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AI Infrastructure Market Size, Share & Industry Trends Analysis Report By Offering (Hardware and Server Software), By End User, By Deployment Type, By Function (Inference and Training), By Technology, By Regional Outlook and Forecast, 2022 - 2028

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    Report

  • 302 Pages
  • August 2022
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5659273
The Global AI Infrastructure Market size is expected to reach $122.8 billion by 2028, rising at a market growth of 24.7% CAGR during the forecast period.

Platforms for building intelligent applications that really are predictive, self-healing, and need little human interaction are known as artificial intelligence (AI) infrastructure. Innovative technologies such as Mobility, IoT, and Big Data are straining IT infrastructure. More than ever, the requirement for intelligent infrastructure is essential for maximizing the potential of AI systems. Every stage of the machine learning workflow is supported by AI infrastructure.



It enables the management and availability of computer resources for the development, testing, and deployment of AI algorithms by data engineers, data scientists, DevOps teams, and software developers. The workload is mapped to the appropriate setup of servers and virtual machines using AI infrastructure. Organizations can now concentrate on resource use, capacity planning, storage management, anomaly detection,
The market for AI infrastructure is expanding as a result of rising adoption of cloud machine learning platforms in businesses and rising demand for AI hardware in strong computing data centres. The market for AI infrastructure is anticipated to grow as the use of Ai technologies in vertical industries like healthcare, BFSI, automotive, and tourism increases. The market for AI infrastructure is also expanding for other reasons.

As businesses increase operational effectiveness and cut costs by automating process flows, they are coming to see the value of integrating artificial intelligence (AI) into their business operations. As a result, businesses have started utilizing autonomous processes to enhance operations and transform customer service (for instance, through chatbots driven by AI), all the while catalyzing creativity to new heights.



The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The below illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions.

COVID-19 Impact Analysis

Due to the dynamic nature of cloud services and their ability to handle unanticipated surges in service demand, the COVID-19 outbreak led many enterprises to expedite their migrations to public cloud solutions. In the era of COVID-19, cloud migrations let enterprises reimagine how they run their operations. Numerous cloud providers now deliver AIaaS and MLaaS due to the increase in demand for AI services. Due to this, the healthcare sector of the cloud market had significant growth in 2020. A lot of AI and ML technology is being employed to combat COVID-19.

Market Growth Factors

Increasing Focus On Parallel Computing In Ai Data Centers

In data centres, CPUs are utilised for serial computing to keep track of a number of memory regions where data and instructions are kept. A processor analyses the instructions and data at the memory locations to perform computations in serial. The steps of a computation are logically ordered and sequential in serial computation. In addition, a processor at a data centre divides a single task into a number of distinct instructions sets that are carried out in a serial fashion. This frequently causes latency issues in data centres, especially when performing AI-based calculations with large data and instruction sets.

Rising Demand For Ai Software And Hardware Among Enterprises

In order to keep up with the growing volume of data created by applications, advanced AI solutions frequently necessitate new hardware and software. These AI-based solutions, for instance, require updates regarding the annotation and collection of data sources, as well as the creation, processing, and fine-tuning of models when more data becomes available. Deep learning, a branch of AI technology, has grown to be one of the most significant computational workloads for businesses and will increase the use of AI infrastructure.

Market Restraining Factors

Absence Of Skilled Professionals In The Market

Companies need expertise and a competent team to create, manage, and integrate AI systems because they are a complicated system. People working with AI systems must be knowledgeable about technologies including machine intelligence, deep learning, machine learning (ML), image recognition, and cognitive computing. Additionally, it is a difficult undertaking that necessitates well-funded internal R&D and patent filing to integrate AI technology into already-existing systems. Even small mistakes can result in system failure or solution malfunction, which can have a significant impact on the result and intended results.

Offering Outlook

On the basis of offering, the AI infrastructure market is segmented into Hardware and Server Software. Hardware segment procured the highest revenue share in the AI infrastructure market in 2021. Processors, storage, memory, and interconnects are hardware components needed to create an AI infrastructure. Smaller, more effective, and more potent xeromorphic chip-based systems are anticipated to displace huge hardware devices in the upcoming years due to the rapid advancement of technology.



