Deep Learning Market Research Report – Forecast to 2023

Global Deep Learning Market Research Report: By Component (Hardware, Software, Services), By Application (Image Recognition, Data Mining, Signal Recognition), By End User (Security, Manufacturing, BFSI, Healthcare, Agriculture) - Forecast till 2023

ID: MRFR/ICT/4600-CR | May 2019 | Region: Global | 177 pages

Market Overview

Global Deep Learning Market is projected to reach USD 17.4 Billion by 2023, registering a 30.87% CAGR during the forecast period (2018–2023).

Deep learning technology is seeing many exciting developments in various machine learning domains, including reinforcement learning, natural language processing (NLP), ML frameworks (Pytorch and TensorFlow), and more. Industrial equipment is progressively turning out to be smart, becoming more useful in condition monitoring, and predictive support. 

Today, artificial intelligence and deep learning capabilities have become exceptionally essential structures, discovering their way into the core of embedded devices. Increasing numbers of smart devices are being introduced, and embedded AI and deep learning technology improve these devices, making them intelligent. Many ML/AI conversation organizations are hoping to use neural networks and deep learning to conjecture time series data.

COVID-19 Analysis

The COVID- 19 pandemic has helped reestablish the most sought-after technologies, such as artificial intelligence, deep learning, machine learning, DevOps, and big data. Pre pandemic, the deep learning technology was already having a big impact on transportation, healthcare, banking, and manufacturing. 

Pandemic-related logistics problems prompted manufacturing companies to consider new automation & control technologies that offset higher wages and increase efficiency. Resultantly, the global deep learning industry began to garner traction, witnessing an increase in automation investments continually. 

To help healthcare workers, innovative industry players started building on emerging cold chain solutions and burgeoning interest in automated vitals monitoring process using the AI-based contactless and remote model. These companies leveraged decision trees, classifications, and deep learning models such as convolutional neural networks, recurrent neural networks for machine learning. 

Ramping up deep learning technology, medical device companies innovated advanced health intelligence trackers and contactless monitoring devices, eliminating the need to spend hours taking patient's readings, and doctors could remotely monitor the data through the dashboard.

Market Dynamics 


Rising Automation to Bolster the Deep Learning Market Opportunities 

Computer vision is one of the major developments in industrial processes, revolutionizing the operation. Besides, deep learning market trends such as rising uses of humanoid robots and augmented (AR) and virtual reality (VR) displays in the automotive and 3D gaming sectors impact the market growth. 

Using deep learning models, computer vision trains computers to interpret and understand the visual world and enable machines to accurately identify objects in videos or images in documents and react to what they see. In manufacturing, computer vision can improve defect detection rates by up to 90 percent.

In banking, computer vision can be used to spot counterfeit bills or for processing document images, rapidly robotizing cumbersome manual processes. Also, deep learning technologies used in medical image analysis are rising exponentially, boosting the market growth. The deep learning–led computer vision technology is used to analyze scans to determine the state of cancerous tumors, avoiding the need for a biopsy.


Deep Learning-based Speech and Image Recognition are Trending 

Significant demand led by the rising automation in manufacturing sectors in emerging economies would offer vast opportunities to global firms in the future. Additional factors boosting the deep learning market size include the increasing use of deep learning-based speech and image recognition software and data mining processes. Besides, the increasing demand from industries such as the government & law enforcement, healthcare, security & surveillance, military & defense, IT & telecommunication, financial services, and research & development sectors positively impacts the deep learning market growth.


Lack of Technical Expertise to Restrain Market Growth

Despite the lucrative growth opportunities, factors such as applications largely limited to earthwork construction, lack of technical expertise, and high-cost training requirements restrict the market growth. Changing trends in manufacturing techniques are projected to act as major growth hindering factors for the market during the forecast period. Also, compatibility issues and high installation costs are expected to slow down the Deep Learning market share. 

Cumulative Growth Analysis

Market Size to Expand at a Strong Rate 

Considering the present market scenario, it is estimated that the deep learning market share is expected to increase further during the review period due to the increasing adoption of artificial intelligence (AI) and deep learning for surveillance, signal processing, and imaging classification. There is a moderate entry barrier due to the higher capital-intensive nature of the deep learning industry. However, the growing demand from end-users is expected to attract several new entrants with constantly upgrading technology.

Segment Overview 

Deep Learning Market is segmented into components, applications, end-user, and regions. The component segment is further sub-segmented into hardware, software, and service. The hardware segment is further bifurcated into processor, memory, network, and others. The software segment is divided into solution and platform. The services segment is sub-segmented into installation, training, and support & maintenance.

The application segment is further sub-segmented into image recognition, data mining, signal recognition, and others. The end-users segment is sub-segmented into security, manufacturing, retail, automotive, media & entertainment, BFSI, healthcare, agriculture, and others. 

