AI Infrastructure Market Growth Opportunities - Global Forecast to 2027 - PowerPoint PPT Presentation

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AI Infrastructure Market Growth Opportunities - Global Forecast to 2027


AI infrastructure market is projected to grow from USD 28.7 billion in 2022 to USD 96.6 billion by 2027, at a CAGR of 27.5% during the forecast period from 2022 to 2027. – PowerPoint PPT presentation

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Title: AI Infrastructure Market Growth Opportunities - Global Forecast to 2027

MarketsandMarkets Presents

AI Infrastructure Market Growth Opportunities -
Global Forecast to 2027 AI Infrastructure Market
by Offering (Hardware, Server Software),
Technology (Machine Learning, Deep Learning),
Function (Training, Inference), Deployment Type
(On-premises, Hybrid, Cloud), End user and Region
- Global Forecast to 2027 https//www.marketsandm
234 Pages Report The global AI infrastructure
market is projected to grow from USD 28.7 billion
in 2022 to USD 96.6 billion by 2027, at a CAGR of
27.5 during the forecast period from 2022 to
2027.  The growth of this market is driven by
factors such as increased data traffic and need
for high computing power, increasing adoption of
cloud-based machine learning platforms,
increasingly large and complex dataset, growing
number of cross-industry partnerships and
collaborations, increasing adoption of AI due to
the COVID-19 pandemic, rising focus on parallel
computing in AI data centers. Browse in-depth
TOC on "AI Infrastructure Market" 176
Tables63 Figures234 Pages
Driver Rising focus on parallel computing in AI
data centers CPUs are used for serial computing
in data centers to track a series of memory
locations where instructions and data are stored.
A processor makes computations serially by
analyzing the instructions and data at the memory
addresses. In serial computation, computational
steps are sequential and logical. In other words,
a single task at a data center is divided into a
series of separate instruction sets, executed
serially by a processor. This typically leads to
latency problems in data centers, especially
during AI-based computations wherein data and
instruction sets are huge in numbers. In the
parallel computing structure, multiple compute
resources are used concurrently to execute
instructions. In this method, instructions are
divided into discrete parts that can be executed
concurrently by multiple co-processors. This
makes parallel computing favorable for
HPC/supercomputers. Ask PDF Brochure https//www
348 Restraint Lack of AI hardware experts and
skilled workforce Artificial Intelligence is a
complex system, and companies require experts and
a skilled workforce for developing, managing, and
implementing AI systems. People dealing with AI
systems should be aware of technologies such as
cognitive computing, machine learning (ML),
machine intelligence, deep learning, and image
recognition. In addition, integrating AI
technology into existing systems is a challenging
task that requires well-funded in-house RD and
patent filling. Even minor errors can translate
into system failure or malfunctioning of a
solution, and this can drastically affect the
outcome and desired result. Professional services
of data scientists and developers are needed to
customize existing ML-enabled AI processors.
Companies across industries embrace emerging
technologies to improve operational efficiency
and performance, reduce waste, conserve natural
resources, reach new markets and audiences with
speed and convenience, and support product and
process innovation.
Opportunity Rising need for co-processors due to
slowdown of Moores Law Moore's law states that
the number of transistors per square inch on
integrated circuits will double about every 18
months until at least 2020. In April 2015, Intel
Corporation stated that it could sustain Moore's
law for another few years by developing 7 nm and
5 nm fabrication technologies. However, moving
forward, it would be challenging to further
reduce the size of processors doing so would
also reduce the space between electrons and
holes, which will create problems such as current
leakage and overheating in ICs. These problems
would lead to slower performance, higher power
consumption by ICs, and a further reduction in
durability. Thus, the need to find an alternate
way to increase the computational power of chips
has fuelled the development of accelerators or
co-processor chips, which are critical elements
of AI infrastructure. Request Free Sample
Pages https//
mpleNew.asp?id38254348 Challenge Concerns
regarding data privacy in AI platforms AI has
several applications in the healthcare industry.
However, the adoption of AI in the industry is
restricted to an extent owing to data privacy
concerns. Patients' health data is protected
under federal laws in many countries, and any
breach or failure to maintain its integrity can
result in legal and financial penalties. As AI
used for patient care requires access to multiple
health datasets, it is essential for AI-based
tools to adhere to all data security protocols
mandated by governments and regulatory
authorities. This is a challenging task as most
AI platforms are consolidated and require
extensive computing power, owing to which,
patient data or parts of it can be required to
reside in a vendor's data center. This is a major
challenge in the market.
China in APAC to account for the largest market
share and highest growth rate during the forecast
period The market in China among APAC countries,
holds the largest market share and highest growth
rate and is expected to retain its position
during the forecast period. The AI infrastructure
market in China is growing rapidly. As
multinational and domestic enterprises
increasingly transit to cloud services providers
(CSPs) and co-location solutions, the growth of
AI data centers in China continues to evolve. The
demand for AI data centers in the country has
increased due to organizations seeking enhanced
connectivity and scalable solutions for their
growing businesses. Various government reforms
and initiatives, such as the establishment of
free trade in Shanghai, are attracting
international investors. APAC to account for the
largest market share and highest growth rate
during the forecast period The market in Asia
Pacific holds the largest market share and
highest growth rate and is expected to retain its
position during the forecast period. The high
growth is due to the presence of most populous
countries such as China and India. India is one
of the world's fastest-growing economies, with a
huge interest in AI's worldwide development. The
Indian government recognizes the potential and is
taking all necessary steps to steer the country
and place it among the leaders in AI. Despite the
favorable ecosystem, the government is trying to
overcome to achieve rapid progress in AI.
Similarly, the Chinese government is speeding up
the construction of new infrastructure projects
such as 5G networks and data centers, bolstering
information services for the expanding market.
Also, the government announced the establishment
of the Next Generation Artificial Intelligence
Development Plan, which promises policy support,
central coordination, and investments of more
than USD 150 billion by 2030.
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