AI Infrastructure Market by Offering (Hardware, Software), Technology (Machine Learning, Deep Learning), Function (Training, Inference), Deployment Type (On-Premises, Cloud), End User, and Region - Global Forecast to 2026
[238 Pages Report] The AI infrastructure market is expected to grow from USD 23.7 billion in 2021 to USD 79.3 billion by 2026, at a CAGR of 27.3%. Increased data traffic and need for high computing power, increasing adoption of cloud machine learning platform, increasingly large and complex dataset, rising focus on parallel computing in AI data centers, and growing number of cross-industry partnerships and collaborations - are the key factors driving the AI infrastructure market.
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COVID-19 Impact on the Global AI Infrastructure Market
The COVID-19 pandemic is an accelerator for AI technology, helping people around the world get more and more comfortable with leveraging these tools for many applications, including healthcare. The adoption of remote patient monitoring, decoding genomic sequence for drug development, healthcare chatbots, and enhancement of CT scans using AI technology in diagnosis is expected to gain momentum during and after the COVID-19 pandemic.
Post-COVID-19, the manufacturing sector is expected to adopt smart manufacturing processes using AI, IoT, and blockchain technologies. Companies can reduce costs, increase process efficiency, and reduce human contact significantly by adopting these technologies. Currently, AI is being used for predictive maintenance and will further be implemented to forecast demand and returns in the supply chain.
Several industries are adversely affected by this pandemic, but some industries are benefiting from this pandemic as well. However, the adoption of AI is expected to grow in the coming years.
Market Dynamics of AI Infrastructure
Driver: Increased data traffic and need for high computing power
GPU/CPU manufacturers, such as NVIDIA, AMD, Intel, Qualcomm, Huawei, and Samsung, have significantly invested in the development of chips that are compatible with AI solutions. Apart from CPUs and GPUs, application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs) are also being developed for AI applications. For example, Google built a new ASIC called tensor processing unit (TPU).
A compute-intensive chip is one of the critical parameters for processing AI algorithms; the faster the chip, the quicker it can process data required to create an AI system. Currently, AI chips are mostly deployed in data centers/high-end servers as end computers are currently incapable of handling such huge workloads and do not have enough power and time frame. NVIDIA has a range of GPUs that offer GPU memory bandwidth according to the application. For example, GeForce GTX Titan X offers a memory bandwidth of 336.5 GB/s and is mostly deployed in desktops, while Tesla V100 16 GB offers a memory bandwidth of 900 GB/s and is used in AI applications.
Effective storage, managing, and interpreting of data have become essential. According to the latest records of Cisco Systems, Inc., the global IP traffic will reach 1.2 ZB per year or 96 EB per month in 2021; the global IP traffic will reach 3.3 ZB per year. This signifies that global IP traffic is flourishing and is likely to generate more data in the near term. Hence, it becomes essential to have higher computing power devices.
Restraint: Lack of AI hardware experts and skilled workforce
AI is a complex system, and companies require experts and a skilled workforce for developing, managing, and implementing AI systems. For example, people dealing with AI systems should be aware of technologies such as cognitive computing, machine learning (ML), machine intelligence, deep learning, and image recognition. In addition, integrating AI technology into existing systems is a challenging task that requires well-funded in-house R&D and patent filling. Even minor errors can translate into system failure or malfunctioning of a solution, and this can drastically affect the outcome and desired result.
Professional services of data scientists and developers are needed to customize existing ML-enabled AI processors. A workforce possessing in-depth knowledge of this technology is limited as AI as a technology is still in its early stage of the life cycle. The impact of this restraining factor is likely to remain high during the initial years of the forecast period.
Companies across industries embrace emerging technologies to improve operational efficiency and performance, reduce waste, conserve natural resources, reach new markets and audiences with speed and convenience, and support product and process innovation. Advancements in technology will significantly impact job availability and quality in the global economy—eliminating jobs, creating new jobs, and demanding new skills from workforces worldwide. Factories embracing machine vision technology would require more complex skill sets, and it could be difficult for lower-skilled, less-educated workers to access opportunities.
Opportunity: Surging demand for FPGA-based accelerators
Field Programmable Gate Array (FPGA) is an integrated circuit that a customer or designer can configure after it is being manufactured (field programmable). FPGAs are programmed using hardware description languages such as VHSIC hardware description language (VHDL) or Verilog. FPGAs offer advantages such as rapid prototyping, short time-to-market, the ability to be reprogramed in the field for debugging, and a long product life cycle. They contain individual programmable logic blocks known as configurable logic blocks (CLBs). These logic blocks are interconnected in such a manner that a user can configure the computing system multiple times. FPGAs contain large resources of logic gates and RAM to perform complex digital computation. FPGAs are used as co-processors to offload work done in microcontrollers, digital signal processors, or any other host processor. FPGAs provide flexible interfacing and are optimized to complement host processors.
Challenge: Concerns regarding data privacy in AI platforms
AI has several applications in the healthcare industry. However, the adoption of AI in the industry is restricted to an extent owing to data privacy concerns. Patients’ health data is protected under federal laws in many countries, and any breach or failure to maintain its integrity can result in legal and financial penalties. As AI used for patient care requires access to multiple health datasets, it is essential for AI-based tools to adhere to all data security protocols mandated by governments and regulatory authorities. This is a challenging task as most AI platforms are consolidated and require extensive computing power owing to which patient data, or parts of it, can be required to reside in a vendor’s data center. This is a major challenge in the market. The figure provided below shows the percentage of healthcare breaches reported by the US Department of Health and Human Services, which has affected more than 500 individuals.
Cloud service providers held the largest share of end users in the AI infrastructure market in 2020
The cloud mainly addresses three areas of operation: software-as-a-service (SaaS), infrastructure-as-a-service (IaaS), and platform-as-a-service (PaaS). Some of the major cloud service providers are AWS, Microsoft, IBM, Google, and Alibaba. These are the companies that provide cloud services to most of the companies worldwide. These companies are expected to lead the overall end user market for AI infrastructure.
The number of data center providers and cloud companies is likely to increase owing to the high efficiency and economies of scale offered by cloud computing. Cloud service providers offer services to several customers from a common shared infrastructure (i.e., equipment for operations, networking, data storage, and hardware) and help companies save their IT infrastructure costs. For example, Amazon Web Services (AWS) provides its IaaS for training and building a statistical model for inferencing purposes.
Hybrid deployment held the largest share of AI infrastructure market in 2020
On the basis of deployment type, market has been segmented as on-premises, cloud, and hybrid. A hybrid deployment mode is mixed computing, storage, and services consisting of on-premises infrastructure, private cloud services, or a public cloud, which can be customized according to the application. Cloud services drive cost savings and support the digital business transformation. The advantage of a hybrid cloud is its increased agility; therefore, it is widely accepted by enterprises to gain a competitive advantage. The automotive, healthcare and industrial organizations started adopting a hybrid infrastructure that combines different technologies and methodologies such as virtualization, private clouds, and other internal IT resources.
