Worldwide Artificial Intelligence Industry to 2026 - Featuring Intel, Xilinx & Samsung Among Others

DUBLIN, Oct. 16, 2020 /PRNewswire/ -- The "Artificial Intelligence (Chipsets) Market by Technology (Machine learning, Natural Language Processing, Context Aware Computing, Computer Vision), Hardware (Processor, Memory, Network), End-User Industry, and Region - Global Forecast to 2026" report has been added to ResearchAndMarkets.com's offering.

The AI (chipsets) market is expected to be valued at USD 7.3 billion in 2020 and is likely to reach USD 57.8 billion by 2026, at a CAGR of 40.1% during the forecast period.

Major drivers for the market are increasingly large and complex datasets driving the need for AI, the adoption of AI for improving consumer services & reducing operational costs, the growing number of AI applications, the improving computing power, and growing adoption of deep learning and neural networks.

The major restraint for the market is the lack of a skilled workforce. Critical challenges facing the AI (chipsets) market include low return on investment, creating models & mechanisms for AI, and the availability of limited structured training data. Underlying opportunities in the AI (chipsets) market include increasing focus on developing human-aware AI systems and bringing AI to edge devices.

The machine learning technology is expected to account for the largest size of the AI (chipsets) market during the forecast period.

Machine learning's ability to collect & handle big data & its applications in real-time speech translation, autonomous robots, and facial analysis are fuelling its growth. AI constitutes various technologies that play a vital role in developing its ecosystem. As AI enables machines to perform activities similar to those performed by human beings, enormous market opportunities have opened up.

The predictive maintenance and machinery inspection application in the manufacturing industry of the AI (chipsets) market is projected to hold the largest share during the forecast period.

The predictive maintenance and machinery inspection application held the largest share among the manufacturing applications of the AI (chipsets) market in 2019. Extensive use of computer vision cameras in machinery inspection, adoption of the Industrial Internet of Things (IIoT), and use of big data in the manufacturing industry are the factors driving the growth of the predictive maintenance and machinery inspection application. The increasing demand for reducing the operational costs and machine downtime is also supplementing the growth of predictive maintenance and machinery inspection application in industries.

The cybersecurity industry held the largest size of the AI (chipsets) market in 2019.

AI is significantly used in antivirus and anti-malware solutions owing to the rise in cybersecurity attacks across the world. Increasing use of mobile devices for a wide range of applications, such as social networking, e-mails, remote monitoring, phone banking, and data storage, opens doors for hackers to attack, thereby making networks more vulnerable to risks. The rapid adoption of cloud-based services, along with the user-friendly approach of antivirus/anti-malware solutions, is contributing to the growth of this end-user industry of the AI (chipsets) market.

Impact of COVID-19 on the AI (chipsets) market

The market is likely to witness a slight plunge in terms of year-on-year growth in 2020. This is largely attributed to the affected supply chains and limited adoption of AI in various end-user industries in 2020 due to the lockdowns and shifting priorities of different industries. The ongoing COVID-19 pandemic has caused disruptions in economies. It is likely to cause supply chain mayhem and eventually force companies and entire industries to rethink and adapt to the global supply chain model. Many manufacturing companies have halted their production, which has collaterally damaged the supply chain and the industry. This disruption has caused a delay in the adoption of AI-based software and hardware products. The industries have started to restructure their business model for 2020, and many SMEs and large manufacturing plants have halted/postponed any new technology upgrade in their factories to recover from the losses caused by the lockdown and economic slowdown. COVID-19 has impacted the educational industries rather positively, with ed-tech companies adopting AI technology to impart education during the lockdown. Ed-tech firms have deployed AI tools to enhance online learning and virtual classroom experience for students.

Several industries are worse hit by this pandemic, but some industries are profiting from this pandemic. However, the adoption of AI is expected to grow. Therefore, we can say the COVID-19 will drive the AI (chipsets) market for certain industries

Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary
3.1 COVID-19 Impact Analysis
3.1.1 Pre-COVID-19 Scenario
3.1.2 Post-COVID-19 Scenario

4 Premium Insights
4.1 Overview of the AI (Chipsets) Market
4.2 AI (Chipsets) Market, by Hardware
4.3 Machine Learning AI (Chipsets) Market, by Subtype
4.4 Asia-Pacific: AI (Chipsets) Market, by End-User Industry and Country
4.5 AI (Chipsets) Market, by Country

