AI Infrastructure Market by Offering, Deployment, End-Users

List of Tables

[199 Pages Report] The AI Infrastructure Market size was estimated at USD 36.52 billion in 2023 and expected to reach USD 45.11 billion in 2024, at a CAGR 24.08% to reach USD 165.40 billion by 2030.

The AI infrastructure market refers to the ecosystem of hardware, software, and services that support the deployment, scaling, and management of artificial intelligence (AI) applications and machine learning (ML) models for various end-use industries. The AI infrastructure includes specialized processors such as GPUs, TPUs, ASICs, memory and storage solutions, networking equipment, software platforms for model training, and consulting services to facilitate AI adoption. The increasing need for high-performance computing platforms to process large datasets and the rising edge-to-cloud AI infrastructure worldwide are surging the demand for AI Infrastructure solutions. Additionally, the government initiatives promoting smart manufacturing and Industry 4.0 facilities contribute to market growth. However, the design complexities, deployment, and maintenance issues may limit the adoption of AI infrastructure solutions. The vulnerability to cyberattacks and data breach incidents poses challenges to the market. Moreover, the technological advancements and integration of AI infrastructure with 5G technology is expected to facilitate a new era of ultra-low latency and high-bandwidth applications, opening up additional opportunities for the market.

KEY MARKET STATISTICS
Base Year [2023]	USD 36.52 billion
Estimated Year [2024]	USD 45.11 billion
Forecast Year [2030]	USD 165.40 billion
CAGR (%)	24.08%

Offering: Innovative solution and services catering to specific needs of the AI ecosystem

The AI hardware, such as specialized processors and high-speed & scalable storage solutions, are crucial for efficient AI model training and inference performance. Organizations with demanding computational requirements prefer CPU & GPU-based systems due to their parallel processing capabilities that provide shorter training times for machine learning models. Services in AI infrastructure include consulting support on deploying AI solutions, ensuring maintainability & scalability model management services for monitoring performance. The training models using cloud-based infrastructures are implemented to maximize resource utilization. Data labeling & annotation services are essential for supervised learning algorithms to maintain privacy & security standards. A diverse range of software tools, such as frameworks, data preparation tools, and model deployment platforms, are available for designing, developing, and deploying AI solutions to provide a high-level interface for complex operations.

Deployment: Increasing utilization of the cloud-based AI infrastructure focusing on the agility and swift deployment of AI-powered services

Cloud-based AI infrastructure offers a flexible and scalable solution that allows organizations to access advanced AI capabilities without the need for large-scale investments in hardware and maintenance. Hybrid AI infrastructure combines the advantages of cloud and on-premise solutions, enabling organizations to optimize their deployments based on specific requirements while maintaining control over sensitive data. On-premise deployment is preferred over cloud-based solutions when organizations require maximum control over their AI infrastructure or have stringent security requirements.

End-Users: Rising deployment of the AI infrastructure into the enterprises and Government entities

Cloud Service Providers (CSPs) provide seamless and scalable AI infrastructures as they cater to a wide range of clients with varying demands for processing power and storage capabilities. Enterprises across various industries leverage AI infrastructure for purposes such as data analytics, automation, and customer service improvement through chatbots and virtual assistants to select a suitable AI infrastructure solution. Government entities utilize AI infrastructure for various applications such as public safety, healthcare systems management, and traffic management, among others, for enhanced security & compliance, cost-effectiveness, and interoperability.

Regional Insights

The Americas represent a highly developed infrastructure with significant growth in investments associated with AI research and development and the presence of significant global market players. The United States, Canada, and Mexico are major countries with rising consumer demands, boosting the adoption of AI infrastructure solutions. In the European Union, countries such as France and Germany are spearheading efforts to increase investments in research and development to develop AI technology. Government initiatives and policies play an essential role in driving AI adoption across various industries in the Asia-Pacific region. Governments in countries including China, Japan, and India have recognized the importance of AI for future economic growth and are heavily investing in research and development (R&D) programs to boost innovation. Additionally, the thriving startup ecosystem contributes significantly to the market growth.