Inference function to account for the largest share in the AI infrastructure market in 2021
On the basis of function, the market has been segmented into inference and training. The inference is computationally less intense than training. Unlike training, it does not include a backward pass to compute the error and update weights. It is usually a production phase wherein the model is deployed to predict the real-world data. An inference platform should enable easy integration of training into deployment systems, offer latency for demanding workloads, have scalability and a standard client interface for successful adoption.
North America is leading the market for AI infrastructure in 2020
North America accounts for the largest share of the global AI infrastructure market, and a similar trend is likely to continue in the near future. The US and Canada are expected to adopt AI-based servers at a high rate. These countries are technologically developed economies in North America owing to their strong focus on investing in R&D activities for the development of new technologies. The US is one of the leading countries in the world to adopt AI technology. In addition, the presence of prominent AI technology providers in the country, such as IBM, Google, Microsoft, NVIDIA, Intel, Facebook, MetaMind, and Amazon, is boosting the growth of the AI infrastructure market in this region.
Key Market Players
Major players in the AI infrastructure market include Intel (US), NVIDIA (US), AMD (US), Samsung (South Korea), Xilinx (US), and so on.
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|
Report Metric |
Details |
|
Market size available for years |
2017–2026 |
|
Base year considered |
2020 |
|
Forecast period |
2021–2026 |
|
Forecast units |
Value (USD Billion) |
|
Segments covered |
Offering, Technology, Function, Deployment Type, End User, and Region |
|
Geographies covered |
North America, Europe, APAC, and RoW |
|
Companies covered |
Intel Corporation (US), NVIDIA Corporation (US), IBM (US), Xilinx (US), Advanced Micro Devices (AMD) (US), Samsung Electronics (South Korea), Micron Technology (US), Google (US), Microsoft (US), Amazon Web Services (US), Cisco (US), ARM (UK), Dell (US), HPE (US), SK Hynix (South Korea), Wave Computing (US), Graphcore (UK), and Synopsys Inc. (US) |
In this research report, the AI infrastructure market has been segmented on the basis of offering, technology, function, deployment type, end user, and geography.
AI infrastructure Market, by Offering
- Hardware
- Processor
- CPU
- GPU
- ASIC
- FPGA
- Memory
- Storage
- Networking
- Processor
- Server Software
AI infrastructure Market, by Technology
- Machine Learning
- Deep Learning
AI infrastructure display Market, by Function
- Training
- Inference
AI infrastructure Market, by Deployment Type
- On-Premises
- Cloud
- Hybrid
AI infrastructure Market, by End User
- Enterprises
- Government Organizations
- Cloud Service Providers
Geographic Analysis
- North America
- Europe
- APAC
- RoW
Recent Developments
- In April 2021, Intel (US) announced to launch a 3rd Gen Intel Xeon Scalable processor that will deliver a balanced architecture with built-in artificial intelligence, crypto acceleration, and advanced security capabilities.
- In April 2021, AMD (US) announced that it is in the process of acquiring Xilinx (US). This will bring together two industry leaders with complementary product portfolios and help capitalize on opportunities in the industry. The process of acquisition is expected to be completed by the end of 2021.
- In November 2020, AMD (US) and IBM (US) have announced an Advance Joint development Agreement to enhance and extend the security AI offering for both companies.
Frequently Asked Questions (FAQ):
What is the current size of the global AI infrastructure market?
The AI infrastructure market is expected to grow from USD 23.7 billion in 2021 to USD 79.3 billion by 2026, at a CAGR of 27.3%.
Who are the winners in the global AI infrastructure market?
Some of the key companies operating in the AI infrastructure market are Intel Corporation (US), NVIDIA Corporation (US), IBM (US), Xilinx (US), Advanced Micro Devices (AMD) (US), Samsung Electronics (South Korea), Micron Technology (US), Google (US), Microsoft (US), Amazon Web Services (US), and so on. These players have adopted various growth strategies such as product launches/developments, partnerships/contracts/ collaborations/acquisitions to expand their global presence and increase their share in the global AI infrastructure market.
What are the major drivers for the AI infrastructure market?
Increased data traffic and need for high computing power, increasing adoption of cloud machine learning platform, increasingly large and complex dataset, rising focus on parallel computing in AI data centers, and growing number of cross-industry partnerships and collaborations —are the key factors driving the AI infrastructure market.
What are the growing end user segments in the AI infrastructure market?
Cloud service providers are estimated to account for the largest share of the AI infrastructure market, by end user, in 2021. Cloud service providers offer services to several customers from a common shared infrastructure (i.e., equipment for operations, networking, data storage, and hardware) and help companies save their IT infrastructure costs.
What are the impact of COVID-19 on the global AI infrastructure market?
The COVID-19 pandemic is an accelerator for AI technology, helping people around the world get more and more comfortable with leveraging these tools for many applications, including healthcare. The adoption of remote patient monitoring, decoding genomic sequence for drug development, healthcare chatbots, and enhancement of CT scans using AI technology in diagnosis is expected to gain momentum during and after the COVID-19 pandemic. .
