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AI Infrastructure Markets to 2025 - Cloud Deployment to Hold the Largest Share, Dominated by IBM, Microsoft, AWS (Amazon.com), Alibaba Cloud, and Google
[July 11, 2019]

AI Infrastructure Markets to 2025 - Cloud Deployment to Hold the Largest Share, Dominated by IBM, Microsoft, AWS (Amazon.com), Alibaba Cloud, and Google


DUBLIN, July 11, 2019 /PRNewswire/ -- The "AI Infrastructure Market by Offering (Hardware, Software), Technology (Machine Learning, Deep Learning), Function (Training, Inference), Deployment Type (On-Premises, Cloud, Hybrid), End User, and Region - Global Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.

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The global AI infrastructure market is projected to grow from USD 14.6 billion in 2019 to USD 50.6 billion by 2025, at a CAGR of 23.1%.

This research report segments the global AI infrastructure market on the basis of offering, technology, deployment, end-user, function geography. The report discusses major drivers, restraints, challenges, and opportunities pertaining to the AI infrastructure market and also includes value chain. The study also includes an in-depth competitive analysis of key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

A few AI infrastructure ecosystem players are as follows: SK HYNIX Inc. (South Korea), Wave Computing (US), Toshiba (Japan), Imagination Technologies (UK), Cambricon Technology (China), Cadence (US), Graphcore (UK), Gyrfalcon Technology Inc. (US), and Tensotorrent Inc. (Canada).

Drivers & Restraints

Major factors driving the AI infrastructure market growth include increasing adoption of cloud machine learning platform, escalating demand for AI hardware in high-performance computing data centers, rising focus on parallel computing in AI data centers, growing volume of data generated in industries such as automotive and healthcare, improving computing power and declining hardware cost, growing number of cross-industry partnerships and collaborations, and expanding AI applications in industries such as healthcare, automotive, finance, and tourism. However, mature markets in North America and Europe is one of the key factors restraining the growth of the market.

Cloud deployment to hold largest share of AI infrastructure market by 2025

The cloud deployment mode provides several benefits, such as reduced operational costs, hassle-free deployment, and high scalability, easy data accessibility, faster access to critical data, and low capital requirement. The demand for the cloud deployment mode for NLP and ML tools in AI is expected to increase with the growing awareness of the benefits of cloud-based solutions.

AI solution providers are focusing on the development of robust cloud-based solutions for their clients as many organizations have migrated from on-premises to either private or public cloud. Moreover, the cloud provides additional flexibility for business operations and real-time data accessibility to companies.

The cloud platform provides improved predictive capability as this type of deployment mode enables faster alarm notification in critical situations. Further, it helps in maintaining a competitive edge by eliminating the administrative roadblocks of the supporting infrastructure and enables organizations to focus on improving their competencies. Major vendors offering cloud-based AI platforms include IBM (US), Microsoft (US), Amazon.com's AWS (US), Alibaba Cloud (China), and Google (US).

Processors to account for largest share of AI infrastructure hardware market

The processor segment includes CPUs, microprocessing units (MPUs), graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs). GPUs are being conventionally developed by companies such as NVIDIA (US) and ARM (UK).

High parallel processing capabilities and improved computing power are the major benefits leading to high adoption of processors in various AI applications. Tensor Processing Units (TPUs) were launched by Google (an Alphabet (US) company) in early 2016. Intel (US) has been a leading provider of CPUs, and Xilinx Inc. (US) is a major provider of FPGAs for AI applications.

APAC is likely to witness significant CAGR in AI infrastructure market during forecast period

APAC is expected to continue to lead the AI infrastructure market and is also likely to be the fastest-growing region. This is mainly attributed due to the increase in the number of manufacturing plants in various sectors, such as automotive, automation, power, and increasing adoption of cloud-based services and machine learning platform.

A few of the prolific automotive equipment manufacturers are present in APAC countries such as Chna, Japan, South Korea, and India. Therefore, the AI infrastructure market in APAC is likely to grow at the highest CAGR during the forecast period.



