AI Infrastructure Market Size was valued at USD 36.14 billion in 2022 and is expected to reach USD 222.42 billion by 2030, and grow at a CAGR of 25.5% over the forecast period 2023-2030.
AI infrastructure refers to the platforms on which organisations can build intelligent applications that are predictive, self-healing, and require minimal human intervention. New age technologies such as IoT, Mobility, and Big Data are putting a strain on IT infrastructure. The need for intelligent infrastructure to harness the power of AI platforms is more apparent than ever.
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Every stage of the machine learning workflow is covered by AI infrastructure. It enables data engineers, data scientists, DevOps teams, and software engineers to manage and access computing resources for training, deploying, and testing artificial intelligence algorithms. Using AI infrastructure, the workload is mapped to the appropriate configuration of virtual machines and servers. Organizations can use AI infrastructure to work on capacity planning, storage management, resource utilisation, anomaly detection, threat detection, and analysis.
KEY DRIVERS:
Cloud machine learning platform adoption is increasing.
Increasing data traffic necessitates the use of powerful computing resources.
Increasing cross-industry collaborations and partnerships.
RESTRAINTS:
A scarcity of AI hardware experts and skilled workforce.
OPPORTUNITIES:
AI-based tools for elderly care have a growing potential.
FPGA-based accelerators are in high demand.
CHALLENGES:
AI algorithm unreliability
Concerns about data privacy in AI platforms.
During the COVID-19 pandemic, digital transformation using artificial intelligence and hybrid cloud is widely used. During quarantine, a new internet infrastructure procedure was critical in supporting retail supply chains. Companies are shifting their investments in order to capitalise on the opportunity provided by new infrastructure, and they are being flexible and open-minded in their approach. The pandemic is expected to have a negative impact on the global AI Infrastructure market overall.
Based on Offering, the AI infrastructure market is segmented into Hardware, and Software. To keep up with the increasing amount of data generated by applications, advanced AI solutions require new software and hardware on a regular basis. These AI-based solutions, for example, require updates around annotation and collation of data sources, as well as accessible creating, processing, and fine-tuning models as newer data becomes available. AI technology, particularly deep learning, has become one of the most important computational workloads for organisations, and its use will increase.
Based on Deployment, the AI infrastructure market is segmented into On-Premises, Cloud, and Hybrid. During the forecast period, the hybrid deployment model has the second largest market share in the AI infrastructure market. Because of the increased agility of a hybrid cloud, it is widely accepted by enterprises seeking a competitive advantage. Organizations in the automotive, healthcare, and industrial sectors have begun to use hybrid infrastructure, which combines various technologies and methodologies such as virtualization, private clouds, and other internal IT resources.
Based on Technology, the AI infrastructure market is segmented into Deep Learning, and Machine Learning. Based on function, the AI infrastructure market is segmented into Inference, and Training. Based on end-user, the AI infrastructure market is segmented into Government Organizations, Cloud Service Providers, and Enterprises.
BY OFFERING
Hardware
Software
BY TECHNOLOGY
Deep Learning
Machine Learning
BY DEPLOYMENT
On-premises
Cloud
Hybrid
BY FUNCTION
Inference
Training
BY END USER
Government Organizations
Cloud Service Providers
Enterprises
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The Asia Pacific market has the largest market share and the highest growth rate, and it is expected to maintain its position during the forecast period. The presence of the most populous countries, such as China and India, accounts for the rapid growth.
China's market has the largest market share and the highest growth rate among APAC countries, and it is expected to maintain its position during the forecast period. China's AI infrastructure market is rapidly expanding. The growth of AI data centres in China continues to evolve as multinational and domestic enterprises increasingly shift to cloud service providers (CSPs) and co-location solutions. The country's demand for AI data centres has increased due to organisations seeking improved connectivity and scalable solutions for their expanding businesses.
India is one of the world's fastest-growing economies, with a keen interest in the global development of artificial intelligence. The Indian government recognises the potential and is taking all necessary steps to steer the country and position it among the leaders in artificial intelligence. Despite a favourable ecosystem, the government is attempting to overcome obstacles in order to achieve rapid progress in AI. Similarly, the Chinese government is hastening the construction of new infrastructure projects such as 5G networks and data centres, which will improve information services for the rapidly expanding market.
North America
USA
Canada
Mexico
Europe
Germany
UK
France
Italy
Spain
The Netherlands
Rest of Europe
Asia-Pacific
Japan
south Korea
China
India
Australia
Rest of Asia-Pacific
The Middle East & Africa
Israel
UAE
South Africa
Rest of Middle East & Africa
Latin America
Brazil
Argentina
Rest of Latin America
The key players in the AI infrastructure market are Amazon Web Services, Google LLC, IBM Corporation, Microsoft Corporation, Oracle Corporation, Cisco Systems Inc., Intel Corporation, Micron Technology Inc., Nvidia Corporation and Samsung Electronics.
