Digital transformation is a method of using digital technology for changing current business approaches into more advance and technologically driven business approaches for increasing customer satisfaction and to enhance revenue opportunities. In addition, various banks, fintech and insurance companies are adopting digital banking platform for increasing transparency among the enterprises and to building more trust among the employees. Furthermore, various insurance companies across the globe are adopting digital transformation to increase productivity of employees as well as to save time and resources of the company.
Deep learning is a subset of machine learning (ML) and artificial intelligence (AI) to imitate the human learning process to learn by example. The technology helps data scientists as it aids in facilitating and accelerating the collection process, analyzing process, and processing process for large amounts of data. In addition, it makes complex correlations between data and learning from examples and previous mistakes. Furthermore, deep learning technology powers chatbots to deliver excellent customer experience and satisfaction. Moreover, deep learning along with ML and AI enables voice assistant work such as iPhone Siri and Google Assistant. In addition, the technology helps e-commerce sites to navigate rapidly. Hence, deep learning technology has various uses and is assisting in various industries.
The key factors that drive the growth of the deep learning market include growing data availability and advancements in hardware technology. The proliferation of digital devices and online platforms is generating massive datasets. This is encouraging the adoption of deep learning techniques to extract meaningful insights from these data. Furthermore, the development of powerful graphics processing units (GPUs) and specialized hardware accelerators such as tensor processing units (TPUs) is enabling faster training and inference of deep learning models. However, increasing data security concerns and high computational requirements is expected to hamper the market growth. Collecting and storing large amounts of sensitive data is raising concerns about data privacy and security breaches. Moreover, training high complex models require expensive hardware which is out of range for medium and small-size companies. On the contrary, industry-specific applications and natural language processing is expected to offer remunerative opportunities for the expansion of the global deep learning market during the forecast period. Deep learning technology helps in providing customized solutions to different industries such as healthcare, manufacturing, finance, and others. Furthermore, natural language processing powered by deep learning could transform customer service, sentiment analysis, language translation, and content generation.
The deep learning market is segmented on the basis of component, application, industry vertical, technology, and region. In terms of components, the market is bifurcated into hardware, software, and service. By application, the market is divided into image recognition, signal recognition, data mining, and others. Based on industry vertical, it is divided into security, marketing, automotive, retail & e-commerce, healthcare, manufacturing, law, and others. On the basis of region, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The report analyzes the profiles of key players operating in the deep learning market such as Advanced Micro Devices Inc., Amazon Web Services, Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung and Xilinx. These players have adopted various strategies to increase their market penetration and strengthen their position in the deep learning market.
Deep learning is a subset of machine learning (ML) and artificial intelligence (AI) to imitate the human learning process to learn by example. The technology helps data scientists as it aids in facilitating and accelerating the collection process, analyzing process, and processing process for large amounts of data. In addition, it makes complex correlations between data and learning from examples and previous mistakes. Furthermore, deep learning technology powers chatbots to deliver excellent customer experience and satisfaction. Moreover, deep learning along with ML and AI enables voice assistant work such as iPhone Siri and Google Assistant. In addition, the technology helps e-commerce sites to navigate rapidly. Hence, deep learning technology has various uses and is assisting in various industries.
The key factors that drive the growth of the deep learning market include growing data availability and advancements in hardware technology. The proliferation of digital devices and online platforms is generating massive datasets. This is encouraging the adoption of deep learning techniques to extract meaningful insights from these data. Furthermore, the development of powerful graphics processing units (GPUs) and specialized hardware accelerators such as tensor processing units (TPUs) is enabling faster training and inference of deep learning models. However, increasing data security concerns and high computational requirements is expected to hamper the market growth. Collecting and storing large amounts of sensitive data is raising concerns about data privacy and security breaches. Moreover, training high complex models require expensive hardware which is out of range for medium and small-size companies. On the contrary, industry-specific applications and natural language processing is expected to offer remunerative opportunities for the expansion of the global deep learning market during the forecast period. Deep learning technology helps in providing customized solutions to different industries such as healthcare, manufacturing, finance, and others. Furthermore, natural language processing powered by deep learning could transform customer service, sentiment analysis, language translation, and content generation.