FPNV Positioning Matrix

The FPNV Positioning Matrix is pivotal in evaluating the AI Infrastructure Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the AI Infrastructure Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Key Company Profiles

The report delves into recent significant developments in the AI Infrastructure Market, highlighting leading vendors and their innovative profiles. These include Accenture PLC, Advanced Micro Devices Inc., Amazon Web Services, Inc., Appinventiv Technology Pvt. Ltd., Cerebras Systems, Cisco Systems, Inc., DataRobot, Inc., Fortinet, Inc., G-Core Labs S.A., Google LLC by Alphabet Inc., Graphcore Limited, Groq, Inc., Hailo Technologies Ltd., Hewlett Packard Enterprise Development LP, Huawei Technologies Co., Ltd., Intel Corporation, International Business Machines Corporation, Lenovo Group Limited, Lightmatter, Inc., Meta Platforms, Inc., Micron Technology Inc., Microsoft Corporation, Mythic, Inc., NEC Corporation, Nutanix, Inc., NVIDIA Corporation, OpenAI OpCo, LLC, Oracle Corporation, Pure Storage, Inc., Salesforce, Inc., SambaNova Systems, Inc, Samsung Electronics Co., Ltd., SAP SE, SenseTime Group Inc., Siemens AG, Sony Group Corporation, Synopsys Inc., and Toshiba Corporation.

Market Segmentation & Coverage

This research report categorizes the AI Infrastructure Market to forecast the revenues and analyze trends in each of the following sub-markets:

Offering
- Hardware
  - CPU & GPU
  - Memory & Storage
  - Networking Equipment

Services
- Data Ingestion & Integration
- Data Preprocessing & Feature Engineering
- Data Storage & Management
- Machine Learning Frameworks & Libraries
- Model Deployment & Serving
- Model Training & Validation
- Monitoring & Maintenance
- Security & Compliance

Software

Deployment
- On-Cloud
- On-Premise

End-Users
- Cloud Service Providers
- Enterprises
- Government

Region
- Americas
  - Argentina
  - Brazil
  - Canada
  - Mexico
  - United States
    - California
    - Florida
    - Illinois
    - New York
    - Ohio
    - Pennsylvania
    - Texas
- Asia-Pacific
  - Australia
  - China
  - India
  - Indonesia
  - Japan
  - Malaysia
  - Philippines
  - Singapore
  - South Korea
  - Taiwan
  - Thailand
  - Vietnam

Europe, Middle East & Africa
- Denmark
- Egypt
- Finland
- France
- Germany
- Israel
- Italy
- Netherlands
- Nigeria
- Norway
- Poland
- Qatar
- Russia
- Saudi Arabia
- South Africa
- Spain
- Sweden
- Switzerland
- Turkey
- United Arab Emirates
- United Kingdom

The report offers valuable insights on the following aspects:

1. Market Penetration: It presents comprehensive information on the market provided by key players.

2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.

3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.

4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.

5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.

The report addresses key questions such as:

1. What is the market size and forecast of the AI Infrastructure Market?

2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the AI Infrastructure Market?

3. What are the technology trends and regulatory frameworks in the AI Infrastructure Market?

4. What is the market share of the leading vendors in the AI Infrastructure Market?

5. Which modes and strategic moves are suitable for entering the AI Infrastructure Market?

Product Code: MRR-B16853776AD5

1. Preface

1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders

2. Research Methodology

2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

5.1. Market Dynamics
- 5.1.1. Drivers
  - 5.1.1.1. Need for high-performance computing platforms to process large datasets
  - 5.1.1.2. Government initiatives promoting smart manufacturing and industry 4.0 facilities
  - 5.1.1.3. Rise of edge-to-cloud AI infrastructure worldwide
- 5.1.2. Restraints
  - 5.1.2.1. Complexity of designing, deploying, and maintaining AI infrastructure
- 5.1.3. Opportunities
  - 5.1.3.1. New technological integration and advancements in AI infrastructure
  - 5.1.3.2. Emerging 5G network deployment in AI infrastructure
- 5.1.4. Challenges
  - 5.1.4.1. Vulnerability to cyberattacks and data breaches
5.2. Market Segmentation Analysis
- 5.2.1. Offering: Innovative solution and services catering to specific needs of the AI ecosystem
- 5.2.2. Deployment: Increasing utilization of the cloud-based AI infrastructure focusing on the agility and swift deployment of AI-powered services
- 5.2.3. End-Users: Rising deployment of the AI infrastructure into the enterprises and Government entities
5.3. Market Trend Analysis
- 5.3.1. Strong presence of experienced AI infrastructure technology providers and research institutes with an enormous number of patent registrations in the Americas
- 5.3.2. Government initiatives and rising penetration of global tech vendors are shaping the future of AI infrastructure in the APAC region
- 5.3.3. Emphasized regulation and standards for AI deployment and advancing AI governance across EMEA
5.4. Cumulative Impact of High Inflation
5.5. Porter's Five Forces Analysis
- 5.5.1. Threat of New Entrants
- 5.5.2. Threat of Substitutes
- 5.5.3. Bargaining Power of Customers
- 5.5.4. Bargaining Power of Suppliers
- 5.5.5. Industry Rivalry
5.6. Value Chain & Critical Path Analysis
5.7. Regulatory Framework Analysis