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TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 30)
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION AND SCOPE
1.2.1 INCLUSIONS AND EXCLUSIONS
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED
FIGURE 1 AI INFRASTRUCTURE MARKET: SEGMENTATION
1.3.2 GEOGRAPHIC SCOPE
1.3.3 YEARS CONSIDERED
1.4 CURRENCY
1.5 PACKAGE SIZE
1.6 STAKEHOLDERS
1.7 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY (Page No. - 36)
2.1 RESEARCH DATA
FIGURE 2 AI INFRASTRUCTURE MARKET: PROCESS FLOW OF MARKET SIZE ESTIMATION
FIGURE 3 AI INFRASTRUCTURE MARKET: RESEARCH DESIGN
2.1.1 SECONDARY AND PRIMARY RESEARCH
2.1.2 SECONDARY DATA
2.1.2.1 Major secondary sources
2.1.2.2 Secondary Sources
2.1.3 PRIMARY DATA
2.1.3.1 Key participants in primary processes across the value chain of the AI infrastructure market
2.1.3.2 Breakdown of primaries
2.1.3.3 Key industry insights
2.2 GROWTH RATE ASSUMPTIONS
2.2.1 SUPPLY-SIDE
2.2.2 DEMAND-SIDE
2.3 MARKET SIZE ESTIMATION
2.3.1 BOTTOM-UP APPROACH
2.3.1.1 Approach for capturing market share by bottom-up analysis (demand-side)
FIGURE 4 BOTTOM-UP APPROACH
FIGURE 5 MARKET SIZE CALCULATION BY BOTTOM-UP APPROACH
2.3.2 TOP-DOWN APPROACH
2.3.2.1 Approach for capturing market share by top-down analysis (supply side)
FIGURE 6 TOP-DOWN APPROACH
FIGURE 7 MARKET SIZE CALCULATION BY TOP-DOWN APPROACH
2.4 MARKET BREAKDOWN AND DATA TRIANGULATION
FIGURE 8 DATA TRIANGULATION
2.5 ASSUMPTIONS
2.6 LIMITATIONS
2.7 RISK ASSESSMENT
3 EXECUTIVE SUMMARY (Page No. - 49)
FIGURE 9 AI INFRASTRUCTURE MARKET, 2017–2026 (USD BILLION)
FIGURE 10 HARDWARE ESTIMATED TO HOLD LARGER SHARE OF AI INFRASTRUCTURE MARKET IN 2021
FIGURE 11 AI INFRASTRUCTURE MARKET, BY END USER, 2021 VS. 2026 (USD BILLION)
FIGURE 12 AI INFRASTRUCTURE MARKET, BY REGION, 2021–2026
3.1 IMPACT OF COVID-19 ON AI INFRASTRUCTURE MARKET
FIGURE 13 IMPACT OF COVID-19 ON AI INFRASTRUCTURE MARKET
3.1.1 REALISTIC SCENARIO (POST-COVID-19)
3.1.2 OPTIMISTIC SCENARIO (POST-COVID-19)
3.1.3 PESSIMISTIC SCENARIO (POST-COVID-19)
4 PREMIUM INSIGHTS (Page No. - 54)
4.1 ATTRACTIVE OPPORTUNITIES IN AI INFRASTRUCTURE MARKET
FIGURE 14 INCREASING ADOPTION OF CLOUD MACHINE LEARNING AND DEMAND FOR AI HARDWARE IN HIGH-PERFORMANCE COMPUTING DATA CENTERS EXPECTED TO DRIVE MARKET
4.2 AI INFRASTRUCTURE HARDWARE MARKET, BY TYPE
FIGURE 15 MEMORY EXPECTED TO GROW AT THE HIGHEST CAGR FROM 2021 TO 2026
4.3 AI INFRASTRUCTURE MARKET, BY FUNCTION
FIGURE 16 INFERENCE FUNCTION EXPECTED TO LEAD THE MARKET DURING FORECAST PERIOD
4.4 AI INFRASTRUCTURE MARKET, BY END USER AND REGION
FIGURE 17 CLOUD SERVICE PROVIDERS AND CHINA EXPECTED TO ACCOUNT FOR THE LARGEST SHARE OF THE MARKET DURING THE FORECAST PERIOD
4.5 AI INFRASTRUCTURE MARKET, BY TECHNOLOGY
FIGURE 18 DEEP LEARNING IS PROJECTED TO LEAD THE MARKET FROM 2021 TO 2026
4.6 AI INFRASTRUCTURE MARKET, BY COUNTRY
FIGURE 19 AI INFRASTRUCTURE MARKET IN CHINA IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
5 MARKET OVERVIEW (Page No. - 57)
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 20 AI INFRASTRUCTURE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
5.2.1 DRIVERS
5.2.1.1 Increased data traffic and need for high computing power
FIGURE 21 IP TRAFFIC GROWTH PROJECTIONS UNTIL 2021
5.2.1.2 Increasing adoption of cloud machine learning platform
5.2.1.3 Increasingly large and complex dataset
TABLE 1 AVERAGE NUMBER OF CONNECTED DEVICES PER CAPITA (2018–2023)
5.2.1.4 Rising focus on parallel computing in AI data centers
5.2.1.5 Growing number of cross-industry partnerships and collaborations
TABLE 2 RECENT DEVELOPMENTS PERTAINING TO INDUSTRY PARTNERSHIPS
5.2.2 RESTRAINTS
5.2.2.1 Lack of AI hardware experts and skilled workforce
FIGURE 22 UNDERQUALIFIED WORKERS IN VARIOUS COUNTRIES, 2019
5.2.3 OPPORTUNITIES
5.2.3.1 Surging demand for FPGA-based accelerators
TABLE 3 RECENT DEVELOPMENTS IN FPGA
5.2.3.2 Rising need for co-processors due to slowdown of Moore’s Law
5.2.3.3 Growing potential of AI-based tools for elderly care
5.2.4 CHALLENGES
5.2.4.1 Concerns regarding data privacy in AI platforms
FIGURE 23 PERCENTAGE AND TYPES OF HEALTHCARE BREACHES REPORTED BY THE US DEPARTMENT OF HEALTH AND HUMAN SERVICES
5.2.4.2 Unreliability of AI algorithms
5.2.4.3 Availability of limited structured data to train and develop efficient AI systems
5.3 AI INFRASTRUCTURE MARKET: COVID-19 IMPACT
5.4 TRENDS/DISRUPTIONS IMPACTING CUSTOMER’S BUSINESS
FIGURE 24 REVENUE SHIFT FOR AI INFRASTRUCTURE MARKET
5.5 PRICING ANALYSIS
FIGURE 25 ASP OF PROCESSOR TYPES IN AI INFRASTRUCTURE MARKET, 2017-2026
TABLE 4 ASP RANGE OF PROCESSOR TYPES IN AI INFRASTRUCTURE MARKET, 2017-2026
TABLE 5 ASP RANGE OF SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET
5.6 VALUE CHAIN ANALYSIS
FIGURE 26 VALUE CHAIN FOR AI INFRASTRUCTURE MARKET
5.7 ECOSYSTEM OF THE AI MARKET
FIGURE 27 ECOSYSTEM
TABLE 6 ROLE OF COMPANIES IN ECOSYSTEM/VALUE CHAIN
5.8 TECHNOLOGY ANALYSIS
TABLE 7 COMPARISON OF AI CHIP TYPE
5.8.1 CLOUD GPU
5.9 PATENT ANALYSIS
TABLE 8 PATENTS FILED, 2018-2021
FIGURE 28 LIST OF MAJOR PATENT OWNERS FOR ARTIFICIAL INTELLIGENCE
5.9.1 LIST OF MAJOR PATENTS
TABLE 9 LIST OF MAJOR PATENTS IN THE AI INFRASTRUCTURE MARKET
5.10 TRADE ANALYSIS
TABLE 10 EXPORTS DATA, BY COUNTRY, 2015–2019 (USD MILLION)
FIGURE 29 EXPORTS DATA FOR HS CODE 854231 FOR TOP FIVE COUNTRIES IN AI INFRASTRUCTURE MARKET, 2015–2019 (THOUSAND UNITS)
TABLE 11 IMPORTS DATA, BY COUNTRY, 2015–2019 (USD MILLION)
FIGURE 30 IMPORTS DATA FOR HS CODE 854231 FOR TOP FIVE COUNTRIES IN AI INFRASTRUCTURE MARKET, 2015–2019 (THOUSAND UNITS)
5.11 CASE STUDY ANALYSIS
