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Global Artificial Intelligence (AI) Infrastructure Market – Industry Trends and Forecast to 2029

  • ICT
  • Upcoming Report
  • May 2022
  • Global
  • 350 Pages
  • No of Tables: 220
  • No of Figures: 60

Global Artificial Intelligence (AI) Infrastructure Market, By Offering (Hardware, Software), Technology (Machine Learning, Deep Learning), Function (Training and Inference), Deployment Type (On-Premises, Cloud, Hybrid), End-User (Enterprises, Government Organizations, Cloud Service Provider) - Industry Trends and Forecast to 2029

AI Infrastructure Market

Market Analysis and Size

Artificial Intelligence has witnessed tremendous growth and development in past years, and will be even more widespread in a couple of brief years. AI Infrastructure makes the world of corporate data well-optimized and more streamlined. Machine learning algorithms that run through databases and message queuing systems are trained with AI Infrastructure to deliver data delivery flow.

Global Artificial Intelligence (AI) Infrastructure Market was valued at USD 23.50 billion in 2021 and is expected to reach USD 422.55 billion by 2029, registering a CAGR of 43.50% during the forecast period of 2022-2029. Cloud account for the largest deployment type segment in the respective market owing to the increase in the number of data center providers and cloud companies. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team also includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.

Market Definition

An Artificial Intelligence (AI) infrastructure refers to the technology that assists with machine learning (ML). The technology signifies the combination of machine learning and artificial intelligence solutions for development and deployment of scalable, reliable and specific data solutions. AI Infrastructure is known to key enable the whole machine learning process from start to finish.

Report Scope and Market Segmentation

Report Metric

Details

Forecast Period

2022 to 2029

Base Year

2021

Historic Years

2020 (Customizable to 2014 - 2019)

Quantitative Units

Revenue in USD Billion, Volumes in Units, Pricing in USD

Segments Covered

Offering (Hardware, Software), Technology (Machine Learning, Deep Learning), Function (Training and Inference), Deployment Type (On-Premises, Cloud, Hybrid), End-User (Enterprises, Government Organizations, Cloud Service Provider)

Countries Covered

U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.

Market Players Covered

Cisco (US), IBM (US), Intel Corporation (US), SAMSUNG (South Korea), Google (US), Microsoft (US), Micron Technology, Inc (US), NVIDIA Corporation (US), Oracle (US), Arm Limited (UK), Xilinx (US), Advanced Micro Devices, Inc (US), Dell (US), Hewlett Packard Enterprises Development LP (US), Habana Labs Ltd (US), Facebook, Inc (US), Synopsys, Inc (US), Nutanix (US), Pure Storage, Inc (US), Amazon Web Services, Inc (US), among others

Market Opportunities

  • Increase in the adoption of Chatbots to decline the operational costs
  • Increase in awareness regarding the incorporation of artificial intelligence (AI)
  • High investments in compute-intensive chip

Artificial Intelligence (AI) Infrastructure Market Dynamics

This section deals with understanding the market drivers, advantages, opportunities, restraints and challenges. All of this is discussed in detail as below:

Drivers

Rise in Awareness regarding Artificial Intelligence (AI)

The increase in awareness regarding the incorporation of artificial intelligence (AI) into business processes among enterprises acts as one of the major factors driving the artificial intelligence (AI) infrastructure market. This technology enhances operational efficiency while reducing cost through automation of process flows.

  • High Investments in Compute-Intensive Chip

GPU/CPU manufacturers, such as AMD, Qualcomm, NVIDIA, and Intel, among others increasing their investments in the development of chips that are compatible with AI solutions accelerate the market growth. Also, development of field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs) drives the market.

  • Surge in the Adoption of Chatbots

The increase in the adoption of Chatbots to decline the operational costs for businesses that is estimated to be up to 30% further influence the market. AI is beneficial for solving a specific set of problems and working with a significant volume of high-quality Big Data.

Additionally, rapid urbanization, change in lifestyle, surge in investments and increased consumer spending positively impact the artificial intelligence (AI) infrastructure market..

Opportunities

Furthermore, surge in demand for FPGA-based accelerators and rise in need for co-processors due to slowdown of Moore’s Law extend profitable opportunities to the market players in the forecast period of 2022 to 2029. The rise in potential of AI-based tools for elderly care will further expand the market.

Restraints/Challenges

On the other hand, concerns regarding data privacy in AI platforms and lack of AI hardware experts and skilled workforce are expected to obstruct market growth. Also, availability of limited structured data to train and develop efficient AI systems and unreliability of AI algorithms are projected to challenge the artificial intelligence (AI) infrastructure market in the forecast period of 2022-2029.

