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The Global Deep Learning Market size is estimated to grow at a CAGR of 29.79% between 2022 and 2027. The size of the market is forecast to increase by USD 11,113.13 million. The growth of the market depends on several factors, including the increasing entry of startups, the growing application of deep learning, and new product launches.
This report extensively covers market segmentation by application (image recognition, voice recognition, video surveillance and diagnostics, and data mining), type (software, services, and hardware), and geography (APAC, North America, Europe, Middle East and Africa, and South America). It also includes an in-depth analysis of drivers, trends, and challenges. Furthermore, the report includes historic market data from 2017 to 2021.
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The increasing entry of startups is notably driving the market growth, although factors such as the lack of technical expertise may impede the market growth. Our researchers studied the data for years, with 2022 as the base year and 2023 as the estimated year, and presented the key drivers, trends, and challenges for the market. Although there has been a decrease in demand for the market during the COVID-19 pandemic, a holistic analysis of drivers will help companies refine marketing strategies to gain a competitive advantage.
The increasing entry of startups is the key factor driving the global deep learning market growth. The market has witnessed an influx of startups in recent years. A rise in the number of startups as a result of increased funding from various global investors is expected to drive the growth of the market during the forecast period.
The increase in funding in the field of deep learning has encouraged several startups to apply this technology across a wide range of industry verticals. Some of the startups offer deep learning technologies for various application areas, including healthcare, automation and robotics, and security. Therefore, the increasing number of startups, coupled with the widening application areas for deep learning, is driving the growth of the global deep learning market.
The increasing number of collaborations among vendors will fuel the global deep-learning market growth. The increase in collaborations/partnerships among vendors is expected to drive the growth of the market during the forecast period. Such collaborations/partnerships help market participants expand their product portfolios, geographic presence, and distribution networks.
Strategic collaboration initiatives enable vendors to gain access to new products, technologies, and resources and improve their market shares, thereby driving business growth. Thus, the increase in collaborations among vendors is expected to support the growth of the market in focus during the forecast period.
The lack of technical expertise is a major challenge to the global deep learning market growth. Deep learning technology requires a completely different set of technical skills and business expertise than that needed for traditional data analysis. The implementation of a deep learning model is very complex and requires advanced knowledge of machine learning and programming languages. The lack of proper technical expertise in most organizations limits the growth of the market.
There are a limited number of subject matter experts who can provide context and proper clarity to business problems, while many organizations, especially SMEs with budget constraints are not in a position to hire the right talent. Additionally, it is time-consuming for organizations to find well-trained professionals with the right skill sets. Therefore, the shortage of technical and business expertise in organizations prevents them from implementing deep learning models to deliver the desired business output, which, in turn, limits the growth of the market.
Our analysis of the life cycle of the market indicates a movement from the innovator’s stage to the laggard’s stage. Technavio has included key purchase criteria, adoption rates, adoption lifecycles, and drivers of price sensitivity to help companies evaluate and develop growth strategies from 2022 to 2027.
Global Deep Learning Market Customer Landscape
The market share growth by the image recognition segment will be significant during the forecast period. Images are real and extensive and, therefore, cannot be forged easily. This makes image repositories important in big data. Thus, exploiting such valuable data can be a great source of information for banks and financial institutions.
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The image recognition segment showed a gradual increase in market share with USD 961.65 million in 2017 and continued to grow by 2021. For example, Facebook can identify and map around 98% of its images correctly to the right person. Imaging technology is being used for identifying and removing fake social accounts on Facebook. Such image-based identification of fake accounts has massive potential to enrich the risk modeling and credit scoring of banks, which increases the demand for AI image recognition in the BFSI sector. Thus, with the growing importance of the image processing and recognition application of AI, the market is expected to witness positive growth during the forecast period. Furthermore, our report provides a brief analysis of the historical and forecast market share and their segments along with the reasons for growth from 2017 to 2027.
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North America is projected to contribute 37% of market growth by 2027. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
The major factor driving the growth of the market in North America is the increasing use of deep learning in various industrial applications, such as voice recognition, image recognition, and smartphone assistants. The growing awareness about the advantages of deep learning has increased its adoption in these industrial applications. Deep learning algorithms help in reducing labor costs by a significant margin. Moreover, deep learning helps organizations save unnecessary costs associated with product recalls by easily detecting subjective defects such as product labeling errors. Deep learning models can perform tasks efficiently and in a much shorter period of time. Owing to the above-mentioned advantages, industries based in North America are increasingly adopting deep learning technologies, which is driving the growth of the deep learning market in the region.
This report forecasts the contribution of all the segments to the growth of the market. In addition, we have included the COVID-19 impact and the recovery strategies for each segment. The outbreak of COVID-19 led to a decline in demand for deep learning solutions in North America. The COVID-19 pandemic spread widely across North America, especially in the US, in 2020. Countries such as the US and Canada imposed lockdowns and travel restrictions to combat the spread of the disease. This directly affected the demand for and supply of deep-learning hardware products and services. However, the demand for deep learning software from the healthcare industry increased during this period. In Q4 2021, the governments also rolled out large-scale vaccination programs, which helped the economy recover gradually. Such developments will influence the growth of the regional market during the forecast period.
Vendors are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market
Atomwise - The company offers deep learning solutions, such as applying deep learning to locate novel allosteric modulators in silico for drug discovery. Also, through this segment, the company develops artificial intelligence systems using deep learning algorithms and supercomputers for drug discovery.
We also have detailed analyses of the market’s competitive landscape and offer information on 20 market vendors, including :
Qualitative and quantitative analysis of vendors has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize vendors as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize vendors as dominant, leading, strong, tentative, and weak.
US Deep Learning market - The market share will grow rapidly at a CAGR of more than 57% by 2021.
Our report forecasts revenue growth at global, regional & country levels and provides an analysis of the latest trends and growth opportunities from 2017 to 2027. The market has been segmented by application, type, and region.
Deep Learning Market Scope |
|
Report Coverage |
Details |
Page number |
173 |
Base year |
2022 |
Historical year |
2017-2021 |
Forecast period |
2023-2027 |
Growth momentum & CAGR |
Accelerate at a CAGR of 29.79% |
Market growth 2023-2027 |
USD 11,113.13 million |
Market structure |
Fragmented |
YoY growth (%) |
20.0 |
Regional analysis |
North America, Europe, APAC, South America, and the Middle East and Africa |
Performing market contribution |
North America at 37% |
Key consumer countries |
US, Canada, China, UK, and Germany |
Competitive landscape |
Leading companies, Competitive Strategies, Consumer engagement scope |
Key companies profiled |
Amazon.com Inc., Atomwise Inc., Comma.ai Inc., Deep Instinct, DeepMind Technologies Ltd., Graphcore Ltd., H2O.ai Inc., Hewlett Packard Enterprise Co., Intel Corp., International Business Machines Corp., Micron Technology Inc., Microsoft Corp., Mphasis Ltd., NVIDIA Corp., Qualcomm Inc., Samsung Electronics Co. Ltd., Sensory Inc., Teledyne FLIR LLC, Viz.ai Inc., and Xilinx Inc. |
Market dynamics |
Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, and Market condition analysis for the forecast period. |
Customization purview |
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized. |
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