5.11.1 KIA MOTORS AMERICA RELIED ON ADVANCED ANALYTICS AND AI SOLUTIONS FROM SAS
5.11.2 VULCAN AI USES AI VISION AND DEEP LEARNING TO CREATE A SAFER WORKPLACE
5.11.3 ACCENTURE, ALONG WITH MICROSOFT, WORKED FOR THE GOVERNMENT OF INDIA TO DEVELOP AN AI TOOL FOR PANDEMIC
5.12 TARIFF AND REGULATORY LANDSCAPE
TABLE 12 TARIFF FOR ELECTRONIC INTEGRATED CIRCUITS AS PROCESSORS AND CONTROLLERS EXPORTED BY US, 2020
TABLE 13 TARIFF FOR ELECTRONIC INTEGRATED CIRCUITS AS PROCESSORS AND CONTROLLERS EXPORTED BY CHINA, 2020
TABLE 14 TARIFF FOR ELECTRONIC INTEGRATED CIRCUITS AS PROCESSORS AND CONTROLLERS EXPORTED BY GERMANY, 2020
5.12.1 REGULATIONS
5.12.1.1 Export-import Regulations
5.12.1.2 Restriction of Hazardous Substances (ROHS) and Waste Electrical and Electronic Equipment (WEEE)
5.12.1.3 Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH)
5.12.1.4 General Data Protection Regulation (GDPR)
5.13 PORTER’S FIVE FORCES ANALYSIS
TABLE 15 PORTER’S FIVE FORCES IMPACT ON THE AI INFRASTRUCTURE MARKET
FIGURE 31 AI INFRASTRUCTURE MARKET: PORTER’S FIVE FORCES ANALYSIS
5.13.1 THREAT OF NEW ENTRANTS
5.13.2 THREAT OF SUBSTITUTES
5.13.3 BARGAINING POWER OF SUPPLIERS
5.13.4 BARGAINING POWER OF BUYERS
5.13.5 INTENSITY OF COMPETITION RIVALRY
6 AI INFRASTRUCTURE MARKET, BY OFFERING (Page No. - 86)
6.1 INTRODUCTION
FIGURE 32 HARDWARE OFFERINGS EXPECTED TO LEAD AI INFRASTRUCTURE MARKET FROM 2021–2026
TABLE 16 AI INFRASTRUCTURE MARKET, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 17 AI INFRASTRUCTURE MARKET, BY OFFERING, 2021–2026 (USD BILLION)
6.2 HARDWARE
FIGURE 33 MEMORY PROJECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 18 HARDWARE IN AI INFRASTRUCTURE MARKET, BY TYPE, 2017–2020 (USD BILLION)
TABLE 19 HARDWARE IN AI INFRASTRUCTURE MARKET, BY TYPE, 2021–2026 (USD BILLION)
TABLE 20 HARDWARE IN AI INFRASTRUCTURE MARKET, BY DEPLOYMENT TYPE, 2017–2020 (USD BILLION)
TABLE 21 HARDWARE IN AI INFRASTRUCTURE MARKET, BY DEPLOYMENT TYPE, 2021–2026 (USD BILLION)
TABLE 22 HARDWARE IN AI INFRASTRUCTURE MARKET, BY FUNCTION, 2017–2020 (USD BILLION)
TABLE 23 HARDWARE IN AI INFRASTRUCTURE MARKET, BY FUNCTION, 2021–2026 (USD BILLION)
TABLE 24 HARDWARE IN AI INFRASTRUCTURE MARKET, BY TECHNOLOGY,2017–2020 (USD BILLION)
TABLE 25 AI INFRASTRUCTURE MARKET FOR HARDWARE OFFERINGS, BY TECHNOLOGY, 2021–2026 (USD BILLION)
TABLE 26 HARDWARE IN AI INFRASTRUCTURE MARKET, BY END USER, 2017–2020 (USD BILLION)
TABLE 27 HARDWARE IN AI INFRASTRUCTURE MARKET, BY END USER, 2021–2026 (USD BILLION)
6.2.1 PROCESSOR
TABLE 28 PROCESSORS IN AI INFRASTRUCTURE MARKET, BY TYPE, 2017–2020 (USD BILLION)
TABLE 29 PROCESSORS IN AI INFRASTRUCTURE MARKET, BY TYPE, 2021–2026 (USD BILLION)
TABLE 30 PROCESSORS IN AI INFRASTRUCTURE MARKET, BY TYPE, 2017–2020 (THOUSAND UNITS)
TABLE 31 PROCESSORS IN AI INFRASTRUCTURE MARKET, BY TYPE, 2021–2026 (THOUSAND UNITS)
6.2.1.1 CPU
6.2.1.1.1 CPU to account for the largest share of AI infrastructure processor market during the forecast period
6.2.1.2 GPU
6.2.1.2.1 NVIDIA is a key provider of GPUs for AI infrastructure
6.2.1.3 FPGA
6.2.1.3.1 Xilinx and Intel are major providers of FPGAs for AI infrastructure
6.2.1.4 ASIC
6.2.1.4.1 ASIC is expected to grow at the highest CAGR during the forecast period
6.2.2 MEMORY
6.2.2.1 High-bandwidth memory, independent of its computing architecture, is developed and deployed for AI applications
6.2.3 STORAGE
6.2.3.1 Artificial intelligence, along with analytics tools, is used in sorting necessary and unessential data
6.2.4 NETWORKING
6.2.4.1 NVIDIA, CISCO, and Intel are key providers of network interconnect adapters for AI applications
6.3 SERVER SOFTWARE
6.3.1 SOFTWARE INTEGRATED INTO EXISTING COMPUTER SYSTEMS CARRIES OUT COMPLEX OPERATIONS
TABLE 32 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY DEPLOYMENT TYPE, 2017–2020 (USD BILLION)
TABLE 33 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY DEPLOYMENT TYPE, 2021–2026 (USD BILLION)
TABLE 34 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY FUNCTION, 2017–2020 (USD BILLION)
TABLE 35 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY FUNCTION, 2021–2026 (USD BILLION)
TABLE 36 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY TECHNOLOGY, 2017–2020 (USD BILLION)
TABLE 37 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY TECHNOLOGY, 2021–2026 (USD BILLION)
TABLE 38 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY END USER, 2017–2020 (USD BILLION)
TABLE 39 SERVER SOFTWARE IN AI INFRASTRUCTURE MARKET, BY END USER, 2021–2026 (USD BILLION)
7 AI INFRASTRUCTURE MARKET, BY TECHNOLOGY (Page No. - 98)
7.1 INTRODUCTION
FIGURE 34 DEEP LEARNING TECHNOLOGY IN AI INFRASTRUCTURE MARKET EXPECTED TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD
TABLE 40 AI INFRASTRUCTURE MARKET, BY TECHNOLOGY, 2017–2020 (USD BILLION)
TABLE 41 AI INFRASTRUCTURE MARKET, BY TECHNOLOGY, 2021–2026 (USD BILLION)
7.2 MACHINE LEARNING
7.2.1 MACHINE LEARNING ENABLES SYSTEMS TO AUTOMATICALLY IMPROVE THEIR PERFORMANCE WITH EXPERIENCES
TABLE 42 AI INFRASTRUCTURE MARKET FOR MACHINE LEARNING, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 43 AI INFRASTRUCTURE MARKET FOR MACHINE LEARNING, BY OFFERING, 2021–2026 (USD BILLION)
7.3 DEEP LEARNING
7.3.1 DEEP LEARNING USES ARTIFICIAL NEURAL NETWORKS TO LEARN MULTIPLE LEVELS OF DATA
TABLE 44 AI INFRASTRUCTURE MARKET FOR DEEP LEARNING, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 45 AI INFRASTRUCTURE MARKET FOR DEEP LEARNING, BY OFFERING, 2021–2026 (USD BILLION)
8 AI INFRASTRUCTURE MARKET, BY FUNCTION (Page No. - 103)
8.1 INTRODUCTION
FIGURE 35 AI INFRASTRUCTURE MARKET FOR TRAINING FUNCTION IS EXPECTED TO GROW AT HIGHER CAGR DURING THE FORECAST PERIOD