Technology Outlook

Based on technology, the AI infrastructure market is classified into Machine Learning and Deep Learning. Machine Learning segment registered the largest revenue share in the AI infrastructure market in 2021. It is because it aids in the development of new goods and provides businesses with a picture of trends in consumer behaviour and operational business patterns. A significant portion of the operations of numerous of today's top businesses, like Google, Facebook, and Uber, revolve around machine learning.

Function Outlook

By function, the AI infrastructure market is bifurcated into Training and Inference. Training segment registered a significant revenue share in the AI infrastructure market in 2021. The cloud is a great place to train algorithms because it gives users access to enormous data repositories across many servers. The more data an AI application evaluates during training, the more effective its algorithm is expected to become.

Deployment Type Outlook

On the basis of deployment, the AI infrastructure market is fragmented into On-premises, Cloud and Hybrid. The cloud deployment mode segment procured the highest revenue share in the AI infrastructure market in 2021. Reduced operational expenses, fuss-free deployment, high scalability, speedy data accessibility, quicker access to crucial data, and low capital requirements are just a few advantages of cloud deployment mode.

End-User Outlook

Based on end-user, the AI infrastructure market is categorized into Enterprises, Government Organizations and Cloud Service Providers. The enterprises segment procured a significant revenue share in the AI infrastructure market in 2021. Through the usage of artificial intelligence, numerous businesses around the world are finding new insights, revenue, and efficiencies (AI). Companies are also learning that by changing the way they approach their infrastructure, they may speed up their initiatives.

Regional Outlook

Region-wise, the AI infrastructure market is analyzed across North America, Europe, Asia Pacific and LAMEA. Asia Pacific registered a promising revenue share in the AI infrastructure market in 2021. The development of AI data centres in China is continuing to change as more domestic and international businesses switch to cloud service providers (CSPs) and co-location options. Due to companies looking for better connection and scalable solutions for their expanding enterprises, the need for AI data centres in the nation has surged.

Cardinal Matrix - AI Infrastructure Market Competition Analysis



The major strategies followed by the market participants are Acquisitions. Based on the Analysis presented in the Cardinal matrix; Google LLC is the forerunners in the AI Infrastructure Market. Companies such as Intel Corporation, Samsung Electronics Co., Ltd., IBM Corporation are some of the key innovators in AI Infrastructure Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Oracle Corporation, Intel Corporation, Samsung Electronics Co., Ltd. (Samsung Group), IBM Corporation, Google LLC, Amazon Web Services, Inc. (Amazon.com, Inc.), Hewlett-Packard Enterprise Company, Cisco Systems, Inc., Dell Technologies, Inc., and Toshiba Corporation.

Strategies deployed in AI Infrastructure Market

; Partnerships, Collaborations and Agreements:

  • Jul-2022: Google entered into a partnership with Northwell Health, the largest healthcare system in New York. This partnership aimed to use Google’s machine learning (ML), artificial intelligence (AI), and cloud capabilities. Additionally, the partnership is expected to escalate the health system’s digital transformation by utilizing cloud technology and artificial intelligence (AI), to enhance clinician experience, patient care, and operational efficiency.

; Product Launches and Product Expansions:

  • May-2021: Google Cloud announced Vertex AI, a new managed machine learning platform that is meant to make it easier for developers to deploy and maintain their AI models. it enables serious deployments for a new generation of AI that will empower data scientists and engineers to do fulfilling and creative work. Ultimately, our goal with Vertex is to reduce the time to ROI for these enterprises, to make sure that they cannot just build a model but get real value from the models they’re building.
  • Apr-2021: Intel released its most advanced artificial intelligence-based data center platform. This platform is expected to offer a substantial performance boost as compared with the previous generation, with an average 46% advancement on popular data center workloads.

; Acquisitions and Mergers:

