Global Deep Learning Market Ecosystem By Components Type; By Product, Parts & Devices, By Services & Solutions; By Application; By Region; By End Users (Logistics, Healthcare, Transportations, Automotive, Retail, BFSI Aerospace, Consumer Electronics, Oil & Gas, Others)

Deep learning is an integral subset of machine learning that has networks capable of learning from unstructured data. Several companies across industries such as retail, healthcare, aerospace & defense, and BFSI, among others, are joining hands with software development companies to use deep learning technology, for saving cost and time and for improving overall efficiency. Healthcare companies such as Bayer A.G., Eli Lilly & Company, Amgen Corporation, and AstraZeneca Plc are strengthening their internal research team and collaborating with software development companies to improve the drug discovery process. The impact of deep learning ecosystem across industries such as retail, healthcare, automotive, telecom, and BFSI are expected to intensify in the next 5 years. The deep learning market ecosystem is poised to grow at an excess of 30% CAGR during the forecast period from 2019-2023.

In terms of investments in the field of artificial intelligence & deep learning market ecosystem, the U.S. has overtaken China to grab the topmost spot as a venture capital investment hub. The U.S. attracted the most investment in 2018, accounting for more than 50% of total investments in AI and Deep Learning ecosystem across the globe. The investment figure in the country is expected to grow significantly in the coming years. The growth in investments in the U.S. is fueled by companies such as Cruise Automation, Zymergen, Dataminr with the total investment reaching approximately US$ 14 Bn in 2019. On the other hand, China attracted investment worth US$ 7.4 Bn in the same year. 

Ecosystem Snapshot: Deep Learning Market

Deep Learning Ecosystem

Despite complexities, major corporations are focusing on implementing deep learning technologies in their processes. Deep learning is used for a wide range of applications such as cybersecurity, predictive maintenance, autonomous vehicles, and threat monitoring, among others. Cyber-attacks have witnessed a steep increase over the past few years across industries. Supply chain attacks increased by approximately 78% in 2018 and data breaches have increased by up to 4 times since 2016. Such threats have led both the public and private sector to invest heavily in defense and cybersecurity. This has led to an exponential rise in demand for solutions specific to deep learning market ecosystem, which in turn, has created a positive impact on the entire ecosystem of artificial intelligence. Cybersecurity companies have witnessed sales growth by approximately 15% over the past 3 years, with annual spending amounting to more than US$ 120 Bn.

Autonomous vehicles are another area for the expansion of deep learning market from a technological point of view. Although a distant concept, developed countries such as the U.S., Germany, and France will witness the entry of autonomous vehicles in the next 5 to 6 years. To speed up the process, several automotive giants are investing heavily in research & development activities to bring out concepts of autonomous vehicles that could be made production-ready. For instance, the Peugeot E-Legend is an autonomous concept vehicle developed by Groupe PSA and is claimed to be 100% driverless. Further, the Renault-Nissan-Mitsubishi alliance is on the process of launching 40 vehicle models including autonomous drive vehicle technologies by 2022. For instance, in June 2019, Volvo Group and NVIDIA Corporation announced joining forces to develop driverless trucks, where Volvo Group would use NVIDIA's AI-enabled platforms for in-vehicle computing, training, and simulation purposes. Such alliances are expected to complement the growth of the deep learning ecosystem in the coming years.

Deep Learning Market Ecosystem: Segmentation

Components Services & Solutions Services & Solutions Applications End-users
Processors Smartphone & Tablet Solution Predictive Maintenance/Self Diagnostics Logistics
Memory Wearable Services Fraud Reduction Healthcare
Storage Workstation System   Cybersecurity Transportation
FPGA Medical Devices   Network Security Automotive
ASIC Pharma/Biopharma   Network Optimization Retail
Modules Smart Modules   Customer Analytics BFSI
  Imaging Systems   Virtual Assistance Telecom & Consumer Electronics
  Smart Trackers   Network Operations & Monitoring Management Oil & Gas
  Smart Meters   Security & Surveillance Others
  Others   Recommendation Engine  
      Predictive Merchandising  
      Inventory Management  

The fall in the value of cryptocurrencies acted as a boon for the GPU manufacturers, as prices of GPUs witnessed a sharp decline after the first quarter of 2018. GPU prices of NVIDIA Corporation and AMD Inc. witnessed a dramatic increase by up to 50% in the first quarter of 2018 due to a boom in cryptocurrencies. This put a lot of pressure on manufacturers and consumers alike, as both were struggling to contend with the high prices of GPUs. However, the value of cryptocurrencies witnessed a sharp decline from the second quarter of 2018, as nearly US$ 6 Bn was wiped out of the global market in a single day. This eased up the road for GPU manufacturers and they resumed their research & development activities to upgrade their hardware.

