AI Infrastructure Market Share, Size, Trends, Industry Analysis Report, By Technology (Machine Learning, Deep Learning), End-Use (Enterprises, Government Organizations, Cloud Service Providers); By Deployment; By Offering; By Region; Segment Forecast, 202

AI Infrastructure Market Share, Size, Trends, Industry Analysis Report, By Technology (Machine Learning, Deep Learning), End-Use (Enterprises, Government Organizations, Cloud Service Providers); By Deployment; By Offering; By Region; Segment Forecast, 2022 - 2030

The global AI infrastructure market size is expected t-reach USD 197.39 billion by 2030 according t-a new study by Polaris Market Research. The report “AI Infrastructure Market Share, Size, Trends, Industry Analysis Report, By Technology (Machine Learning, Deep Learning), End-Use (Enterprises, Government Organizations, Cloud Service Providers); By Deployment; By Offering; By Region; Segment Forecast, 2022 – 2030” gives a detailed insight int-current market dynamics and provides analysis on future market growth.

The prominent factors for the market growth such as the rising penetration of the cloud machine learning platforms, coupled with the growing focus on parallel computing in artificial intelligence data centers are stimulating the industry demand globally. In addition, increased data traffic and escalating requirements for computing power are further supporting the industry’s development in the forthcoming years. Based on the offering, the hardware segment is holding the highest shares in the global industry in 2020, owing t-the demand for artificial intelligence hardware is considerably increasing as of its adoption in various applications such as robotic process automation, machine learning, and biometrics.

Therefore, businesses are deploying artificial intelligence hardware that creates the demand for AI infrastructure for industry growth worldwide. Whereas the artificial intelligence software and services segment is likely t-rise at a healthy rate in the foreseen years due t-the growing penetration of digital platforms. Moreover, artificial intelligence applications comprise sparse matrices; vide-analytics, primitives, inference, and multi-hardware communication ability are boosting the segment growth in impending years.

Growing demand for the Field Programmable Gate Array (FPGA) is an incorporated circuit, which designers or consumers can configure after it is being manufactured (field programmable). These FPGAs are programmed t-understand hardware report languages such as Verilog and VHSIC hardware description language (VHDL). FPGAs present various benefits like short time-to-market, fast prototyping, the capability t-be redesigned in the domain for long product life, and cycle debugging. This comprises entity programmable logic blocks, generally called configurable logic blocks (CLBs), which are interrelated in that way, users can configure the computing system multiple times. Thus, these features may positively support the artificial intelligence infrastructure industry demand in the near future.

Market participants such as Samsung Electronics, Amazon Web Service, Cadence Design Systems, Cisco, Sensetime, Dell, Xilinx, Graphcore, Advanced Micr-Devices, Inc, Hewlett Packard Enterprise Development LP, Google, IBM, Imagination Technologies, INTEL, Micron Technology, Microsoft, NVIDIA, SK Hynix, Tenstorrent, Toshiba, Wave Computing, and Gyrfalcon Technology are some of the key players operating in the global artificial intelligence infrastructure market.

There are numerous market competitors wh-are introducing various new products for acquiring a prominent position across the artificial intelligence infrastructure market. For instance, in April 2021, AMD declared that the company is in the process of acquiring Xilinx. The objective of this acquisition is t-bring together tw-industry leaders with complementary product portfolios and capitalize on opportunities in the AI infrastructure industry.

Polaris Market Research has segmented the AI infrastructure market report on the basis of offering, deployment, technology, end-use, and region:

AI Infrastructure, Offering Outlook (Revenue – USD Billion, 2018 – 2030)

• Hardware
Processor
Storage
Memory
• Software

AI Infrastructure, Deployment Outlook (Revenue – USD Billion, 2018 – 2030)

• On-Premises
• Cloud
• Hybrid

AI Infrastructure, Technology Outlook (Revenue – USD Billion, 2018 – 2030)

• Machine Learning
• Deep Learning

AI Infrastructure, End-Use Outlook (Revenue – USD Billion, 2018 – 2030)

• Enterprises
• Government Organizations
• Cloud Service Providers

AI Infrastructure, Regional Outlook (Revenue – USD Billion, 2018 – 2030)

• North America
• U.S.
• Canada
• Europe
• France
• Germany
• UK
• Italy
• Spain
• Netherlands
• Austria
• Asia Pacific
• China
• India
• Japan
• Malaysia
• South Korea
• Indonesia
• Latin America
• Mexico
• Brazil
• Argentina
• Middle East & Africa
• UAE
• Saudi Arabia
• Israel
• South Africa