TABLE 46 AI INFRASTRUCTURE MARKET, BY FUNCTION, 2017–2020 (USD BILLION)
TABLE 47 AI INFRASTRUCTURE MARKET, BY FUNCTION, 2021–2026 (USD BILLION)
8.2 TRAINING
8.2.1 TRAINING IS COMPUTATIONALLY INTENSIVE AND IS BEST ACCELERATED WITH GPUS
TABLE 48 AI INFRASTRUCTURE MARKET FOR TRAINING, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 49 AI INFRASTRUCTURE MARKET FOR TRAINING, BY OFFERING, 2021–2026 (USD BILLION)
8.3 INFERENCE
8.3.1 ON-PREMISES INFERENCE PLATFORM IS ADOPTED TO GAIN FASTER RESULTS THAN THAT OF THE CLOUD
TABLE 50 AI INFRASTRUCTURE MARKET FOR INFERENCE, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 51 AI INFRASTRUCTURE MARKET FOR INFERENCE, BY OFFERING, 2021–2026 (USD BILLION)
9 AI INFRASTRUCTURE MARKET, BY DEPLOYMENT TYPE (Page No. - 107)
9.1 INTRODUCTION
FIGURE 36 CLOUD DEPLOYMENT IN AI INFRASTRUCTURE MARKET IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 52 AI INFRASTRUCTURE MARKET, BY DEPLOYMENT TYPE, 2017–2020 (USD BILLION)
TABLE 53 AI INFRASTRUCTURE MARKET, BY DEPLOYMENT TYPE, 2021–2026 (USD BILLION)
9.2 ON-PREMISES
9.2.1 DATA-SENSITIVE ENTERPRISES PREFER ON-PREMISES AI SOLUTIONS BASED ON ADVANCED NLP TECHNIQUES AND ML MODELS
TABLE 54 ON-PREMISE AI INFRASTRUCTURE MARKET, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 55 ON-PREMISE AI INFRASTRUCTURE MARKET, BY OFFERING, 2021–2026 (USD BILLION)
9.3 CLOUD
9.3.1 CLOUD-BASED AI SOLUTIONS PROVIDE ADDITIONAL FLEXIBILITY AND MORE ACCURATE REAL-TIME DATA ESSENTIAL FOR EFFECTIVE BUSINESS OPERATIONS
TABLE 56 CLOUD-BASED AI INFRASTRUCTURE MARKET, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 57 CLOUD-BASED AI INFRASTRUCTURE MARKET, BY OFFERING, 2021–2026 (USD BILLION)
9.4 HYBRID
9.4.1 HYBRID INFRASTRUCTURE WOULD HELP IN MAKING WORK PROCESSES FASTER, SAVE TIME AND MONEY
TABLE 58 HYBRID AI INFRASTRUCTURE MARKET, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 59 HYBRID AI INFRASTRUCTURE MARKET, BY OFFERING, 2021–2026 (USD BILLION)
10 AI INFRASTRUCTURE MARKET, BY END USER (Page No. - 112)
10.1 INTRODUCTION
FIGURE 37 AI INFRASTRUCTURE MARKET, BY END USER, 2021–2026 (USD BILLION)
TABLE 60 AI INFRASTRUCTURE MARKET, BY END USER, 2017–2020 (USD BILLION)
TABLE 61 AI INFRASTRUCTURE MARKET, BY END USER, 2021–2026 (USD BILLION)
10.2 ENTERPRISES
10.2.1 THE UTILIZATION OF ADVANCED BIG DATA SOLUTIONS FOR OPERATIONAL DATA EXPLOSION IS IMPACTING FUTURE REQUIREMENTS FOR AI-BASED SERVERS
FIGURE 38 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN APAC IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 62 AI INFRASTRUCTURE MARKET FOR ENTERPRISES, BY REGION, 2017–2020 (USD BILLION)
TABLE 63 AI INFRASTRUCTURE MARKET FOR ENTERPRISES, BY REGION, 2021–2026 (USD BILLION)
TABLE 64 AI INFRASTRUCTURE MARKET FOR ENTERPRISES, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 65 AI INFRASTRUCTURE MARKET FOR ENTERPRISES, BY OFFERING, 2021–2026 (USD BILLION)
TABLE 66 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN NORTH AMERICA, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 67 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN NORTH AMERICA, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 68 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN EUROPE, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 69 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN EUROPE, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 70 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN APAC, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 71 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN APAC, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 72 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN ROW, BY REGION, 2017–2020 (USD BILLION)
TABLE 73 AI INFRASTRUCTURE MARKET FOR ENTERPRISES IN ROW, BY REGION, 2021–2026 (USD BILLION)
10.3 GOVERNMENT ORGANIZATIONS
10.3.1 GOVERNMENTS WORLDWIDE ARE WORKING TOWARD IMPLEMENTING AI IN SECURITY SOLUTIONS TO PROTECT CRITICAL GOVERNMENT AND DEFENSE-RELATED INFRASTRUCTURE
FIGURE 39 HARDWARE OFFERINGS IN GOVERNMENT ORGANIZATIONS PROJECTED TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD
TABLE 74 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 75 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS, BY OFFERING, 2021–2026 (USD BILLION)
TABLE 76 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS, BY REGION, 2017–2020 (USD BILLION)
TABLE 77 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS, BY REGION, 2021–2026 (USD BILLION)
TABLE 78 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN NORTH AMERICA, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 79 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN NORTH AMERICA, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 80 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN EUROPE, BY COUNTRY, 2017–2020 (USD MILLION)
TABLE 81 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN EUROPE, BY COUNTRY, 2021–2026 (USD MILLION)
TABLE 82 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN APAC, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 83 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN APAC, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 84 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN ROW, BY REGION, 2017–2020 (USD BILLION)
TABLE 85 AI INFRASTRUCTURE MARKET FOR GOVERNMENT ORGANIZATIONS IN ROW, BY REGION, 2021–2026 (USD BILLION)
10.4 CLOUD SERVICE PROVIDERS (CSP)
10.4.1 CLOUD SERVICE PROVIDERS DELIVER INDUSTRY-SPECIFIC FUNCTIONALITY OR HELP USERS MEET CERTAIN REGULATORY REQUIREMENTS
FIGURE 40 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN APAC IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 86 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS, BY REGION, 2017–2020 (USD BILLION)