  • Dec-2021: Oracle Corporation acquired Cerner Corporation, an American supplier of health information technology services, devices, and hardware. This acquisition aimed to assist Oracle to scale up its cloud business in the hospital and health system market.
  • Nov-2021: IBM today announced the acquisition of SXiQ, an Australian digital transformation services company specializing in cloud applications, cloud platforms and cloud cybersecurity. IBM's acquisition of SXiQ brings additional hybrid and multicloud expertise that is at the core of open innovation for clients. SXiQ will enhance IBM Consulting's capabilities in Australia and New Zealand to modernize applications and technology infrastructure in the cloud.
  • Jun-2021: Hewlett Packard Enterprise completed the acquisition of Determined AI, a San Francisco-based startup. This acquisition aimed to provide a strong and robust software stack to train AI models quicker, at any scale, utilizing its open source machine learning (ML) platform.
  • Jun-2021: IBM today announced the closing of its acquisition of Turbonomic, Inc., an Application Resource Management (ARM) and Network Performance Management (NPM) software provider based in Boston, MA. Now that Turbonomic is a part of our portfolio, IBM is the only company providing a one-stop shop of AI-powered automation capabilities, all built on Red Hat OpenShift to run anywhere.
  • Jan-2020: Samsung acquired TeleWorld Solutions, a strategic wireless engineering and consulting firm. This acquisition aimed to allow Samsung to fulfill mobile carriers’ increasing requirements for enhancing their 4G and 5G networks, and eventually develop new opportunities to improve its service capabilities to the customers.

; Business Expansion:

  • May-2021: Dell introduced the flagship Apex services brand. Under this expansion, Dell launched Apex Custom Solutions, Apex Data Storage Services, and the Apex Console. Apex Data Storage Services provides three performance tiers of the block along with file enterprise storage, and capacity starting as low as 50 terabytes.

Scope of the Study

Market Segments Covered in the Report:

By Offering

  • Hardware
  • Server Software

By End User

  • Cloud Service Providers
  • Enterprises
  • Government Organizations

By Deployment Type

  • On-premise
  • Hybrid
  • Cloud

By Function

  • Inference
  • Training

By Technology

  • Machine Learning
  • Deep Learning

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

  • Oracle Corporation
  • Intel Corporation
  • Samsung Electronics Co., Ltd. (Samsung Group)
  • IBM Corporation
  • Google LLC
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • Hewlett-Packard Enterprise Company
  • Cisco Systems, Inc.
  • Dell Technologies, Inc.
  • Toshiba Corporation

