NEW
YORK, Jan. 18, 2025 /PRNewswire/ -- Report on
how AI is redefining market landscape - The global artificial
intelligence (AI) chips market size is estimated to grow by
USD 902.65 billion from 2025-2029,
according to Technavio. The market is estimated to grow at a CAGR
of over 81.2% during the forecast period. Increased focus on
developing AI chips for smartphones is driving market
growth, with a trend towards convergence of AI and IoT.
However, dearth of technically skilled workers for ai chips
development poses a challenge. Key market players include Advanced
Micro Devices Inc., Baidu Inc., Broadcom Inc., Cerebras, Fujitsu
Ltd., Google LLC, Graphcore Ltd., Huawei Technologies Co. Ltd.,
Intel Corp., International Business Machines Corp., MediaTek Inc.,
Microchip Technology Inc., NVIDIA Corp., NXP Semiconductors NV,
Qualcomm Inc., SambaNova Systems Inc., Samsung Electronics Co.
Ltd., SenseTime Group Inc., Taiwan Semiconductor Manufacturing Co.
Ltd., and Tesla Inc..
Key insights into market evolution with
AI-powered analysis. Explore trends, segmentation, and growth
drivers- View Free Sample PDF
Artificial
Intelligence (AI) Chips Market Scope
|
Report
Coverage
|
Details
|
Base year
|
2024
|
Historic
period
|
2019 - 2023
|
Forecast
period
|
2025-2029
|
Growth momentum &
CAGR
|
Accelerate at a CAGR of
81.2%
|
Market growth
2025-2029
|
USD 902.65
billion
|
Market
structure
|
Fragmented
|
YoY growth 2022-2023
(%)
|
61.7
|
Regional
analysis
|
North America, Europe,
APAC, South America, and Middle East and Africa
|
Performing market
contribution
|
North America at
42%
|
Key
countries
|
US, Canada, China, UK,
Germany, France, Japan, Italy, India, and Brazil
|
Key companies
profiled
|
Advanced Micro Devices
Inc., Baidu Inc., Broadcom Inc., Cerebras, Fujitsu Ltd., Google
LLC, Graphcore Ltd., Huawei Technologies Co. Ltd., Intel Corp.,
International Business Machines Corp., MediaTek Inc., Microchip
Technology Inc., NVIDIA Corp., NXP Semiconductors NV, Qualcomm
Inc., SambaNova Systems Inc., Samsung Electronics Co. Ltd.,
SenseTime Group Inc., Taiwan Semiconductor Manufacturing Co. Ltd.,
and Tesla Inc.
|
Market Driver
Artificial Intelligence (AI) is revolutionizing industries from
healthcare to retail, finance, and automotive with deep learning
and machine learning algorithms. The demand for AI technologies is
driving the growth of AI chips market. Companies like Advanced
Micro Devices, Nvidia, and Huawei are leading the way with AI chip
lines, such as the Trainium2 chip and Ascend 910B chipset. These chips are designed to handle
the high computing requirements of AI technologies, including
quantum computing and generative AI. Major cloud providers like
Microsoft Azure, Amazon Web Services, and Google Cloud are
investing in AI data centers to offer AI services to businesses and
developers. Edge computing is also gaining popularity for real-time
applications, reducing latency and improving data processing
efficiency. Energy efficiency is a key consideration for AI chip
manufacturers, as AI applications consume vast amounts of power. AI
chip lines include CPUs, GPUs, FPGAs, and ASICs, each optimized for
specific applications. Ethical concerns around AI use are also
driving the development of specific integrated chips for AI
applications. AI technologies are being integrated into various
industries, from healthcare to manufacturing, with applications
ranging from image recognition to cognitive computing. Patent
filings for AI technologies are on the rise, with companies seeking
to protect their intellectual property. However, system failure and
malfunctioning remain concerns, as AI systems can have significant
impacts on businesses and individuals. The AI chip market is
expected to continue growing, with applications in mobile phones,
personal computers, gaming consoles, and embedded systems. The
future of AI technologies lies in the integration of AI chips into
various devices, from wearable devices to smart homes and connected
cars, enabling personalized health, real-time analysis, and
more.