TABLE 87 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS, BY REGION, 2021–2026 (USD BILLION)
TABLE 88 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS, BY OFFERING, 2017–2020 (USD BILLION)
TABLE 89 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS, BY OFFERING, 2021–2026 (USD BILLION)
TABLE 90 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN NORTH AMERICA, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 91 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN NORTH AMERICA, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 92 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN EUROPE, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 93 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN EUROPE, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 94 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN APAC, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 95 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN APAC, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 96 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN ROW, BY REGION, 2017–2020 (USD BILLION)
TABLE 97 AI INFRASTRUCTURE MARKET FOR CLOUD SERVICE PROVIDERS IN ROW, BY REGION, 2021–2026 (USD BILLION)
11 GEOGRAPHIC ANALYSIS (Page No. - 129)
11.1 INTRODUCTION
FIGURE 41 GEOGRAPHIC SNAPSHOT: AI INFRASTRUCTURE MARKET IN APAC EXPECTED TO GROW AT THE HIGHEST CAGR DURING FORECAST PERIOD
FIGURE 42 AMONG COUNTRIES, THE US IS EXPECTED TO LEAD AI INFRASTRUCTURE MARKET FROM 2021 TO 2026
TABLE 98 AI INFRASTRUCTURE MARKET, BY REGION, 2017–2020 (USD BILLION)
TABLE 99 AI INFRASTRUCTURE MARKET, BY REGION, 2021–2026 (USD BILLION)
11.2 NORTH AMERICA
FIGURE 43 NORTH AMERICA: AI INFRASTRUCTURE MARKET SNAPSHOT
TABLE 100 AI INFRASTRUCTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 101 AI INFRASTRUCTURE MARKET IN NORTH AMERICA, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 102 AI INFRASTRUCTURE MARKET IN NORTH AMERICA, BY END USER, 2017–2020 (USD BILLION)
TABLE 103 AI INFRASTRUCTURE MARKET IN NORTH AMERICA, BY END USER, 2021–2026 (USD BILLION)
11.2.1 US
11.2.1.1 Improved economy and high disposable income in the US drive the demand for modern technologies, and thereby boost the market
TABLE 104 AI INFRASTRUCTURE MARKET IN US, BY END USER, 2017–2020 (USD BILLION)
TABLE 105 AI INFRASTRUCTURE MARKET IN US, BY END USER, 2021–2026 (USD BILLION)
11.2.2 CANADA
11.2.2.1 High adoption of AI technologies is fueling the market in this country
TABLE 106 AI INFRASTRUCTURE MARKET IN CANADA, BY END USER, 2017–2020 (USD BILLION)
TABLE 107 AI INFRASTRUCTURE MARKET IN CANADA, BY END USER, 2021–2026 (USD BILLION)
11.2.3 MEXICO
11.2.3.1 The market is driven by the growing penetration of AI in security and BFSI industries in the country
TABLE 108 AI INFRASTRUCTURE MARKET IN MEXICO, BY END USER, 2017–2020 (USD BILLION)
TABLE 109 AI INFRASTRUCTURE MARKET IN MEXICO, BY END USER, 2021–2026 (USD BILLION)
11.3 EUROPE
FIGURE 44 EUROPE: AI INFRASTRUCTURE MARKET SNAPSHOT
TABLE 110 AI INFRASTRUCTURE MARKET IN EUROPE, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 111 AI INFRASTRUCTURE MARKET IN EUROPE, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 112 AI INFRASTRUCTURE MARKET IN EUROPE, BY END USER, 2017–2020 (USD BILLION)
TABLE 113 AI INFRASTRUCTURE MARKET IN EUROPE, BY END USER, 2021–2026 (USD BILLION)
11.3.1 UK
11.3.1.1 Government initiatives to increase the adoption of AI would drive the market in the UK
TABLE 114 AI INFRASTRUCTURE MARKET IN UK, BY END USER, 2017–2020 (USD BILLION)
TABLE 115 AI INFRASTRUCTURE MARKET IN UK, BY END USER, 2021–2026 (USD BILLION)
11.3.2 GERMANY
11.3.2.1 Adoption of cloud computing and Industry 4.0 increased demand for data centers in Germany and thereby is expected to drive the market
TABLE 116 AI INFRASTRUCTURE MARKET IN GERMANY, BY END USER, 2017–2020 (USD BILLION)
TABLE 117 AI INFRASTRUCTURE MARKET IN GERMANY, BY END USER, 2021–2026 (USD BILLION)
11.3.3 FRANCE
11.3.3.1 Investment of venture capitalists in startups for the development of AI ecosystem surge AI infrastructure market growth in the country
TABLE 118 AI INFRASTRUCTURE MARKET IN FRANCE, BY END USER, 2017–2020 (USD BILLION)
TABLE 119 AI INFRASTRUCTURE MARKET IN FRANCE, BY END USER, 2021–2026 (USD BILLION)
11.3.4 REST OF EUROPE
11.3.4.1 Government investments are expected to drive the market in this region
TABLE 120 AI INFRASTRUCTURE MARKET IN REST OF EUROPE, BY END USER, 2017–2020 (USD BILLION)
TABLE 121 AI INFRASTRUCTURE MARKET IN REST OF EUROPE, BY END USER, 2021–2026 (USD BILLION)
11.4 APAC
FIGURE 45 APAC: AI INFRASTRUCTURE MARKET SNAPSHOT
TABLE 122 AI INFRASTRUCTURE MARKET IN APAC, BY COUNTRY, 2017–2020 (USD BILLION)
TABLE 123 AI INFRASTRUCTURE MARKET IN APAC, BY COUNTRY, 2021–2026 (USD BILLION)
TABLE 124 AI INFRASTRUCTURE MARKET IN APAC, BY END USER, 2017–2020 (USD BILLION)
TABLE 125 AI INFRASTRUCTURE MARKET IN APAC, BY END USER, 2021–2026 (USD BILLION)
11.4.1 CHINA
11.4.1.1 Strong R&D activities have been the driver for the market growth in China
TABLE 126 AI INFRASTRUCTURE MARKET IN CHINA, BY END USER, 2017–2020 (USD BILLION)
TABLE 127 AI INFRASTRUCTURE MARKET IN CHINA, BY END USER, 2021–2026 (USD BILLION)
11.4.2 JAPAN
11.4.2.1 Small and medium-sized companies in Japan are utilizing infrastructure-as-a-service
TABLE 128 AI INFRASTRUCTURE MARKET IN JAPAN, BY END USER, 2017–2020 (USD BILLION)
TABLE 129 AI INFRASTRUCTURE MARKET IN JAPAN, BY END USER, 2021–2026 (USD BILLION)
11.4.3 INDIA
11.4.3.1 Growing adoption of cloud-based services expected to positively impact the AI infrastructure market