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Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global AI Infrastructure Market, by Offering
1.4.2 Global AI Infrastructure Market, by End User
1.4.3 Global AI Infrastructure Market, by Deployment Type
1.4.4 Global AI Infrastructure Market, by Function
1.4.5 Global AI Infrastructure Market, by Technology
1.4.6 Global AI Infrastructure Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.2.4 Business Expansions
3.3 Market Share Analysis, 2021
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.4.2 Key Strategic Move: (Acquisition and Mergers: 2018, Aug - 2021, Dec) Leading Players
Chapter 4. Global AI Infrastructure Market by Offering
4.1 Global Hardware Market by Region
4.2 Global Server Software Market by Region
Chapter 5. Global AI Infrastructure Market by End user
5.1 Global Cloud Service Providers Market by Region
5.2 Global Enterprises Market by Region
5.3 Global Government Organizations Market by Region
Chapter 6. Global AI Infrastructure Market by Deployment Type
6.1 Global On-premise Market by Region
6.2 Global Hybrid Market by Region
6.3 Global Cloud Market by Region
Chapter 7. Global AI Infrastructure Market by Function
7.1 Global Inference Market by Region
7.2 Global Training Market by Region
Chapter 8. Global AI Infrastructure Market by Technology
8.1 Global Machine Learning Market by Region
8.2 Global Deep Learning Market by Region
Chapter 9. Global AI Infrastructure Market by Region
9.1 North America AI Infrastructure Market
9.1.1 North America AI Infrastructure Market by Offering
9.1.1.1 North America Hardware Market by Country
9.1.1.2 North America Server Software Market by Country
9.1.2 North America AI Infrastructure Market by End user
9.1.2.1 North America Cloud Service Providers Market by Country
9.1.2.2 North America Enterprises Market by Country
9.1.2.3 North America Government Organizations Market by Country
9.1.3 North America AI Infrastructure Market by Deployment Type
9.1.3.1 North America On-premise Market by Country
9.1.3.2 North America Hybrid Market by Country
9.1.3.3 North America Cloud Market by Country
9.1.4 North America AI Infrastructure Market by Function
9.1.4.1 North America Inference Market by Country
9.1.4.2 North America Training Market by Country
9.1.5 North America AI Infrastructure Market by Technology
9.1.5.1 North America Machine Learning Market by Country
9.1.5.2 North America Deep Learning Market by Country
9.1.6 North America AI Infrastructure Market by Country
9.1.6.1 US AI Infrastructure Market
9.1.6.1.1 US AI Infrastructure Market by Offering
9.1.6.1.2 US AI Infrastructure Market by End user
9.1.6.1.3 US AI Infrastructure Market by Deployment Type
9.1.6.1.4 US AI Infrastructure Market by Function
9.1.6.1.5 US AI Infrastructure Market by Technology
9.1.6.2 Canada AI Infrastructure Market
9.1.6.2.1 Canada AI Infrastructure Market by Offering
9.1.6.2.2 Canada AI Infrastructure Market by End user
9.1.6.2.3 Canada AI Infrastructure Market by Deployment Type
9.1.6.2.4 Canada AI Infrastructure Market by Function
9.1.6.2.5 Canada AI Infrastructure Market by Technology
9.1.6.3 Mexico AI Infrastructure Market
9.1.6.3.1 Mexico AI Infrastructure Market by Offering
9.1.6.3.2 Mexico AI Infrastructure Market by End user
9.1.6.3.3 Mexico AI Infrastructure Market by Deployment Type
9.1.6.3.4 Mexico AI Infrastructure Market by Function
9.1.6.3.5 Mexico AI Infrastructure Market by Technology
9.1.6.4 Rest of North America AI Infrastructure Market
9.1.6.4.1 Rest of North America AI Infrastructure Market by Offering
9.1.6.4.2 Rest of North America AI Infrastructure Market by End user
9.1.6.4.3 Rest of North America AI Infrastructure Market by Deployment Type
9.1.6.4.4 Rest of North America AI Infrastructure Market by Function
9.1.6.4.5 Rest of North America AI Infrastructure Market by Technology
9.2 Europe AI Infrastructure Market
9.2.1 Europe AI Infrastructure Market by Offering
9.2.1.1 Europe Hardware Market by Country
9.2.1.2 Europe Server Software Market by Country
9.2.2 Europe AI Infrastructure Market by End user
9.2.2.1 Europe Cloud Service Providers Market by Country
