Artificial Intelligence Chip Market - Trends Forecast Till 2028
Artificial Intelligence Chip Market, By Component (Hardware, Software and Services), Technology (Machine Learning, Natural Language Processing, Context-Aware Computing, Computer Vision), Application (Smartphone, Smart Wearable, Robotics, Automobile, Medical Imaging, Security Systems), End-Users (Healthcare, Automotive, Agriculture, Manufacturing, Retail, Security, Human Resource, Banking and Financial Services, Marketing, Law), Geography (North America, Europe, Asia-Pacific, Middle East and Africa and South America)
Published Date: May, 2020
Base Year Estimate: 2019
Report ID: D-IT-AICM-12
Number of Pages: 274
Domain: IT & Telecom
Artificial Intelligence Chip Market – Trends Forecast Till 2028
The global artificial intelligence chip market is anticipated to reach USD 164.9 billion by 2020 growing at a CAGR of 36.2% during the forecasting period, 2020-2028. Artificial intelligence chip is a chip that has featured artificial intelligence technology used for machine learning. It helps in automating the processes, solving mathematical and computational problems. Factors such as the rise in demand of smart cities, emerging quantum computing market, and lack of skilled workforce are some of the major drivers for the global artificial intelligence chip market
The global artificial intelligence chip market is segmented into component, technology, application, end-user, and geography.
The component segment is sub-segmented into Hardware, Software, and Services. The hardware segment has been segmented into Processor, Accelerator, Memory, Network, Storage and Others. The processor has been further segmented into image processor, vision processor and video processor. Accelerator has been further segmented into Graphics Processing Units (GPU), Central Processing Units (CPU), Application Specific Integrated Chips (ASIC), Field Programmable Gate Arrays (FPGA), and System-On-Chip (SOC).
The technology segment is sub segmented into Machine Learning, Natural Language Processing, Context-Aware Computing, and Computer Vision. The machine Learning segment has been further segmented into supervised learning, deep learning, reinforcement learning, unsupervised learning, and others.
The application segment has been segmented into Smartphones, Smart Wearable, Robotics, Automobile, Medical Imaging and Security Systems.
The end-User segment has been segmented into sub-segmented into Healthcare, Automotive, Agriculture, Manufacturing, Retail, Security, Human Resource, Banking and Financial Services, Marketing, Law. Healthcare is sub segmented into Patient Data & Risk Analysis, Lifestyle Management & Monitoring, Precise Medicine, Medical Imaging & Diagnostics, Drug Discovery, Virtual Assistant, Wearables, and Research. The automotive segment is further sub segmented into Autonomous Driving, Human–Machine Interface, and Semi-Autonomous Driving. Agriculture has been segmented into Precision Farming, Livestock Monitoring, Drone Analytics, Agricultural Robots, and Others. Manufacturing segmented into Predictive Maintenance and Machinery Inspection, Material Movement, Field Services, Production Planning, Reclamation, Quality Control, and Others. Retail has been further sub segmented into Customer Relationship Management, Product Recommendation and Planning, Visual Search, Virtual Assistant, Price Optimization, Payment Services Management, Supply Chain Management, and Demand Planning, and Others. Security has been further sub-segmented into Risk And Compliance Management, Identity And Access Management (IAM), Data Loss Prevention, Antivirus/Antimalware, Encryption, Intrusion Detection/Prevention Systems, Unified Threat Management, Others. Human Resource has been further sub-segmented into Sentiment Analysis, Virtual Assistant, Personalized Learning and Development, Employee Engagement, Applicant Tracking & Assessment, Resume Analysis, and Others. The banking and Financial Services segment has been further sub-segmented into Business Analytics and Reporting, Virtual Assistant, Customer Behaviour Analytics and Others. Marketing has been further sub-segmented into Dynamic Pricing, Social Media Advertising, Search Advertising, Sales & Marketing Automation, Analytics Platform, Content Curation, Virtual Assistant, and Others. Law has been further sub-segmented into Legal Research, EDiscovery, Case Prediction, Compliance, Contract Analysis, and Others
Geographically, the global artificial intelligence chip market is sub-segmented into North America, Europe, Asia-Pacific, Middle East and Africa and South America and insights are provided for each region and major countries within the regions.
North America and Europe regions are the largest contributors to the artificial intelligence chip market in the forecast period 2020-2028 and the Asia-Pacific region is expected to grow with the highest CAGR during the forecast period 2020-2028.
Key players in the global artificial intelligence chip market are Intel, Nvidia, Samsung Electronics, Xilinx, Micron Technology, IBM, Microsoft, Google, Amazon Web Services (AWS), Facebook, Baidu, Oracle, Salesforce, SAS, SAP, General Electric, Cisco, Rockwell, Siemens and among others.
The companies have come up with various promotional activities in from of launch, investment, acquisition, and other, for instance:
- In 2019, Intel has collaborated with the Facebook for the development of an AI chip that would help in inference, in which AI algorithm performs certain functions like tagging friends in the photos.
- In 2019, Apple has announced the launch of the new AI chip A12 Bionic which is a 7nm smartphone chip consist of 6.9 billion transistors and a neural engine along with a graphics processing unit (GPU). It has properties like performing almost 5 trillion operations per second.
Hence, tremendous progress has been made over the last decade and yet a lot more to come in recent years.
In addition to the market data for the artificial intelligence market. Delvens offers client-centric reports and is customized according to the company’s specific demand and requirements.
This research method involved the usage of extensive secondary sources (such as directories and databases)—Hoovers, Avention, annual reports, investor presentation, conferences like Jefferies conference)—to identify and collect information useful for this study of the artificial intelligence market. The purpose of secondary research is to identify and collection of extensive, technical, market-oriented, and commercial studies of the global artificial intelligence market. Through secondary research, the market is classified and segmented as per industry trends, developments, regional markets, products, and technological developments.
The primary sources mainly included several industry experts from the core and related industries and suppliers, manufacturers, distributors, alliances, and organizations related to all segments of this industry’s supply chain. In-depth interviews were conducted with various primary respondents—including key industry participants, subject matter experts (SMEs), C-level executives of key market players, and industry consultants, among other experts—to obtain and verify critical qualitative and quantitative information as well as to assess future prospects. The following figure depicts the market research methodology used in drafting this report on the artificial intelligence market.
Primary Respondent Breakdown is given below:
Top-down and bottom approaches were used to derive the market estimate and validate the total revenue of the artificial intelligence market. This approach has also been used to derive the market for segmentation and sub-segmentation.
Impact analysis has been conducted for deriving the market size. After collecting the in-depth quantitative and qualitative data, we contact primary respondents in order to gain a 98.8% of confidence level on our data.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Industry/Strategic Consultants