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increasingly Large and Complex Dataset Driving the Need for Ai
5.2.1.2 Adoption of AI for Improving Consumer Services and Reducing Operational Cost
5.2.1.3 Growing Number of AI Applications
5.2.1.4 Improving Computing Power
5.2.1.5 Growing Adoption of Deep Learning and Neural Networks
5.2.2 Restraints
5.2.2.1 Lack of Skilled AI Workforce
5.2.3 Opportunities
5.2.3.1 Increasing Focus on Developing Human-Aware AI Systems
5.2.3.2 Bringing AI to Edge Devices
5.2.4 Challenges
5.2.4.1 Low Return on Investment
5.2.4.2 Creating Models and Mechanisms for Ai
5.2.4.3 Limited Structured Data
5.3 Impact of COVID-19
5.4 Ecosystem
5.5 Pricing Analysis
5.6 Technology Analysis
5.7 List of Emerging Sme's and Start-Ups of AI (Chipsets) Market
5.8 Case Studies

6 Artificial Intelligence (Chipsets) Market, by Hardware
6.1 Introduction
6.2 Processor
6.2.1 High Parallel Processing Capabilities and Improved Computing Power Have Resulted in Adoption of Processors
6.3 Memory
6.3.1 High-Bandwidth Memory is Being Developed and Deployed for AI Applications, Independent of Its Computing Architecture
6.4 Network
6.4.1 NVIDIA (Us) and Intel (Us) are Key Providers of Network Interconnect Adapters for AI Applications

7 Artificial Intelligence (Chipsets) Market, by Technology
7.1 Introduction
7.2 Machine Learning
7.2.1 Deep Learning
7.2.1.1 Deep Learning Uses Artificial Neural Networks to Learn Multiple Levels of Data
7.2.2 Supervised Learning
7.2.2.1 Classification and Regression are Major Segments of Supervised Learning
7.2.3 Unsupervised Learning
7.2.3.1 Unsupervised Learning Includes Clustering Methods Consisting of Algorithms with Unlabeled Training Data
7.2.4 Reinforcement Learning
7.2.4.1 Reinforcement Learning Allows Systems and Software to Determine Ideal Behavior for Maximizing the Performance of Systems
7.2.5 Others
7.3 Natural Language Processing
7.3.1 Nlp is Developed for Real-Time Translation and Developing Systems That Can Interact Through Dialogues
7.4 Context Aware Computing
7.4.1 Development of More Sophisticated Hard and Soft Sensors Has Accelerated the Growth of Context Aware Computing
7.5 Computer Vision
7.5.1 Computer Vision Analyzes Information of Different Geometric Shapes, Volumes, and Pattern
7.6 Predictive Analysis
7.6.1 Predictive Analysis is Majorly Used in Agriculture Applications

8 Artificial Intelligence (Chipsets) Market, by Function
8.1 Introduction
8.2 Training
8.2.1 Building a Good Model is Directly Related to the Quality and Quantity of Data Used in the Process of a Learning Model
8.3 Inference
8.3.1 On-Premises Inference Platform is Adopted to Gain Faster Results Than That of Cloud