9.2.2.2 Europe Enterprises Market by Country
9.2.2.3 Europe Government Organizations Market by Country
9.2.3 Europe AI Infrastructure Market by Deployment Type
9.2.3.1 Europe On-premise Market by Country
9.2.3.2 Europe Hybrid Market by Country
9.2.3.3 Europe Cloud Market by Country
9.2.4 Europe AI Infrastructure Market by Function
9.2.4.1 Europe Inference Market by Country
9.2.4.2 Europe Training Market by Country
9.2.5 Europe AI Infrastructure Market by Technology
9.2.5.1 Europe Machine Learning Market by Country
9.2.5.2 Europe Deep Learning Market by Country
9.2.6 Europe AI Infrastructure Market by Country
9.2.6.1 Germany AI Infrastructure Market
9.2.6.1.1 Germany AI Infrastructure Market by Offering
9.2.6.1.2 Germany AI Infrastructure Market by End user
9.2.6.1.3 Germany AI Infrastructure Market by Deployment Type
9.2.6.1.4 Germany AI Infrastructure Market by Function
9.2.6.1.5 Germany AI Infrastructure Market by Technology
9.2.6.2 UK AI Infrastructure Market
9.2.6.2.1 UK AI Infrastructure Market by Offering
9.2.6.2.2 UK AI Infrastructure Market by End user
9.2.6.2.3 UK AI Infrastructure Market by Deployment Type
9.2.6.2.4 UK AI Infrastructure Market by Function
9.2.6.2.5 UK AI Infrastructure Market by Technology
9.2.6.3 France AI Infrastructure Market
9.2.6.3.1 France AI Infrastructure Market by Offering
9.2.6.3.2 France AI Infrastructure Market by End user
9.2.6.3.3 France AI Infrastructure Market by Deployment Type
9.2.6.3.4 France AI Infrastructure Market by Function
9.2.6.3.5 France AI Infrastructure Market by Technology
9.2.6.4 Russia AI Infrastructure Market
9.2.6.4.1 Russia AI Infrastructure Market by Offering
9.2.6.4.2 Russia AI Infrastructure Market by End user
9.2.6.4.3 Russia AI Infrastructure Market by Deployment Type
9.2.6.4.4 Russia AI Infrastructure Market by Function
9.2.6.4.5 Russia AI Infrastructure Market by Technology
9.2.6.5 Spain AI Infrastructure Market
9.2.6.5.1 Spain AI Infrastructure Market by Offering
9.2.6.5.2 Spain AI Infrastructure Market by End user
9.2.6.5.3 Spain AI Infrastructure Market by Deployment Type
9.2.6.5.4 Spain AI Infrastructure Market by Function
9.2.6.5.5 Spain AI Infrastructure Market by Technology
9.2.6.6 Italy AI Infrastructure Market
9.2.6.6.1 Italy AI Infrastructure Market by Offering
9.2.6.6.2 Italy AI Infrastructure Market by End user
9.2.6.6.3 Italy AI Infrastructure Market by Deployment Type
9.2.6.6.4 Italy AI Infrastructure Market by Function
9.2.6.6.5 Italy AI Infrastructure Market by Technology
9.2.6.7 Rest of Europe AI Infrastructure Market
9.2.6.7.1 Rest of Europe AI Infrastructure Market by Offering
9.2.6.7.2 Rest of Europe AI Infrastructure Market by End user
9.2.6.7.3 Rest of Europe AI Infrastructure Market by Deployment Type
9.2.6.7.4 Rest of Europe AI Infrastructure Market by Function
9.2.6.7.5 Rest of Europe AI Infrastructure Market by Technology
9.3 Asia Pacific AI Infrastructure Market
9.3.1 Asia Pacific AI Infrastructure Market by Offering
9.3.1.1 Asia Pacific Hardware Market by Country
9.3.1.2 Asia Pacific Server Software Market by Country
9.3.2 Asia Pacific AI Infrastructure Market by End user
9.3.2.1 Asia Pacific Cloud Service Providers Market by Country
9.3.2.2 Asia Pacific Enterprises Market by Country
9.3.2.3 Asia Pacific Government Organizations Market by Country
9.3.3 Asia Pacific AI Infrastructure Market by Deployment Type
9.3.3.1 Asia Pacific On-premise Market by Country
9.3.3.2 Asia Pacific Hybrid Market by Country
9.3.3.3 Asia Pacific Cloud Market by Country
9.3.4 Asia Pacific AI Infrastructure Market by Function
9.3.4.1 Asia Pacific Inference Market by Country
9.3.4.2 Asia Pacific Training Market by Country
9.3.5 Asia Pacific AI Infrastructure Market by Technology
9.3.5.1 Asia Pacific Machine Learning Market by Country
9.3.5.2 Asia Pacific Deep Learning Market by Country
9.3.6 Asia Pacific AI Infrastructure Market by Country
9.3.6.1 China AI Infrastructure Market
9.3.6.1.1 China AI Infrastructure Market by Offering
9.3.6.1.2 China AI Infrastructure Market by End user
9.3.6.1.3 China AI Infrastructure Market by Deployment Type