Industries such as BFSI, telecom, retail, and aerospace & defense are lucrative areas for the penetration of deep learning as these industries generate and store a vast amount of data daily, and a sophisticated cyberattack can have a disastrous effect on these industries. For instance, the WannaCry ransomware attack in 2017 was a major cyberattack that targeted computers running on Windows operating systems by encrypting data and demanding ransom payments in the form of cryptocurrencies. More than 200,000 companies were affected spanning across 150 countries. Russia, India, Taiwan, and Ukraine were highly affected by the attack. To prevent future attacks, major corporations have ramped up their R&D expenses to focus more on AI and deep learning technologies to improve cybersecurity.

Deep Learning Market Ecosystem Statistics Glimpse

Deep Learning Ecosystem Statistics

There are many trends that are having an impact on the Deep Learning market forecast. These, when evaluated from a company’s perspective, can drive growth. Our numerous consulting projects have generated sizeable synergies across all regions and all sizes of companies.

Deep Learning market Ecosystem: Key Players

Company Ecosystem Positioning Total Revenue Industry Region
IBM Corporation Solution & Service Provider       $ 79 Billion Automotive, Aerospace & Defense, BFSI, Public & Social Sector, Healthcare, Retail, etc. Global Inc. Solution & Service Provider       $72.4 Billion Retail Global
Google Inc. Solution & Service Provider       $136.22 Billion BFSI, Retail, etc. Global
Intel Corporation Hardware Manufacturers and Service Provider $37 Billion Automotive, Telecom, BFSI, Healthcare, Aerospace & Defense, etc. Global
NVIDIA Corporation Hardware Manufacturers and Service Provider $9.7 Billion Healthcare, Retail, Automotive, Public & Social Sector, Telecom, etc. Global

Very few markets have interconnectivity with other markets like deep learning. Our Interconnectivity module focuses on the key nodes of heterogeneous markets in detail. AI processors, AI-enabled imaging systems, AI in healthcare, AI in cybersecurity, 3D printing markets are some of our key researched markets.

Deep Learning Market Ecosystem Major Interconnectivities

Deep Learning Ecosystem Major Interconnectivities

Global Deep Learning Market Ecosystem Key Trends:

Trends  Components  Products  Technology  End-users  Impact on Market 
Deep learning allows for the development of sophisticated forecasting models that incorporate unstructured datasets in the retail sector  GPU     Retail 2.72%
Using deep learning to detect faulty parts in an aircraft, thereby making it easier for aircraft engineers        Aerospace & Defense 0.46%


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  1. Introduction
    1. Global AI Deep Learning Market Definition
    2. Scope of study 
    3. Annual SaaS
  2. Executive Summary
    1. Global Market Segmentation
    2. Global Market Overview
      1. Mega Growth Drivers
      2. Major Growth Blockers
    3. Global Market Statistics
      1. By Investment
        1. AI Technology Industry Player
        2. Investment Companies
      2. By Market Revenue / Shipments/ Price Points                        
    4. Mega Trends
    5. Competitive Landscape
      1. SWOT
      2. PEST
      3. Company Ranking
    6. Market Attractiveness
      1. By Segment Level
      2. By Geography (Region/Country)
    7. Interconnectivity
      1. Allied/Interconnected Markets
      2. Allied/Interconnected Technologies
      3. Allied/Interconnected Applications
      4. Allied/Interconnected End Users

 Ecosystem Positioning

  1. Global AI Deep Learning Market Ecosystem Snapshot
    1. Global AI Deep Learning Market Ecosystem Broad Heads
      1. Demand Side
    2. Supply Side
  2. Global AI Market by Deep Learning Technology Segmentation
      1. By Components
        1. Processors
        2. Memory
        3. Storage
        4. FPGA
        5. ASIC
        6. Modules
      2.  By Product, Parts & Devices
        1. Smartphones and Tablets
        2. Wearables
        3. Workstation Systems
        4. Medical Devices
        5. Pharmaceuticals/ Biopharma
        6. Hospital Management
        7. Smart Modules
        8. Imaging Systems
        9. Smart Trackers
        10. Smart Meters
        11. Others
      3. By Services & Solutions
        1.  Solutions
        2. Services
      4. By Application
        1. Predictive Maintenance/Self Diagnostics
        2. Fraud Reduction
        3. Cybersecurity
        4. Network Security
        5. Network Optimization
        6. Customer Analytics
        7. Virtual Assistance
        8. Network Operations & Monitoring Management
        9. Security & Surveillance
        10. Recommendation Engines
        11. Predictive Merchandising
        12. Inventory Management
        13. Others
      5. By End Users
        1. Logistics
        2. Healthcare
        3. transportations
        4. Automotive
        5. Retail
        6. BFSI
        7. Aerospace
        8. Consumer Electronics
        9. Oil & Gas
        10. Others
      6. Geographic Overview
        1. North America
          1. U.S.
          2. Canada
          3. Mexico
        2. Europe
          1. U.K.
          2. Germany
          3. Italy
          4. Spain
          5. France
          6. Rest of Europe
        3. APAC
          1. India
          2. Japan
          3. China
          4. South Korea
          5. Taiwan
          6. Rest of APAC
        4. RoW
          1. Middle East
          2. Africa
          3. South America
  3. Competitive Landscape Mapping by Ecosystem Positioning
    1. Company by each node
    2. Vendor Landscaping
    3. Ecosystem Level Analysis
    4. Global AI Deep Learning Ecosystem Broad Heads
  4. Competitive Landscape Mapping by Ecosystem Positioning
    1. A company by each node
    2. Vendor Landscaping