This artificial intelligence (AI) infrastructure market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on artificial intelligence (AI) infrastructure market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

COVID-19 Impact on Artificial Intelligence (AI) Infrastructure Market

The COVID-19 pandemic had a positive impact on the artificial intelligence (AI) infrastructure market. It helped millions of people globally in leveraging advanced tools for various applications, especially healthcare. Artificial intelligence (AI) infrastructure was highly useful for numerous medical applications such as decoding genomic sequence for drug development, enhancement of CT scans, remote patient monitoring, and healthcare chatbots, among others. The artificial intelligence (AI) infrastructure market is expected to witness high growth Post-COVID-19 due to the adoption of smart manufacturing processes using AI, blockchain and IoT technologies.

Recent Developments

  • Intel announced to launch a 3rd Gen Intel Xeon Scalable processor in April’2021. The processor provides a balanced architecture with built-in artificial intelligence, advanced security capabilities and crypto acceleration.
  • AMD announced the news regarding acquisition of Xilinx in April’2021. The acquisition will offer both companies complementary product portfolios and assist in capitalizing opportunities in the industry.

Global Artificial Intelligence (AI) Infrastructure Market Scope and Market Size

The artificial intelligence (AI) infrastructure market is segmented on the basis of offering, technology, function, deployment and end-user. The growth amongst these segments will help you analyze meager growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Offering

Technology

Function

  • Training
  • Inference

Deployment Type

  • On-Premises
  • Cloud
  • Hybrid

End-User

  • Enterprises
  • Government Organizations
  • Cloud Service Provider

Artificial Intelligence (AI) Infrastructure Market Regional Analysis/Insights

The artificial intelligence (AI) infrastructure market is analysed and market size insights and trends are provided by country, offering, technology, function, deployment and end-user as referred above.

The countries covered in the artificial intelligence (AI) infrastructure market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.

North America dominates the artificial intelligence (AI) infrastructure market due to the high adoption rate of AI based servers and presence of prominent AI technology providers within the region.

Asia-Pacific (APAC) is expected to witness significant growth during the forecast period of 2022 to 2029 because of the construction of "new infrastructure" projects, such as 5G networks and data centers in the region.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.   

Competitive Landscape and Artificial Intelligence (AI) Infrastructure Market

The artificial intelligence (AI) infrastructure market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to artificial intelligence (AI) infrastructure market.

Some of the major players operating in artificial intelligence (AI) infrastructure market are

  • Cisco (US)
  • IBM (US)
  • Intel Corporation (US)
  • SAMSUNG (South Korea)
  • Google (US)
  • Microsoft (US)
  • Micron Technology, Inc (US)
  • NVIDIA Corporation (US)
  • Oracle (US)
  • Arm Limited (UK)
  • Xilinx (US)
  • Advanced Micro Devices, Inc (US)
  • Dell (US)
  • Hewlett Packard Enterprises Development LP (US)
  • Habana Labs Ltd (US)
  • Facebook, Inc (US)
  • Synopsys, Inc (US)
  • Nutanix (US)
  • Pure Storage, Inc (US)
  • Amazon Web Services, Inc (US)

Research Methodology: Global Artificial Intelligence (AI) Infrastructure Market

Data collection and base year analysis is done using data collection modules with large sample sizes. The market data is analyzed and estimated using market statistical and coherent models. Also market share analysis and key trend analysis are the major success factors in the market report. To know more please request an analyst call or can drop down your enquiry.

The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market, and primary (industry expert) validation. Apart from this, data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.

Customization Available          

Data Bridge Market Research is a leader in advanced formative research. We take pride in servicing our existing and new customers with data and analysis that match and suits their goal. The report can be customized to include price trend analysis of target brands understanding the market for additional countries (ask for the list of countries), clinical trial results data, literature review, refurbished market and product base analysis. Market analysis of target competitors can be analyzed from technology-based analysis to market portfolio strategies. We can add as many competitors that you require data about in the format and data style you are looking for. Our team of analysts can also provide you data in crude raw excel files pivot tables (Factbook) or can assist you in creating presentations from the data sets available in the report.


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Frequently Asked Questions

The Artificial Intelligence (AI) Infrastructure Market is expected USD 422.55 billion by 2029.
The Artificial Intelligence (AI) Infrastructure Market is expected to witness CAGR of 43.50% during the forecast period of 2022-2029
On the basis of product, the Artificial Intelligence (AI) Infrastructure Market is segmented into Machine Learning, Deep Learning.
The major countries covered in the Artificial Intelligence (AI) Infrastructure Market are Cisco (US), IBM (US), Intel Corporation (US), SAMSUNG (South Korea), Google (US), Microsoft (US), Micron Technology, Inc (US), NVIDIA Corporation (US), Oracle (US), Arm Limited (UK), Xilinx (US), Advanced Micro Devices, Inc (US), Dell (US), Hewlett Packard Enterprises Development LP (US), Habana Labs Ltd (US), Facebook, Inc (US), Synopsys, Inc (US), Nutanix (US), Pure Storage, Inc (US), Amazon Web Services, Inc (US), among others.