By regions, the market is segmented into Americas (US, Canada, Mexico, Rest-of-North America), Asia Pacific (China, Japan, India, South Korea, and Rest-of-the-APAC), Europe (Germany, UK, France, Italy, and Rest-of-Europe), and Rest-of-the-World.

Regional Analysis

North America to Maintain its Leading Position

North America is the market leader and could continue to maintain its leading position throughout the assessment period. Factors such as the growing uptake of deep learning technology for voice & image recognition, data mining, signal recognition, and diagnostics purposes drive the deep learning market growth. The US market leads the regional market, followed by Canada and Mexico, mainly due to the well-established healthcare sector.  

Besides, the high growth in automation of instrumentation processes across the industries, advances in agricultural processes, and developed network infrastructure increase the deep learning market size. The Mexican deep learning market demonstrates high potential in the automotive, agriculture, and aerospace sectors.

Europe Holds Second Highest Share in Global Market 

Europe accounts for the second-biggest share in the global market. Increasing adoption of deep learning technology by governments for surveillance, fraud detection, and data mining and escalating demand from the automotive and electronics industries in the region foster the market growth considerably. Additionally, rising healthcare spending and strict regulations positively impact market growth.

Competitive Landscape

Players Focus on Product Development to Gain Impetus

The deep learning market appears extremely fragmented, considering the presence of established manufacturers. Eminent players seek opportunities to integrate across the extensive value chain while focusing on expanding production capacities, R&D investments, and M&A activities to gain additional impetus. They deliver reliable, leading-edge solutions and services, substantially investing in developing adept technologies and products. 

List of Key Companies 

  • Intel Corporation (USA)

  • Amazon Inc. (USA)

  • Samsung Electronics Co Ltd (South Korea)

  • Sensory Inc. (USA)

  • Micron Technology (USA)

  • Xilinx Inc. (USA)

  • Mellanox Technologies (USA)

  • Google LLC (USA)

  • Adapteva Inc. (USA)

  • NVIDIA Corporation (USA)

  • Qualcomm Technologies Inc. (USA)

  • Baidu Inc (China)

  • Advanced Micro Devices Inc. (USA)

  • IBM Corporation (USA)

  • Facebook (USA)

  • Microsoft Corporation (USA)

  • Tenstorrent (Canada) 

Amazon Web Services (AWS) is a leading global technology company energizing society and industry's transformation to achieve a more productive, sustainable future. Nearly after three years since it was first launched, AWS's SageMaker platform has gotten significantly upgraded features that make it easier for developers to automate and scale-up processes to build new automation and machine learning capabilities.

Recent Developments

  • January 07, 2021 – Syntiant, a deep learning chip technology company, unveiled a new deep learning processor for audio and sensor applications - the Syntiant NDP120 Neural Decision Processor (NDP). This latest generation of chips for audio and sensor processing is intended for always-on applications in battery-powered devices.

  • January 07, 2021 – Ohio State University researchers demonstrated how AI Deep Learning could impact label uses for FDA-approved drugs. Researchers showed how deep learning could emulate clinical trials to identify drug candidates for repurposing, a solution that can help improve drug safety and accelerate novel treatments by clinicians.

  • January 05, 2021 – Scientists at the University of California announced the development of a new deep-learning framework that predicts gene regulation at the single-cell level. The novel ability could further understanding and treatment of diseases such as cancer.

  • December 9, 2020 – Amazon Web Services (AWS), announced the expansion of its SageMaker capabilities with end-to-end features for machine learning. Products designed to simplify machine learning applications and development process include distributed training, making complex, deep learning models faster compared to current approaches by automatically splitting data across multiple GPUs to accelerate training times

Report Overview 

The report features unique and relevant factors estimated to significantly impact the deep learning industry during the review period. This detailed and considerable amount of information can help industry players understanding the market better. The MRFR report elaborates on the historical and current trends boosting the growth of the deep learning market. Besides, the analysis of COVID-19 impact on the deep learning market is also included in the report.

Segmentation Table

By Component

  • Hardware

  • Software

  • Services 

By Application

  • Image Recognition

  • Data Mining

  • Signal Recognition

By End-User 

  • Security

  • Manufacturing

  • BFSI

  • Healthcare

  • Agriculture

By Region 

  • North America

  • Europe

  • Asia Pacific

  • Rest of the World (RoW)

Frequently Asked Questions (FAQ) :

Google LLC (USA), Qualcomm Technologies Inc. (USA), Mellanox Technologies (USA), Xilinx Inc. (USA), Adapteva, Inc. (USA), and NVIDIA Corporation (USA) are the challengers in the market.

The end-user segments of manufacturing, retail, security, automotive, healthcare, and agriculture are characterizing the market.

A 30.87 % CAGR is proposed to transform the market in the upcoming years.

The regional segments of North America, Europe, and the APAC region are included in the study.

A 30.87% CAGR is estimated to steer the market towards profitable outcomes in the forecast period.

The mounting investments for progressing machine learning are estimated to create promising growth traction.

The North American region is expected to play a major role in the market.