The deep learning market is segmented on the basis of component, application, industry vertical, technology, and region. In terms of components, the market is bifurcated into hardware, software, and service. By application, the market is divided into image recognition, signal recognition, data mining, and others. Based on industry vertical, it is divided into security, marketing, automotive, retail & e-commerce, healthcare, manufacturing, law, and others. On the basis of region, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The report analyzes the profiles of key players operating in the deep learning market such as Advanced Micro Devices Inc., Amazon Web Services, Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung and Xilinx. These players have adopted various strategies to increase their market penetration and strengthen their position in the deep learning market.
Key Benefits for Stakeholders
- The study provides an in-depth analysis of the global deep learning market along with the current & future trends to illustrate the imminent investment pockets.
- Information about key drivers, restraints, & opportunities and their impact analysis on the global deep learning market size is provided in the report.
- Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
- The quantitative analysis of the global deep learning market from 2022 to 2032 is provided to determine the market potential.
Additional benefits you will get with this purchase are:
- Quarterly update (only available with the purchase of an enterprise license)
- 5 additional company profiles of your choice, pre- or post-purchase, as a free update.
- Free updated version (once released) with the purchase of a 1-5 or enterprise user license.
- 16 analyst hours of support (post-purchase, if you find additional data requirements upon review of the report, you may receive support amounting to 16 analyst hours to solve questions, and post-sale queries)
- 15% free customization (in case the scope or segment of the report does not match your requirements, 20% is equivalent to 3 working days of free work, applicable once)
- Free data pack (Excel version) with the purchase of a 1-5 or enterprise user license.
- Free report update, if the report is 6-12 months old or older.
- 24-hour priority response
- Free industry updates and white papers.
Key Market Segments
By Component
- Software
- Service
- Hardware
By Application
- Image recognition
- Signal recognition
- Data mining
- Others
By Industry Vertical
- Security
- Marketing
- Automotive
- Retail and E-Commerce
- Healthcare
- Manufacturing
- Law
- Others
By Region
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- France
- Italy
- Spain
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- Australia
- South Korea
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
Key Market Players
- Amazon Web Services, Inc.
- Google LLC
- IBM Corporation
- Microsoft Corporation
- NVIDIA Corporation
- Xilinx
- Samsung
- Advanced Micro Devices Inc. (Xilinx Inc.)
- Intel Corporation
- Qualcomm Technologies, Inc.
Table of Contents
CHAPTER 1: INTRODUCTION
CHAPTER 2: EXECUTIVE SUMMARY
CHAPTER 3: MARKET OVERVIEW
CHAPTER 4: DEEP LEARNING MARKET, BY COMPONENT
CHAPTER 5: DEEP LEARNING MARKET, BY APPLICATION
CHAPTER 6: DEEP LEARNING MARKET, BY INDUSTRY VERTICAL
CHAPTER 7: DEEP LEARNING MARKET, BY REGION
CHAPTER 8: COMPETITIVE LANDSCAPE
CHAPTER 9: COMPANY PROFILES
List of Tables
List of Figures
Executive Summary
According to this report, the deep learning market was valued at $16.9 billion in 2022, and is estimated to reach $406 billion by 2032, growing at a CAGR of 37.8% from 2023 to 2032.The Deep Learning Market is likely to experience a significant growth rate of 37.8% from 2023-2032 owing to increasing market demand for data mining
Deep learning is a kind of artificial intelligence and machine learning technology that imitates human behavior to generate human brain cells-generated information. The technology is useful in performing classification tasks and recognizing patterns in photos, text, audio, and other data. In addition, it is utilized to automate jobs that ordinarily call for human intellect, such as annotating photographs and transcribing audio files.