Key Topics Covered

1 Introduction
1.1 Study Objectives
1.2 Definition
1.3 Study Scope
1.3.1 Markets Covered
1.3.2 Geographic Scope
1.3.3 Years Considered
1.4 Currency
1.5 Limitations
1.6 Stakeholders


2 Research Methodology
2.1 Research Data
2.1.1 Secondary Data
2.1.1.1 Secondary Sources
2.1.2 Primary Data
2.1.2.1 Primaries Sources
2.1.2.2 Key Industry Insights
2.1.2.3 Breakdown of Primaries
2.2 Market Size Estimation
2.2.1 Bottom-Up Approach
2.2.2 Top-Down Approach
2.3 Market Breakdown and Data Triangulation
2.4 Research Assumptions

3 Executive Summary

4 Premium Insights
4.1 Attractive Opportunities in AI Infrastructure Market
4.2 AI Infrastructure Hardware Market, By Type
4.3 AI Infrastructure Market, By Deployment
4.4 AI Infrastructure Market, By Function
4.5 AI Infrastructure Market for Enterprise, By Region
4.6 AI Infrastructure Market, By Technology
4.7 AI Infrastructure Market, By Geography

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increasing Adoption of Cloud Machine Learning Platform
5.2.1.2 Escalating Demand for AI Hardware in High-Performance Computing Data Centers
5.2.1.3 Rising Focus on Parallel Computing in AI Data Centers
5.2.1.4 Growing Volume of Data Generated in Industries Such as Automotive and Healthcare
5.2.1.5 Improving Computing Power and Declining Hardware Cost
5.2.1.6 Growing Number of Cross-Industry Partnerships and Collaborations
5.2.1.7 Expanding AI Applications in Industries Such as Healthcare, Automotive, Finance, and Tourism
5.2.1.8 Evolving Applications of Industrial IoT and Automation Technologies
5.2.2 Restraints
5.2.2.1 Dearth of AI Hardware Experts
5.2.3 Opportunities
5.2.3.1 Surging Demand for FPGA-Based Accelerators
5.2.3.2 Rising Need for Coprocessors Due to Slowdown of Moore's Law
5.2.3.3 Increasing Focus on Developing Human-Aware AI Systems
5.2.4 Challenges
5.2.4.1 Unreliability of AI Algorithms
5.2.4.2 Creation of Application-Specific Models and Mechanisms of AI in Cloud
5.2.4.3 Concerns Regarding Data Privacy in AI Platforms
5.2.4.4 No Assurance or Guarantee on Returns on Investment
5.2.4.5 Availability of Limited Structured Data to Train and Develop Efficient AI Systems

6 AI Infrastructure Market, By Offering
6.1 Introduction
6.2 Hardware
6.2.1 Processor
6.2.1.1 CPU
6.2.1.2 GPU
6.2.1.3 FPGA
6.2.1.4 ASIC
6.2.2 Memory
6.2.2.1 High-Bandwidth Memory, Independent of Its Computing Architecture, is Being 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 (US), Intel (US) And CISCO (US) Are Key Providers of Network Interconnect Adapters for AI Applications
6.3 Server Software
6.3.1 Creating Intelligent Software Involves Simulating Several Capabilities Such as Problem-Solving, Perception, and Knowledge Representation

7 AI Infrastructure Market, By Technology
7.1 Introduction
7.2 Machine Learning
7.2.1 Machine Learning Enables Systems to Automatically Improve Their Performance With Experience
7.3 Deep Learning
7.3.1 Deep Learning Uses Artificial Neural Networks to Learn Multiple Levels of Data

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

9 AI Infrastructure Market, By Deployment Type
9.1 Introduction
9.2 On-Premises
9.2.1 Data-Sensitive Enterprises Prefer On-Premises AI Solutions Based on Advanced Nlp Techniques and Ml Models
9.3 Cloud
9.3.1 Cloud-Based AI Solutions Provide Additional Flexibility and More Accurate Real-Time Data Essential for Effective Business Operations
9.4 Hybrid
9.4.1 Hybrid Infrastructure Would Help in Fast Work Processes, Saving Time, and Money