The Internet of Things (IoT) market is experiencing significant
growth due to the advantages it offers in various industries such
as aerospace and defense, automotive, consumer electronics,
healthcare, and more. IoT devices, which include cameras, drones,
smart speakers, smartphones, smart TVs, and others, are making
decisions based on data received without human intervention. To
enable power-efficient data processing and machine learning
computation in these devices, AI chips are being integrated. This
trend is driving the demand for AI chips in the IoT market,
enabling devices to perform complex tasks and improve overall
efficiency.
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Market Challenges
- Artificial Intelligence (AI) is revolutionizing industries from
healthcare to retail, finance, and automotive. However, the
increasing demand for AI technologies, including deep learning and
machine learning, poses challenges for hardware components like AI
chips. Advanced Micro and Nvidia lead the market with their AI chip
lines, such as Trainium2 and A100 chip, respectively. These chips
power AI algorithms and technologies, enabling applications like
image recognition, pose detection, and behavioral patterns
analysis. However, developing AI chips comes with challenges.
Energy efficiency is crucial as AI applications require high
computing power. Quantum computing and highbandwidth memory are
potential solutions, but patent filings and system failure risks
exist. AI data centers and centralized cloud servers face latency
issues, necessitating edge computing and Edge devices. Ethical
concerns surrounding AI use also arise. Major cloud providers like
Microsoft Azure, Amazon Web Services, and Google Cloud offer AI
services, but energy efficiency and latency remain concerns. AI
applications in healthcare, retail, finance, and automotive require
real-time data processing, making AI chip lines, GPUs, FPGAs, CPUs,
ASICs, and DSP essential. The future of AI lies in cognitive
computing, machine intelligence, and AI data centers, but
challenges persist in ensuring energy efficiency, reliability, and
ethical use.
- The AI chips market is witnessing significant expansion due to
the potential financial gains that businesses can reap from
artificial intelligence. However, the absence of a sufficient
workforce with specialized AI knowledge presents a substantial
challenge to market growth. Companies must meticulously evaluate
the integration of AI, considering its high research and
development costs. The scarcity of skilled professionals in this
field is currently the most significant barrier for enterprises
looking to implement AI in their operations.
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Segment Overview
This artificial intelligence (AI) chips market report
extensively covers market segmentation by
- Product
- 1.1 ASICs
- 1.2 GPUs
- 1.3 CPUs
- 1.4 FPGAs
- End-user
- 2.1 Media and advertising
- 2.2 BFSI
- 2.3 IT and telecommunication
- 2.4 Others
- Geography
- 3.1 North America
- 3.2 Europe
- 3.3 APAC
- 3.4 South America
- 3.5 Middle East and
Africa
- Processing Type
- Application
- Technology
1.1 ASICs- Artificial Intelligence (AI) chips market
is witnessing significant growth due to the increasing adoption of
application-specific integrated circuits (ASICs) in data centers.
ASICs are customized chips that offer faster performance compared
to GPUs and FPGAs. They are specifically designed for parallel
processing, making them ideal for AI applications. Google's Tensor
Processing Unit (TPU) is a prime example of ASIC-based
AI chips. TPU is a network of hardware and software that can learn
specific tasks by analyzing large data sets. It is already being
used in applications like Google Search and Google Street View.
Data centers are incorporating TPUs at the back end of servers to
manage data effectively. TPU's instruction set allows TensorFlow
programs to be changed, enabling the development of new algorithms.
TensorFlow is an open-source machine learning library with a data
flow graph structure, where nodes represent arithmetical
operations, and edges denote multidimensional arrays.
ASIC-based AI chips are expected to continue gaining
market share due to their higher performance and speed compared to
GPUs, FPGAs, and CPUs.