9 Artificial Intelligence (Chipsets) Market, by End-User Industry
9.1 Introduction
9.2 Healthcare
9.2.1 Growing Patient Data is Driving the Adoption AI in Healthcare
9.2.1.1 Patient Data & Risk Analysis
9.2.1.2 Lifestyle Management & Monitoring
9.2.1.3 Precision Medicine
9.2.1.4 Inpatient Care & Hospital Management
9.2.1.5 Medical Imaging & Diagnostics
9.2.1.6 Drug Discovery
9.2.1.7 Virtual Assistant
9.2.1.8 Wearables
9.2.1.9 Research
9.2.1.10 Healthcare Assistance Robots
9.2.1.11 Emergency Room & Surgery
9.2.1.12 Mental Health
9.2.1.13 Cybersecurity
9.3 Manufacturing
9.3.1 Industry 4.0 is the Driving Factor for AI Adoption in Manufacturing
9.3.1.1 Material Movement
9.3.1.2 Predictive Maintenance and Machinery Inspection
9.3.1.3 Production Planning
9.3.1.4 Field Services
9.3.1.5 Reclamation
9.3.1.6 Quality Control
9.4 Automotive
9.4.1 Automated Driving Using AI is the Trend in this Industry
9.4.1.1 Autonomous Driving
9.4.1.2 Human-Machine Interface
9.4.1.3 Semi-Autonomous Driving
9.5 Agriculture
9.5.1 Adoption of AI Technologies Such as Ml and Computer Vision is Driving the Market
9.5.1.1 Precision Farming
9.5.1.2 Livestock Monitoring
9.5.1.3 Drone Analytics
9.5.1.4 Agricultural Robots
9.5.1.5 Labor Management
9.5.1.6 Others
9.6 Retail
9.6.1 Enhanced Customer Experience due to AI is Driving Its Adoption in Retail
9.6.1.1 Product Recommendation and Planning
9.6.1.2 Customer Relationship Management
9.6.1.3 Visual Search
9.6.1.4 Virtual Assistant
9.6.1.5 Price Optimization
9.6.1.6 Payment Services Management
9.6.1.7 Supply Chain Management and Demand Planning
9.6.1.8 Others
9.7 Cybersecurity
9.7.1 Increased Number of Cybersecurity Threats is Leading to the Adoption of AI in this Industry
9.7.1.1 Identity and Access Management (Iam)
9.7.1.2 Risk and Compliance Management
9.7.1.3 Encryption
9.7.1.4 Data Loss Prevention
9.7.1.5 Unified Threat Management
9.7.1.6 Antivirus/Antimalware
9.7.1.7 Intrusion Detection/Prevention Systems
9.7.1.8 Others
9.8 Human Resources
9.8.1 AI Adoption in Hr is Reshaping How Companies Operate
9.8.1.1 Virtual Assistant
9.8.1.2 Sentiment Analysis
9.8.1.3 Scheduling Group Meetings and Interviews
9.8.1.4 Personalized Learning and Development
9.8.1.5 Applicant Tracking & Assessment
9.8.1.6 Employee Engagement
9.8.1.7 Resume Analysis
9.9 Marketing
9.9.1 AI Has Major Applications in Marketing
9.9.1.1 Social Media Advertising
9.9.1.2 Search Advertising
9.9.1.3 Dynamic Pricing
9.9.1.4 Virtual Assistant
9.9.1.5 Content Curation
9.9.1.6 Sales & Marketing Automation
9.9.1.7 Analytics Platform
9.9.1.8 Others
9.10 Law
9.10.1 AI is Being Used in Law to Increase Productivity and Margins
9.10.1.1 Ediscovery
9.10.1.2 Legal Research
9.10.1.3 Contract Analysis
9.10.1.4 Case Prediction
9.10.1.5 Compliance
9.10.1.6 Others
9.11 Fintech
9.11.1 AI is Used in Fintech Companies to Design Investment Strategies
9.11.1.1 Virtual Assistant
9.11.1.2 Business Analytics and Reporting
9.11.1.3 Customer Behavior Analytics
9.11.1.4 Others
9.12 Government
9.12.1 Government Bodies are Adopting AI to Tackle Cyberterrorism

10 Artificial Intelligence (Chipsets) Market, by Region
10.1 Introduction
10.2 North America
10.3 Europe
10.4 APAC
10.5 Rest of the World

11 Competitive Landscape
11.1 Overview
11.2 Market Ranking Analysis: AI (Chipsets) Market
11.3 Market Share Analysis
11.4 Competitive Leadership Mapping
11.4.1 Visionary Leaders
11.4.2 Dynamic Differentiators
11.4.3 Innovators
11.4.4 Emerging Companies
11.5 Competitive Situation and Trends
11.5.1 New Product Developments and Launches
11.5.2 Collaborations and Partnerships
11.5.3 Acquisitions

12 Company Profiles
12.1 Key Players
12.1.1 NVIDIA
12.1.2 Intel
12.1.3 Xilinx
12.1.4 Samsung
12.1.5 Micron
12.1.6 Qualcomm Technologies
12.1.7 IBM
12.1.8 Google
12.1.9 Microsoft
12.1.10 Amazon Web Services (AWS)
12.2 Other Companies
12.2.1 AMD
12.2.2 General Vision
12.2.3 Graphcore
12.2.4 Mediatek
12.2.5 Huawei Technologies
12.2.6 Fujitsu
12.2.7 Wave Computing
12.2.8 Mythic
12.2.9 Zero Asic
12.2.10 Koniku
12.2.11 Tenstorrent
12.2.12 Sambanova
12.2.13 Kalray
12.2.14 XMOS
12.2.15 Greenwaves Technologies

13 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/qfimnk

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