Google LLC-Company Financial Analysis
| Report Attributes | Details |
|---|---|
| Market Size in 2022 | US$ 36.14 Billion |
| Market Size by 2030 | US$ 222.42 Billion |
| CAGR | CAGR of 25.5% From 2023 to 2030 |
| Base Year | 2022 |
| Forecast Period | 2023-2030 |
| Historical Data | 2020-2021 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Product (Lighting Controls, Hvac Controls, Surveillance Products, Access Controls) • By Standard (Wi Fi And Infrared, En Ocean, Bac Net, Z Wave, Zigbee, Dali, Knx) |
| Regional Analysis/Coverage | North America (USA, Canada, Mexico), Europe (Germany, UK, France, Italy, Spain, Netherlands, Rest of Europe), Asia-Pacific (Japan, South Korea, China, India, Australia, Rest of Asia-Pacific), The Middle East & Africa (Israel, UAE, South Africa, Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America) |
| Company Profiles | Amazon Web Services, Google LLC, IBM Corporation, Microsoft Corporation, Oracle Corporation, Cisco Systems Inc., Intel Corporation, Micron Technology Inc., Nvidia Corporation and Samsung Electronics. |
| Key Drivers | • Cloud machine learning platform adoption is increasing. • Increasing data traffic necessitates the use of powerful computing resources. |
| RESTRAINTS | • A scarcity of AI hardware experts and skilled workforce. |
The market value is expected to reach USD 222.42 billion by 2030.
The market has been segmented with respect to offering, technology, deployment, function and end-user.
Asian pacific region is expected to dominate the AI infrastructure Market.
Yes, and they are Raw material vendors, Distributors/traders/wholesalers/suppliers, Regulatory authorities, including government agencies and NGO, Commercial research & development (R&D) institutions, Importers and exporters, Government organizations, research organizations, and consulting firms, Trade/Industrial associations, End-use industries.
Manufacturers, Consultants, Association, Research Institutes, private and university libraries, suppliers, and distributors of the product.
Table of Content:
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Research Methodology
3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges
4. Impact Analysis
4.1 COVID-19 Impact Analysis
4.2 Impact of Ukraine- Russia war
4.3 Impact of ongoing Recession
4.3.1 Introduction
4.3.2 Impact on major economies
4.3.2.1 US
4.3.2.2 Canada
4.3.2.3 Germany
4.3.2.4 France
4.3.2.5 United Kingdom
4.3.2.6 China
4.3.2.7 Japan
4.3.2.8 South Korea
4.3.2.9 Rest of the World
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. AI infrastructure Market Segmentation, by offering
8.1Introduction
8.2 Hardware
8.3 Software
9. AI infrastructure Market Segmentation, by equipment technology
9.1Introduction
9.2 Deep Learning
9.3 Machine Learning
10. AI infrastructure Market Segmentation, by deployment
10.1 Introduction
10.2 On-premises
10.3 Cloud
10.4 Hybrid
11. AI infrastructure Market Segmentation, by function
11.1 Introduction
11.2 Inference
11.3 Training
12. AI infrastructure Market Segmentation, by end-user
12.1 Introduction
12.2 Government Organizations
12.3 Cloud Service Providers
12.4 Enterprises
13. Regional Analysis
13.1 Introduction
13.2 North America
13.2.1 USA
13.2.2 Canada
13.2.3 Mexico
13.3 Europe
13.3.1 Germany
13.3.2 UK
13.3.3 France
13.3.4 Italy
13.3.5 Spain
13.3.6 The Netherlands
13.3.7 Rest of Europe
13.4 Asia-Pacific
13.4.1 Japan
13.4.2 South Korea
13.4.3 China
13.4.4 India
13.4.5 Australia
13.4.6 Rest of Asia-Pacific
13.5 The Middle East & Africa
13.5.1 Israel
13.5.2 UAE
13.5.3 South Africa
13.5.4 Rest
13.6 Latin America
13.6.1 Brazil
13.6.2 Argentina
13.6.3 Rest of Latin America
14. Company Profiles
14.1 IBM Corporation
14.1.1 Financial
14.1.2 Products/ Services Offered
14.1.3 SWOT Analysis
14.1.4 The SNS view
14.2 Amazon Web Services
14.3 Google LLC
14.4 Microsoft Corporation
14.5 Oracle Corporation
14.6 Cisco Systems Inc.
14.7 Intel Corporation
14.8 Micron Technology Inc.
14.9 Nvidia Corporation
14.10 Samsung Electronics
15. Competitive Landscape
15.1 Competitive Benchmark
15.2 Market Share analysis
15.3 Recent Developments
16. Conclusion
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