
12.1.5. Recent Developments & Business Strategy
12.2. Google
12.3. IBM
12.4. Intel
12.5. Micron Technology
12.6. Microsoft
12.7. Nvidia
12.8. Qualcomm
12.9. Samsung Electronics
12.10. Sensory Inc.
12.11. Skymind
12.12. Xilinx
12.13. AMD
12.14. General Vision
12.15. Graphcore
12.16. Mellanox Technologies
12.17. Huawei Technologies
12.18. Fujitsu
12.19. Baidu
12.20. Mythic
12.21. Adapteva, Inc.
12.22. Koniku