9.3.6.1.4 China AI Infrastructure Market by Function
9.3.6.1.5 China AI Infrastructure Market by Technology
9.3.6.2 Japan AI Infrastructure Market
9.3.6.2.1 Japan AI Infrastructure Market by Offering
9.3.6.2.2 Japan AI Infrastructure Market by End user
9.3.6.2.3 Japan AI Infrastructure Market by Deployment Type
9.3.6.2.4 Japan AI Infrastructure Market by Function
9.3.6.2.5 Japan AI Infrastructure Market by Technology
9.3.6.3 India AI Infrastructure Market
9.3.6.3.1 India AI Infrastructure Market by Offering
9.3.6.3.2 India AI Infrastructure Market by End user
9.3.6.3.3 India AI Infrastructure Market by Deployment Type
9.3.6.3.4 India AI Infrastructure Market by Function
9.3.6.3.5 India AI Infrastructure Market by Technology
9.3.6.4 South Korea AI Infrastructure Market
9.3.6.4.1 South Korea AI Infrastructure Market by Offering
9.3.6.4.2 South Korea AI Infrastructure Market by End user
9.3.6.4.3 South Korea AI Infrastructure Market by Deployment Type
9.3.6.4.4 South Korea AI Infrastructure Market by Function
9.3.6.4.5 South Korea AI Infrastructure Market by Technology
9.3.6.5 Singapore AI Infrastructure Market
9.3.6.5.1 Singapore AI Infrastructure Market by Offering
9.3.6.5.2 Singapore AI Infrastructure Market by End user
9.3.6.5.3 Singapore AI Infrastructure Market by Deployment Type
9.3.6.5.4 Singapore AI Infrastructure Market by Function
9.3.6.5.5 Singapore AI Infrastructure Market by Technology
9.3.6.6 Malaysia AI Infrastructure Market
9.3.6.6.1 Malaysia AI Infrastructure Market by Offering
9.3.6.6.2 Malaysia AI Infrastructure Market by End user
9.3.6.6.3 Malaysia AI Infrastructure Market by Deployment Type
9.3.6.6.4 Malaysia AI Infrastructure Market by Function
9.3.6.6.5 Malaysia AI Infrastructure Market by Technology
9.3.6.7 Rest of Asia Pacific AI Infrastructure Market
9.3.6.7.1 Rest of Asia Pacific AI Infrastructure Market by Offering
9.3.6.7.2 Rest of Asia Pacific AI Infrastructure Market by End user
9.3.6.7.3 Rest of Asia Pacific AI Infrastructure Market by Deployment Type
9.3.6.7.4 Rest of Asia Pacific AI Infrastructure Market by Function
9.3.6.7.5 Rest of Asia Pacific AI Infrastructure Market by Technology
9.4 LAMEA AI Infrastructure Market
9.4.1 LAMEA AI Infrastructure Market by Offering
9.4.1.1 LAMEA Hardware Market by Country
9.4.1.2 LAMEA Server Software Market by Country
9.4.2 LAMEA AI Infrastructure Market by End user
9.4.2.1 LAMEA Cloud Service Providers Market by Country
9.4.2.2 LAMEA Enterprises Market by Country
9.4.2.3 LAMEA Government Organizations Market by Country
9.4.3 LAMEA AI Infrastructure Market by Deployment Type
9.4.3.1 LAMEA On-premise Market by Country
9.4.3.2 LAMEA Hybrid Market by Country
9.4.3.3 LAMEA Cloud Market by Country
9.4.4 LAMEA AI Infrastructure Market by Function
9.4.4.1 LAMEA Inference Market by Country
9.4.4.2 LAMEA Training Market by Country
9.4.5 LAMEA AI Infrastructure Market by Technology
9.4.5.1 LAMEA Machine Learning Market by Country
9.4.5.2 LAMEA Deep Learning Market by Country
9.4.6 LAMEA AI Infrastructure Market by Country
9.4.6.1 Brazil AI Infrastructure Market
9.4.6.1.1 Brazil AI Infrastructure Market by Offering
9.4.6.1.2 Brazil AI Infrastructure Market by End user
9.4.6.1.3 Brazil AI Infrastructure Market by Deployment Type
9.4.6.1.4 Brazil AI Infrastructure Market by Function
9.4.6.1.5 Brazil AI Infrastructure Market by Technology
9.4.6.2 Argentina AI Infrastructure Market
9.4.6.2.1 Argentina AI Infrastructure Market by Offering
9.4.6.2.2 Argentina AI Infrastructure Market by End user
9.4.6.2.3 Argentina AI Infrastructure Market by Deployment Type
9.4.6.2.4 Argentina AI Infrastructure Market by Function
9.4.6.2.5 Argentina AI Infrastructure Market by Technology
9.4.6.3 UAE AI Infrastructure Market
9.4.6.3.1 UAE AI Infrastructure Market by Offering
9.4.6.3.2 UAE AI Infrastructure Market by End user
9.4.6.3.3 UAE AI Infrastructure Market by Deployment Type
9.4.6.3.4 UAE AI Infrastructure Market by Function
9.4.6.3.5 UAE AI Infrastructure Market by Technology
9.4.6.4 Saudi Arabia AI Infrastructure Market
9.4.6.4.1 Saudi Arabia AI Infrastructure Market by Offering