10 AI Infrastructure Market, By End-User
10.1 Introduction
10.2 Enterprises
10.2.1 Utilization of Advanced Big Data Solutions for Operational Data Explosion is Impacting Future Requirements for AI-Based Servers
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
10.4 Cloud Service Providers (CSP)
10.4.1 Cloud Service Providers Need to Deliver Industry-Specific Functionality or Help Users Meet Certain Regulatory Requirements

11 Geographic Analysis
11.1 Introduction
11.2 North America
11.2.1 US
11.2.1.1 Improved Economy and High Disposable Income in US Lead to Increased Demand for Modern Technologies, Which, in Turn, Boosts AI Infrastructure Market Growth
11.2.2 Canada
11.2.2.1 High Adoption of AI Technologies, Especially Ml and Nlp, is Fueling Canadian Market Growth
11.2.3 Mexico
11.2.3.1 Mexican Market Growth is Driven By Growing Penetration of AI in Security and BFSI Industries in Country
11.3 Europe
11.3.1 UK
11.3.1.1 Adoption of Supercomputers Would Drive Market in UK
11.3.2 Germany
11.3.2.1 Adoption of Cloud Computing and Industry 4.0 has Created Increased Demand for Data Centers in Germany
11.3.3 France
11.3.3.1 Investment of Venture Capitalists in French Start-Ups for Development of AI Ecosystem Surge AI Infrastructure Market Growth in Country
11.3.4 Rest of Europe
11.3.4.1 Spain, Italy, Sweden, Norway, Netherlands, Belgium, Russia, and Poland Drive AI Infrastructure Market Growth in Rest of Europe
11.4 APAC
11.4.1 China
11.4.1.1 Growing Demand for High-Density, Redundant Facilities is Triggering Deployment of Data Centers, Thereby Escalating Demand for AI Infrastructure
11.4.2 Japan
11.4.2.1 Small and Medium-Sized Companies in Japan are Utilizing Infrastructure-As-A-Service (Through Cloud)
11.4.3 India
11.4.3.1 Growing Adoption of Cloud-Based Services to Have Positive Impact on AI Infrastructure Market
11.4.4 Rest of APAC
11.4.4.1 Australia, Thailand, South Korea, and Indonesia are Major Countries Responsible for Growth in Rest of APAC
11.5 RoW
11.5.1 South America
11.5.1.1 Brazil has Largest Computing Services Market in South America, Followed By Chile and Argentina
11.5.2 Middle East and Africa
11.5.2.1 Smart Mobile Data Traffic Would Lead to Increased Workload on Data Centers, Resulting in AI Server Growth

12 Competitive Landscape
12.1 Overview
12.2 Ranking Analysis of Key Players in AI Infrastructure Market
12.3 Competitive Situations and Trends
12.3.1 Product Launches
12.3.2 Agreements, Partnerships, Collaborations, & Contracts
12.3.3 Acquisitions
12.3.4 AI Infrastructure Market (Global) Competitive Leadership Mapping, 2018
12.3.4.1 Visionary Leaders
12.3.4.2 Dynamic Differentiators
12.3.4.3 Innovators
12.3.4.4 Emerging Companies

13 Company Profiles
13.1.1 Intel Corporation
13.1.1.1 Business Overview
13.1.1.2 Products and Solutions Offered
13.1.1.3 Recent Developments
13.1.1.4 SWOT Analysis
13.1.2 NVIDIA Corporation
13.1.3 Samsung Electronics
13.1.4 Micron Technology
13.1.5 Xilinx
13.1.6 Advanced Micro Devices (AMD)
13.1.7 IBM
13.1.8 Google
13.1.9 Microsoft
13.1.10 Amazon Web Services
13.1.11 CISCO
13.1.12 ARM
13.1.13 Dell
13.1.14 HPE
13.1.15 Habana Labs
13.1.16 Synopsys Inc.
13.2 Other Key Players
13.2.1 S K Hynix Inc.
13.2.2 Wave Computing
13.2.3 Toshiba
13.2.4 Imagination Technologies
13.2.5 Cambricon Technologies
13.2.6 Graphcore
13.2.7 Gyrfalcon Technology Inc.
13.2.8 Cadence Design Systems
13.2.9 Tenstorrent

For more information about this report visit https://www.researchandmarkets.com/r/o3ujj4

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

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SOURCE Research and Markets


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