TABLE 130 AI INFRASTRUCTURE MARKET IN INDIA, BY END USER, 2017–2020 (USD BILLION)
TABLE 131 AI INFRASTRUCTURE MARKET IN INDIA, BY END USER, 2021–2026 (USD BILLION)
11.4.4 REST OF APAC
11.4.4.1 Increasing adoption of cloud services by small and medium-sized enterprises expected to drive the market in this region
TABLE 132 AI INFRASTRUCTURE MARKET IN REST OF APAC, BY END USER, 2017–2020 (USD BILLION)
TABLE 133 AI INFRASTRUCTURE MARKET IN REST OF APAC, BY END USER, 2021–2026 (USD BILLION)
11.5 ROW
TABLE 134 AI INFRASTRUCTURE MARKET IN ROW, BY REGION, 2017–2020 (USD BILLION)
TABLE 135 AI INFRASTRUCTURE MARKET IN ROW, BY REGION, 2021–2026 (USD BILLION)
TABLE 136 AI INFRASTRUCTURE MARKET IN ROW, BY END USER, 2017–2020 (USD BILLION)
TABLE 137 AI INFRASTRUCTURE MARKET IN ROW, BY END USER,2021–2026 (USD BILLION)
11.5.1 SOUTH AMERICA
11.5.1.1 Increased availability of computing services in the region expected to drive the market
TABLE 138 AI INFRASTRUCTURE MARKET IN SOUTH AMERICA, BY END USER, 2017–2020 (USD BILLION)
TABLE 139 AI INFRASTRUCTURE MARKET IN SOUTH AMERICA, BY END USER, 2021–2026 (USD BILLION)
11.5.2 MIDDLE EAST & AFRICA
11.5.2.1 Smart mobile data traffic would increase the workload on data centers and thereby boost AI server growth
TABLE 140 AI INFRASTRUCTURE MARKET IN MIDDLE EAST & AFRICA, BY END USER, 2017–2020 (USD BILLION)
TABLE 141 AI INFRASTRUCTURE MARKET IN MIDDLE EAST & AFRICA, BY END USER, 2021–2026 (USD BILLION)
12 COMPETITIVE LANDSCAPE (Page No. - 157)
12.1 OVERVIEW
FIGURE 46 COMPANIES ADOPTED PRODUCT LAUNCHES AS A KEY GROWTH STRATEGY FROM 2020 TO 2021
12.2 REVENUE ANALYSIS OF KEY PLAYERS IN THE AI INFRASTRUCTURE MARKET
FIGURE 47 TOP PLAYERS IN AI INFRASTRUCTURE MARKET, 2016–2020
12.3 MARKET SHARE ANALYSIS OF KEY PLAYERS IN AI INFRASTRUCTURE (PROCESSOR) MARKET IN 2020
TABLE 142 AI INFRASTRUCTURE (PROCESSOR) MARKET: DEGREE OF COMPETITION
12.4 MARKET RANKING ANALYSIS OF KEY PLAYERS IN AI INFRASTRUCTURE (STORAGE) MARKET IN 2020
FIGURE 48 AI INFRASTRUCTURE (STORAGE) MARKET, RANKING OF KEY PLAYERS, 2020
12.5 COMPANY EVALUATION QUADRANT
12.5.1 STARS
12.5.2 EMERGING LEADERS
12.5.3 PERVASIVE
12.5.4 PARTICIPANTS
FIGURE 49 AI INFRASTRUCTURE MARKET: COMPANY EVALUATION QUADRANT, 2020
12.6 COMPANY EVALUATION QUADRANT – PRODUCT FOOTPRINT
12.6.1 COMPANY FOOTPRINT, BY TECHNOLOGY
12.6.2 COMPANY FOOTPRINT, BY END-USER
12.6.3 COMPANY FOOTPRINT, BY REGION
12.6.4 COMPANY FOOTPRINT
12.7 STARTUP/SME EVALUATION QUADRANT, 2020
12.7.1 PROGRESSIVE COMPANY
12.7.2 RESPONSIVE COMPANY
12.7.3 DYNAMIC COMPANY
12.7.4 STARTING BLOCK
FIGURE 50 AI INFRASTRUCTURE MARKET (GLOBAL) STARTUP/SME EVALUATION QUADRANT, 2020
12.8 COMPETITIVE SITUATIONS AND TRENDS
12.8.1 NEW PRODUCT LAUNCHES AND DEVELOPMENTS
TABLE 143 NEW PRODUCT LAUNCHES AND DEVELOPMENTS, 2020–2021
12.8.2 DEALS
TABLE 144 DEALS, 2020–2021
13 COMPANY PROFILES (Page No. - 171)
(Business Overview, Products/solutions/services Offered, Recent Developments, and MnM View (Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats))*
13.1 INTRODUCTION
13.2 KEY PLAYERS
13.2.1 INTEL
TABLE 145 INTEL: BUSINESS OVERVIEW
FIGURE 51 INTEL: COMPANY SNAPSHOT
13.2.2 NVIDIA
TABLE 146 NVIDIA: BUSINESS OVERVIEW
FIGURE 52 NVIDIA: COMPANY SNAPSHOT
13.2.3 AMD
TABLE 147 AMD: BUSINESS OVERVIEW
FIGURE 53 AMD: COMPANY SNAPSHOT
13.2.4 SAMSUNG ELECTRONICS
TABLE 148 SAMSUNG ELECTRONICS: BUSINESS OVERVIEW
FIGURE 54 SAMSUNG ELECTRONICS: COMPANY SNAPSHOT
13.2.5 XILINX
TABLE 149 XILINX: BUSINESS OVERVIEW
FIGURE 55 XILINX: COMPANY SNAPSHOT
13.2.6 MICRON TECHNOLOGY
TABLE 150 MICRON TECHNOLOGY: BUSINESS OVERVIEW
FIGURE 56 MICRON TECHNOLOGY: COMPANY SNAPSHOT
13.2.7 IBM
TABLE 151 IBM: BUSINESS OVERVIEW
FIGURE 57 IBM: COMPANY SNAPSHOT
13.2.8 GOOGLE
TABLE 152 GOOGLE: BUSINESS OVERVIEW
FIGURE 58 GOOGLE: COMPANY SNAPSHOT
13.2.9 MICROSOFT
TABLE 153 MICROSOFT: BUSINESS OVERVIEW
FIGURE 59 MICROSOFT: COMPANY SNAPSHOT
13.2.10 AMAZON WEB SERVICE
TABLE 154 AMAZON WEB SERVICE (AWS): BUSINESS OVERVIEW
FIGURE 60 AMAZON WEB SERVICE: COMPANY SNAPSHOT
13.3 OTHER KEY PLAYERS
13.3.1 GRAPHCORE
TABLE 155 GRAPHCORE: COMPANY OVERVIEW
13.3.2 SK HYNIX
TABLE 156 SK HYNIX: COMPANY OVERVIEW
13.3.3 CISCO
TABLE 157 CISCO: COMPANY OVERVIEW
13.3.4 ARM
TABLE 158 ARM: COMPANY OVERVIEW
13.3.5 DELL
TABLE 159 DELL: COMPANY OVERVIEW
13.3.6 HPE
TABLE 160 HPE: COMPANY OVERVIEW
13.3.7 WAVE COMPUTING
TABLE 161 WAVE COMPUTING: COMPANY OVERVIEW
13.3.8 TOSHIBA
TABLE 162 TOSHIBA: COMPANY OVERVIEW
13.3.9 GYRFALCON TECHNOLOGY
TABLE 163 GYRFALCON TECHNOLOGY: COMPANY OVERVIEW
13.3.10 IMAGINATION TECHNOLOGIES
TABLE 164 IMAGINATION TECHNOLOGIES: COMPANY OVERVIEW
13.3.11 CAMBRICON TECHNOLOGIES
TABLE 165 CAMBRICON TECHNOLOGIES: COMPANY OVERVIEW
13.3.12 CADENCE DESIGN SYSTEMS
TABLE 166 CADENCE DESIGN SYSTEMS: COMPANY OVERVIEW
13.3.13 TENSTORRENT
TABLE 167 TENSTORRENT: COMPANY OVERVIEW
13.3.14 SYNOPSYS
TABLE 168 SYNOPSYS: COMPANY OVERVIEW
13.3.15 SENSETIME
TABLE 169 SENSETIME: COMPANY OVERVIEW
*Details on Business Overview, Products/solutions/services Offered, Recent Developments, and MnM View (Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats) might not be captured in case of unlisted companies.
14 APPENDIX (Page No. - 230)
14.1 INSIGHTS OF INDUSTRY EXPERTS
14.2 DISCUSSION GUIDE
14.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
14.4 AVAILABLE CUSTOMIZATIONS
14.5 RELATED REPORTS
14.6 AUTHOR DETAILS
The study involved four major activities in estimating the size of the AI infrastructure market. Exhaustive secondary research was done to collect information on the market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain through primary research. Both top-down and bottom-up approaches were employed to estimate the total market’s size. After that, market breakdown and data triangulation were used to determine the market sizes of segments and sub-segments.