9.4.6.4.2 Saudi Arabia AI Infrastructure Market by End user
9.4.6.4.3 Saudi Arabia AI Infrastructure Market by Deployment Type
9.4.6.4.4 Saudi Arabia AI Infrastructure Market by Function
9.4.6.4.5 Saudi Arabia AI Infrastructure Market by Technology
9.4.6.5 South Africa AI Infrastructure Market
9.4.6.5.1 South Africa AI Infrastructure Market by Offering
9.4.6.5.2 South Africa AI Infrastructure Market by End user
9.4.6.5.3 South Africa AI Infrastructure Market by Deployment Type
9.4.6.5.4 South Africa AI Infrastructure Market by Function
9.4.6.5.5 South Africa AI Infrastructure Market by Technology
9.4.6.6 Nigeria AI Infrastructure Market
9.4.6.6.1 Nigeria AI Infrastructure Market by Offering
9.4.6.6.2 Nigeria AI Infrastructure Market by End user
9.4.6.6.3 Nigeria AI Infrastructure Market by Deployment Type
9.4.6.6.4 Nigeria AI Infrastructure Market by Function
9.4.6.6.5 Nigeria AI Infrastructure Market by Technology
9.4.6.7 Rest of LAMEA AI Infrastructure Market
9.4.6.7.1 Rest of LAMEA AI Infrastructure Market by Offering
9.4.6.7.2 Rest of LAMEA AI Infrastructure Market by End user
9.4.6.7.3 Rest of LAMEA AI Infrastructure Market by Deployment Type
9.4.6.7.4 Rest of LAMEA AI Infrastructure Market by Function
9.4.6.7.5 Rest of LAMEA AI Infrastructure Market by Technology
Chapter 10. Company Profiles
10.1 Oracle Corporation
10.1.1 Company Overview
10.1.2 Financial Analysis
10.1.3 Segmental and Regional Analysis
10.1.4 Research & Development Expense
10.1.5 Recent strategies and developments:
10.1.5.1 Acquisition and Mergers:
10.1.6 SWOT Analysis
10.2 Intel Corporation
10.2.1 Company Overview
10.2.2 Financial Analysis
10.2.3 Segmental and Regional Analysis
10.2.4 Research & Development Expenses
10.2.5 Recent strategies and developments:
10.2.5.1 Product Launches and Product Expansions:
10.2.5.2 Acquisition and Mergers:
10.2.6 SWOT Analysis
10.3 Samsung Electronics Co., Ltd. (Samsung Group)
10.3.1 Company Overview
10.3.2 Financial Analysis
10.3.3 Segmental and Regional Analysis
10.3.4 Research & Development Expense
10.3.5 Recent strategies and developments:
10.3.5.1 Acquisition and Mergers:
10.3.6 SWOT Analysis
10.4 IBM Corporation
10.4.1 Company Overview
10.4.2 Financial Analysis
10.4.3 Regional & Segmental Analysis
10.4.4 Research & Development Expenses
10.4.5 Recent strategies and developments:
10.4.5.1 Acquisition and Mergers:
10.4.6 SWOT Analysis
10.5 Google LLC
10.5.1 Company Overview
10.5.2 Financial Analysis
10.5.3 Segmental and Regional Analysis
10.5.4 Research & Development Expense
10.5.5 Recent strategies and developments:
10.5.5.1 Partnerships, Collaborations, and Agreements:
10.5.5.2 Product Launches and Product Expansions:
10.5.6 SWOT Analysis
10.6 Amazon Web Services, Inc. (Amazon.com, Inc.)
10.6.1 Company Overview
10.6.2 Financial Analysis
10.6.3 Segmental Analysis
10.6.4 SWOT Analysis
10.7 Hewlett Packard Enterprise Company
10.7.1 Company Overview
10.7.2 Financial Analysis
10.7.3 Segmental and Regional Analysis
10.7.4 Research & Development Expense
10.7.5 Recent strategies and developments:
10.7.5.1 Acquisition and Mergers:
10.7.6 SWOT Analysis
10.8 Cisco Systems, Inc.
10.8.1 Company Overview
10.8.2 Financial Analysis
10.8.3 Regional Analysis
10.8.4 Research & Development Expense
10.8.5 SWOT Analysis
10.9 Dell Technologies, Inc.
10.9.1 Company Overview
10.9.2 Financial Analysis
10.9.3 Segmental and Regional Analysis
10.9.4 Research & Development Expense
10.9.5 Recent strategies and developments:
10.9.5.1 Acquisition and Mergers:
10.9.5.2 Business Expansions:
10.9.6 SWOT Analysis:
10.10. Toshiba Corporation
10.10.1 Company Overview
10.10.2 Financial Analysis
10.10.3 Segmental and Regional Analysis
10.10.4 Research and Development Expense
10.10.5 SWOT Analysis

Companies Mentioned

  • Oracle Corporation
  • Intel Corporation
  • Samsung Electronics Co., Ltd. (Samsung Group)
  • IBM Corporation
  • Google LLC
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • Hewlett-Packard Enterprise Company
  • Cisco Systems, Inc.
  • Dell Technologies, Inc.
  • Toshiba Corporation

Methodology

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