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comprehensive report today to discover how AI-driven innovations
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Research Analysis
Artificial Intelligence (AI) Chips Market: The global AI Chips
Market is experiencing significant growth due to the increasing
adoption of AI technologies in various industries such as
healthcare, retail, finance, automotive, and IoT devices. AI Chips
are specialized hardware components designed to accelerate AI
algorithms, including deep learning and machine learning. These
chips are essential for powering AI applications in robotics,
autonomous vehicles, and high-performance computing systems. The
market includes various types of chips such as Specific Integrated
Chips (SICs), CPUs, FPGAs, and GPUs. Advanced Micro, Trainium2
chip, and other players are developing innovative AI Chips to
address the growing demand for AI hardware. AI Chips are also being
integrated into quantum computing systems, cloud, and edge
computing infrastructure. The market's growth is driven by the
increasing use of AI in various applications, such as generative
AI, supercomputers, and highbandwidth memory. However, ethical
concerns regarding AI technologies and the need for
energy-efficient and cost-effective solutions pose challenges to
the market's growth. In summary, the AI Chips Market is poised for
significant growth due to the increasing adoption of AI
technologies in various industries and the development of
specialized hardware components to accelerate AI algorithms.
However, ethical concerns and the need for energy-efficient and
cost-effective solutions present challenges to the market's
growth.
Market Research Overview
Artificial Intelligence (AI) Chips Market: Overview The
Artificial Intelligence (AI) Chips Market is a rapidly growing
sector that focuses on developing specialized hardware components
to support AI algorithms, deep learning, and machine learning
applications. These chips are designed to enhance the performance
and energy efficiency of AI technologies, including quantum
computing, neural networks, and cognitive computing. AI Chips are
integral to various industries, including robotics, healthcare,
retail, finance, automotive, and manufacturing, where real-time
data processing and low latency are essential. The market includes
a range of hardware components, such as CPUs, GPUs, FPGAs, ASICs,
DSPs, and microcontrollers, each optimized for specific AI
applications. Deep learning and machine learning algorithms require
high computing power and large amounts of data processing. AI
chips, such as the Trainium2 chip, are designed to address these
requirements, offering high bandwidth memory and parallel computing
capabilities. Advanced AI technologies, such as generative AI and
large language models, are driving the demand for more powerful and
energy-efficient chips. Edge computing and Edge devices are also
gaining popularity, as they enable data processing closer to the
source, reducing latency and increasing the speed of real-time
applications. Ethical concerns surrounding AI and data privacy are
also influencing the market, as companies invest in AI chip lines
that prioritize security and data protection. The market is
expected to continue growing, driven by the increasing adoption of
AI technologies in various industries and the development of new AI
applications, such as computer vision, pose detection, and
behavioral pattern recognition. Patent filings and system failure
or malfunctioning issues are ongoing challenges in the market, as
companies race to innovate and improve the performance and
reliability of their AI chips. The market is highly competitive,
with players such as Nvidia, Ascend, and Microsoft Azure offering a
range of AI chip solutions for various applications. In summary,
the AI Chips Market is a dynamic and evolving sector, driven by the
increasing adoption of AI technologies and the need for specialized
hardware components to support their growing demands for high
computing power, energy efficiency, and data processing
capabilities. The market includes a range of hardware components,
from CPUs and GPUs to FPGAs and ASICs, each optimized for specific
AI applications and industries, including healthcare, retail,
finance, automotive, and manufacturing. Ethical concerns, patent
filings, and system reliability are ongoing challenges, but the
market is expected to continue growing, driven by the increasing
adoption of AI technologies and the development of new
applications, such as computer vision, pose detection, and
behavioral pattern recognition.
Table of Contents:
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation
- Product
-
- End-user
-
- Media And Advertising
- BFSI
- IT And Telecommunication
- Others
- Geography
-
- North America
- Europe
- APAC
- South America
- Middle East And Africa
- Processing Type
- Application
- Technology
7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix
About Technavio
Technavio is a leading global technology research and advisory
company. Their research and analysis focuses on emerging market
trends and provides actionable insights to help businesses identify
market opportunities and develop effective strategies to optimize
their market positions.
With over 500 specialized analysts, Technavio's report library
consists of more than 17,000 reports and counting, covering 800
technologies, spanning across 50 countries. Their client base
consists of enterprises of all sizes, including more than 100
Fortune 500 companies. This growing client base relies on
Technavio's comprehensive coverage, extensive research, and
actionable market insights to identify opportunities in existing
and potential markets and assess their competitive positions within
changing market scenarios.
Contacts
Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/
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SOURCE Technavio