Trend Analysis

  1. Global Deep Learning Market Trends
    1. Trend Mapping
      1. Trend Description
      2. Trend Evaluation
        1. Impact
        2. Importance
        3. Remarks
      3. Trend Outlook (Short, Mid, Long Term)
      4. Trend Company Mapping
      5. Related Global AI Deep Learning Market Mapping
      6. Trend Region/Country Mapping

Global Deep Learning Market Regulatory Analysis

  1. Overview
    1. Regulatory Mapping
    2. Regulatory Impact
    3. Regulatory Interlinkage

Global Deep Learning Market Sizing, Volume and ASP Analysis & Forecast

  1. Global Deep Learning Market Sizing & Volume
    1. Cross-segmentation
    2. Global AI Deep Learning Market Sizing and Global AI Technologies Market Forecast
    3. Global AI Deep Learning Market Volume Analysis
    4. Average Selling Price Analysis
  1. Global AI Deep Learning Market Growth Analysis

Global Market by Deep Learning Technology Sizing, Volume and ASP Analysis & Forecast

  1. Global Deep Learning Market by Sizing & Volume
    1. Cross-segmentation
    2. Global AI Deep Learning Sizing and Global AI Market Size Forecast
    3. Global AI Deep Learning Volume Analysis
    4. Average Selling Price Analysis
    5. Global AI Deep Learning Growth Analysis

Competitive Intelligence

  1. Competitive Intelligence
    1. Top Industry Players vs Trend Tagging
        1. Importance
        2. Trend Nature (Positive/ Negative)
        3. Value
        4. Interconnectivity for each vendor
    2. Global AI Deep Learning Share Analysis
        1. By Each Node
    3. Strategies Adopted by Global AI Deep Learning Technology participants
        1. Global AI Deep Learning Strategies
          1. New product launch Strategies
          2. Geographic Expansion Strategies
          3. Product-line Expansion Strategies
          4. Operational / Efficiency building Strategies
          5. Other Strategies

Company Profiles

  1. Company Profiles (Total available company profiles for this market are around 125, this is sample list of companies. Please write us at for details)
    1. Microsoft
      1. Company Fundamentals
      2. Subsidiaries list
      3. Share Holding Pattern
      4. Key Employees and Board of Directors
      5. Financial Analysis
        1. Financial Summary
        2. Ratio Analysis
        3. Valuation Metrics
      6. Product & Services
      7. Client & Strategies
      8. Ecosystem Presence
      9. SWOT
      10. Trends Mapping
      11. Analyst Views
    2. Intel
    3. Amazon
    4. Google
    5. IBM
    6. Micron
    7. Nvidia
    8. Qualcomm
    9. Samsung
    10. Oracle  
    11. Xilinix
    12. Sensory Inc.
    13. Apple
    14. Salesforce
    15. Clarifai
    16. Neurala
    17. H2O.AI
    18. Voysis
    19. Aiera
    20. AMD
    21. Skymind
    22. Huawei
    23. Fujitsu
    24. Baidu
    25. Open AI
    26. Cray Inc


Global AI Market by Deep Learning Technology Developments

  1.  Market Developments
    1. Global AI Market by Deep Learning Technology Events & Rationale
    2. R&D, Technology and Innovation
    3. Business & Corporate advancements
    4. M&A, JVs/Partnerships
    5.  Political, Macro-economic, Regulatory
    6.  Awards & Recognition
    7. Others


  1. Ask for Customization
    1. Sensitivity Analysis
    2. TAM SAM SOM Analysis
    3. Other Customization
  2. Appendix
    1. Sources
    2. Assumptions
    3. Contact

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