Increased data accessibility and hardware advancements are driving the growth of the deep learning market. This is what is driving the market for deep learning: the explosion of digital data in sectors like healthcare, banking, retail, and manufacturing needs the use of cutting-edge techniques like deep learning to analyze and extract insightful knowledge from vast volumes of data. Reduced hardware prices and more funding for research and development to enable deep learning are also two other industry growth drivers. Furthermore, the market's primary growth drivers include reducing hardware costs and rising investment in research and development to support deep learning. However, increasing complexity in hardware due to complex algorithm used in technology is a major factor that hampers the growth of the market. Complex algorithms require more computational resources to produce accurate results. In addition, to support deep learning technology hardware with higher complexities are required which are difficult to manage and operate.
The market also offers growth opportunities to the key players in the market. Rise in investments in different industrial sectors presents a significant opportunity for the deep learning market. A number of variables, including ageing populations, improvements in medical technology, and increasing demand for healthcare services, are causing healthcare spending to rise steadily in many nations. Further, the manufacturing sector's rising investments in R&D, capital equipment, labor, technology adoption, and innovation are opening up opportunities for the growth of the deep learning industry.
The deep learning market is segmented on the basis of component, application, industry vertical, technology, and region. In terms of component, the market is bifurcated into hardware, software, and service. By application, the market is divided into image recognition, signal recognition, data mining, and others. Based on industry vertical, it is divided into security, marketing, automotive, retail & e-commerce, healthcare, manufacturing, law, and others. Region wise, it is analyzed across North America (the U. S., and Canada), Europe (UK, Germany, France, Italy, Spain, and rest of Europe), Asia-Pacific (China, India, Japan, Australia, South Korea and rest of Asia-Pacific), and LAMEA (Latin America, Middle East, and Africa).
The key players profiled in the study are Advanced Micro Devices Inc., Amazon Web Services Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung, and Xilinx. The players in the market have been actively engaged in the adoption various strategies such as collaboration, product launch, and partnership to remain competitive and gain advantage over the competitors in the market. For instance, in March 2023 Amazon Web Services, Inc. collaborated with NVIDIA Corporation to build world largest on-demand artificial intelligence infrastructure to train complex large language models (LLMs) and develop generative AI applications. This collaboration has the potential to drive the growth of deep-learning models. Moreover, in August 2021, IBM Corporation launched IBM Telum Processor. The processor is designed to deploy deep learning into enterprise workloads to address fraud in real time in the finance and insurance sector. The processor contains chip hardware that helps customers achieve business insights at scale across banking, finance, trading, insurance applications, and customer interactions. Therefore, such strategies foster deep learning market growth in the ICT sector.
Key Market Insights
By component, the software segment was the highest revenue contributor to the market, and is estimated to $230.18 billion by 2032, with a CAGR of 40.2%. However, the same segment is expected to be the fastest growing segment during the forecast period.By application, the image recognition segment dominated the global market, and is estimated to reach $123.08 billion by 2032, with a CAGR of 33.3%. However, the data mining segment is expected to be the fastest growing segment with the CAGR of 41.6% during the forecast period.
By industry vertical, the security segment dominated the global market, and is estimated to reach $48.36 billion by 2032, with a CAGR of 29.1%. However, the healthcare segment is expected to be the fastest growing segment with the CAGR of 43.8% during the forecast period.
Based on region, North America was the highest revenue contributor, accounting for $6.23 billion in 2022, and is estimated to reach $124.03 billion by 2032, with a CAGR of 35.2%.
Companies Mentioned
- Amazon Web Services, Inc.
- Google LLC
- IBM Corporation
- Microsoft Corporation
- NVIDIA Corporation
- Xilinx
- Samsung
- Advanced Micro Devices Inc.(Xilinx Inc.)
- Intel Corporation
- Qualcomm Technologies, Inc.
Methodology
The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.
They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.
They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:
- Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
- Scientific and technical writings for product information and related preemptions
- Regional government and statistical databases for macro analysis
- Authentic news articles and other related releases for market evaluation
- Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast
Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.
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