The AI Infrastructure Market is expected to grow from USD 16.5 billion in 2020 to USD 63.7 billion by 2026 at a CAGR of 25.2% from 2020 to 2026.
AI Infrastructure comprises of use of deep learning machine technology which enables a machine to develop a hierarchical structure. For instance, the first film of an image can be scanned for basic edges. It is then followed by a layer which collects the edge forming shapes and lastly a layer which can identify the machine parts. After scanning number of such layers to recognize the required information, the neural network of the machine can then turn the features into an algorithm, which then is used to identify the image.
Rising deployment of cloud machine learning tools in companies and surging popularity of AI hardware in high-performing computing data centers will fuel growth of AI infrastructure market over forecasted time span. In addition to this, extensive usage of artificial intelligence in BFSI, healthcare, automotive and tourism sectors will drive expansion of AI infrastructure market over forecast period. Decrease in hardware costs and significant focus of firms on utilizing parallel computing in AI data centers will favor growth of AI infrastructure market size in upcoming years. Surging proportion of cross-industry alliances and collaborations will further fuel expansion of AI infrastructure industry. Increase in data traffic and requirement of high computing power will propel market trends. The rising use of robotics, industrial IoT and big data across fields is boosting the growth of the global AI infrastructure market. In addition, the several governments of developing countries such as India are investing in building efficient and effective AI ecosystem which will further project the growth of the market. Apart from this, the dearth of AI hardware experts and skilled workforce will likely to impede the market growth.
Field Programmable Gate Array (FPGA) is an integrated circuit which a customer or designer can configure after it is being created (field programmable). FPGAs are programmed using hardware description languages including VHSIC hardware description language (VHDL) or Verilog. FPGAs provide benefits such as short time-to-market, rapid prototyping, the ability to be reprogrammed in the field for debugging, and an improved product life cycle which increases the demand for FPGA-based accelerators further creates opportunities for the market.
The global AI Infrastructure Market is segregated on the basis of Component as Hardware and Software. Based on Deployment Model the global AI Infrastructure Market is segmented in On-Premise, Cloud and Hybrid. Based on End User the global AI Infrastructure Market is segmented in Government Organizations, Enterprises and Cloud Service Providers (CSPs).
The global AI Infrastructure Market report provides geographic analysis covering regions, such as Europe, North America, Asia Pacific, and Rest of The World. The AI Infrastructure Market for each region is further segmented for major countries including the U.S., Canada, Germany, the U.K., France, Italy, China, India, Japan, Brazil, South Africa, and others.
Competitive Analysis
Intel Corporation, NVIDIA Corporation, IBM, Samsung Electronics, Google and others are among the major players in the global AI Infrastructure Market. The companies studied in terms of product strategy and various n several growth and expansion strategies to gain a competitive edge in the market. The major players not only follow value chain integration with business operations in multiple stages of the value chain.
The global AI Infrastructure Market has been segmented as below:
AI Infrastructure Market, By Component
AI Infrastructure Market, By Deployment Model
AI Infrastructure Market, By End User
AI Infrastructure Market, By Region
AI Infrastructure Market, By Company
The report covers the below scope:
The years considered for the study are as follows:
Report Scope:
The global AI Infrastructure Market report scope includes detailed study covering underlying factors influencing the industry trends. The report covers analysis on regional and country level market dynamics. The scope also covers competitive overview providing company market shares along with company profiles for major revenue contributing companies. The report scope includes detailed competitive outlook covering market shares and profiles key participants in the global AI Infrastructure Market share. Major industry players with significant revenue share include Intel Corporation, NVIDIA Corporation, IBM, Samsung Electronics, Google and others.
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1. Introduction
1.1. Key Points
1.2. Report Description
1.3. Markets Covered
1.4. Stakeholders
2. Research Methodology
2.1. Research Scope
2.2. Research Methodology
2.2.1. Market Research Process
2.2.2. Research Methodology
2.2.2.1. Secondary Research
2.2.2.2. Primary Research
2.2.2.3. Models for Estimation
2.3. Market Size Estimation
2.3.1. Bottom-Up Approach
2.3.2. Top-Down Approach
3. Executive Summary
4. Market Overview
4.1. Introduction
4.2. Drivers
4.3. Restraints
4.4. Opportunities
4.5. Challenges
5. AI Infrastructure Market, By Component
5.1. Key Points
5.2. Hardware
5.3. Software
6. AI Infrastructure Market, By Deployment Model
6.1. Key Points
6.2. On-Premise
6.3. Cloud
6.4. Hybrid
7. AI Infrastructure Market, By End User
7.1. Key Points
7.2. Government Organizations
7.3. Enterprises
7.4. Cloud Service Providers (CSPs)
8. Competitive Landscape
8.1. Introduction
8.2. Start-up companies- AI Infrastructure Market
8.3. Recent Developments
8.3.1. Mergers & Acquisitions
8.3.2. New Product Developments
8.3.3. Portfolio/Production Capacity Expansions
8.3.4. Joint Ventures, Collaborations, Partnerships & Agreements
8.3.5. Others
9. Company Profile
9.1. Intel Corporation
9.2. NVIDIA Corporation
9.3. IBM
9.4. Samsung Electronics
9.5. Google
9.6. Microsoft
9.7. Micron Technology
9.8. Amazon Web Services
9.9. CISCO
9.10. Oracle
9.11. ARM
9.12. Xilinx
9.13. Advanced Micro Devices (AMD)
9.14. Dell
9.15. HPE
9.16. Habana Labs
9.17. Synopsys Inc.
9.18. Facebook
9.19. Xilinx
9.20. CiscoNutanix
AI Infrastructure Market, By Component
AI Infrastructure Market, By Deployment Model
AI Infrastructure Market, By End User
AI Infrastructure Market, By Company