Secondary Research
The secondary sources referred to for this research study include organizations such as Association for the Advancement of Artificial Intelligence (AAAI), European Association for Artificial Intelligence (EurAI) , AI Association of Patent and Trademark Attorneys (AIPAT), Data Science Association, International Association for Artificial Intelligence and Law (IAAIL), white papers, AI-related marketing journals, certified publications, and articles from recognized authors; gold and silver standard websites; directories; and databases. Secondary data has been collected and analyzed to arrive at the overall market size, which is further validated by primary research.
Primary Research
Extensive primary research has been conducted after acquiring an understanding of the AI infrastructure market scenario through secondary research. Several primary interviews have been conducted with market experts from both the demand- (enterprises, cloud service providers, government organizations) and supply-side (OEM/ODM, system integrators, solution providers) players across four major regions, namely, Americas, Europe, APAC, and Rest of the World (Middle East, Africa). Approximately 75% and 25% of primary interviews have been conducted from the demand and supply side, respectively. Primary data has been collected through questionnaires, emails, and telephonic interviews. In the canvassing of primaries, various departments within organizations, such as sales, operations, and administration, were covered to provide a holistic viewpoint in our report.
After interacting with industry experts, brief sessions were conducted with highly experienced independent consultants to reinforce the findings from our primaries. This, along with the in-house subject matter experts’ opinions, has led us to the findings as described in the remainder of this report.
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
Both top-down and bottom-up approaches were used to estimate and validate the total size of the AI infrastructure market. These methods were also extensively used to estimate the sizes of various market sub-segments. The research methodology used to estimate the market sizes includes the following:
- The key players in the market were identified through extensive secondary research.
- The industry’s supply chain and market size, in terms of value, were determined through primary and secondary research.
All percentage shares, splits, and breakdowns were determined using secondary sources and verified through primary sources. Qualitative aspects such as market drivers, restraints, opportunities, and challenges have been taken into consideration while calculating and forecasting the market size.
Global AI Infrastructure Market Size: Bottom-Up Approach
Data Triangulation
After arriving at the overall market size-using the market size estimation processes explained above-the market was split into several segments and sub-segments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakdown procedures were employed, wherever applicable. The data was triangulated by studying various factors and trends from both the demand and supply sides.
Report Objectives:
- To define, describe, and forecast the head-mounted display (HMD) market, in terms of value, on the basis of type, technology, product type, component, connectivity, application, and region
- To describe, segment, and forecast the AI infrastructure market, by offering, deployment, function, technology, and end user, in terms of value
- To describe, segment, and forecast the AI infrastructure market, by offering, in terms of volume
- To describe and forecast the market for various segments, by region—North America, Europe, Asia Pacific (APAC), and the Rest of the World (RoW)
- To provide detailed information regarding drivers, restraints, opportunities, and challenges that influence the growth of the AI infrastructure market
- To provide a detailed overview of the AI infrastructure value chain
- To analyze micromarkets with respect to individual growth trends, prospects, and contribution to the overall AI infrastructure market
- To analyze opportunities in the market for stakeholders by identifying the high-growth segments of the AI infrastructure market
- To profile key players in the AI infrastructure market and comprehensively analyze their market ranking in terms of revenues, shares, and core competencies
- To analyze the competitive strategies such as product launches and developments, partnerships & collaborations, and acquisitions in the global AI infrastructure market
Available Customizations:
With the given market data, MarketsandMarkets offers customizations according to the company’s specific needs. The following customization options are available for the report:
Company Information
- Detailed analysis and profiling of additional market players (up to 5)
- Triangulate with your Own Data
- Get Data as per your Format and Definition
- Gain a Deeper Dive on a Specific Application, Geography, Customer or Competitor
- Any level of Personalization
- What are the Known and Unknown Adjacencies Impacting the AI Infrastructure Market
- What will your New Revenue Sources be?
- Who will be your Top Customer; what will make them switch?
- Defend your Market Share or Win Competitors
- Get a Scorecard for Target Partners
Growth opportunities and latent adjacency in AI Infrastructure Market