6. AI Infrastructure Market, by Offering

6.1. Introduction
6.2. Hardware
6.3. Services
6.4. Software

7. AI Infrastructure Market, by Deployment

7.1. Introduction
7.2. On-Cloud
7.3. On-Premise

8. AI Infrastructure Market, by End-Users

8.1. Introduction
8.2. Cloud Service Providers
8.3. Enterprises
8.4. Government

9. Americas AI Infrastructure Market

9.1. Introduction
9.2. Argentina
9.3. Brazil
9.4. Canada
9.5. Mexico
9.6. United States

10. Asia-Pacific AI Infrastructure Market

10.1. Introduction
10.2. Australia
10.3. China
10.4. India
10.5. Indonesia
10.6. Japan
10.7. Malaysia
10.8. Philippines
10.9. Singapore
10.10. South Korea
10.11. Taiwan
10.12. Thailand
10.13. Vietnam

11. Europe, Middle East & Africa AI Infrastructure Market

11.1. Introduction
11.2. Denmark
11.3. Egypt
11.4. Finland
11.5. France
11.6. Germany
11.7. Israel
11.8. Italy
11.9. Netherlands
11.10. Nigeria
11.11. Norway
11.12. Poland
11.13. Qatar
11.14. Russia
11.15. Saudi Arabia
11.16. South Africa
11.17. Spain
11.18. Sweden
11.19. Switzerland
11.20. Turkey
11.21. United Arab Emirates
11.22. United Kingdom

12. Competitive Landscape

12.1. Market Share Analysis, 2023
12.2. FPNV Positioning Matrix, 2023
12.3. Competitive Scenario Analysis
- 12.3.1. Saudi Arabia Partners with China to Create Arabic-based AI System
- 12.3.2. AMD to Acquire Open-Source AI Software Expert Nod.ai
- 12.3.3. SambaNova Unveils the SN40L, Powering its Full Stack AI Platform
- 12.3.4. EY Announces Launch of Artificial Intelligence Platform EY.ai Following USD 1.4 Billion Investment
- 12.3.5. Partnership to Launch UAE as the World's First AI Nation
- 12.3.6. Jio Platforms Ties up with NVIDIA to Build Cloud-based AI Infrastructure
- 12.3.7. Tata Partners With NVIDIA to Build Large-Scale AI Infrastructure
- 12.3.8. Microsoft Expands UAE's G42 Partnership to Include Cloud, AI Tools
- 12.3.9. Google Cloud and NVIDIA Expand Partnership to Advance AI Computing, Software and Services
- 12.3.10. Contextual AI and Google Cloud Partner to Bring Generative AI to the Enterprise
- 12.3.11. Nutanix Simplifies Adoption of Generative AI with New Nutanix GPT-in-a-Box Solution
- 12.3.12. VAST Data Launches Unified Data Platform for the Age of AI
- 12.3.13. AMD Announces Plan to Invest USD 135 Million to Expand Adaptive Computing Research, Development and Engineering Operations in Ireland
- 12.3.14. Lenovo to Invest USD 1 Billion over 3 Years on Expansion and Optimisation of AI Infrastructure
- 12.3.15. Hewlett Packard Enterprise acquires Pachyderm to expand AI-at-scale capabilities with reproducible AI

13. Competitive Portfolio

13.1. Key Company Profiles
13.2. Key Product Portfolio