세계의 AI 칩 시장 : 예측 - 칩 유형별, 처리 유형별, 기능별, 테크놀로지 노드별, 메모리 유형별, 용도별, 최종 사용자별, 지역별 분석(-2032년)

According to Stratistics MRC, the Global AI Chips Market is accounted for $170.3 billion in 2025 and is expected to reach $721.5 billion by 2032 growing at a CAGR of 22.9% during the forecast period. AI chips are specialized processors designed to handle artificial intelligence tasks like machine learning and deep learning. These chips accelerate complex computations by processing large volumes of data in parallel. With growing demand for faster, more efficient AI models, these chips are becoming essential across industries, from healthcare and finance to robotics and smart devices.

According to NVIDIA, the demand for GPU computing to support AI workloads has surged, with data center revenue reaching $22.6 billion in Q2 FY2024, a 171% increase year-over-year.

Market Dynamics:

Driver:

Explosive growth of Ai adoption across industries

The rapid integration of artificial intelligence across sectors such as healthcare, automotive, finance, and manufacturing is a primary driver for the AI chips market. As organizations increasingly leverage AI for automation, analytics, and decision-making, the demand for specialized chips capable of handling complex computations has surged. This widespread adoption is not limited to large enterprises; small and medium-sized businesses are also embracing AI-driven solutions. Furthermore, the proliferation of data centers and cloud-based services has intensified the need for high-performance AI chips, fueling market expansion.

Restraint:

High research & development and manufacturing costs

Developing and manufacturing advanced AI chips is an expensive and intricate process, requiring significant investments in R&D, specialized talent, and state-of-the-art fabrication facilities. The complexity of chip design, coupled with the need for constant innovation to keep pace with evolving AI algorithms, creates high entry barriers. Additionally, supply chain disruptions and the scarcity of critical raw materials can further escalate costs. These factors collectively constrain market growth, particularly for new entrants and smaller firms, and may slow the pace of technological advancement in the industry.

Opportunity:

Advancements in Ai algorithms and models

Ongoing breakthroughs in AI algorithms and models present substantial opportunities. As models become more sophisticated and resource-intensive, there is a growing need for hardware that can efficiently process these workloads. Moreover, the evolution of edge computing and the emergence of new AI applications in robotics, IoT, and autonomous systems are driving demand for innovative chip architectures. Companies that successfully harness these advancements stand to benefit from increased adoption, as industries seek hardware optimized for both performance and energy efficiency.

Threat:

Ethical concerns and regulatory scrutiny

AI chips face mounting challenges from ethical considerations and regulatory oversight. Issues such as data privacy, algorithmic bias, and the potential misuse of AI technologies have prompted governments and regulatory bodies to introduce stricter guidelines. These evolving regulations can increase compliance costs and delay product launches. Additionally, heightened public scrutiny may impact consumer trust and slow the adoption of AI-powered solutions.

Covid-19 Impact:

The Covid-19 pandemic initially disrupted global supply chains and manufacturing operations, causing delays in AI chip production and deployment. However, the crisis also accelerated digital transformation as organizations shifted to remote work and increased reliance on AI-driven technologies. This led to a surge in demand for AI chips in sectors such as healthcare, logistics, and e-commerce. Despite early setbacks, the market quickly adapted, and investments in AI infrastructure rose, positioning the industry for robust post-pandemic growth.

The graphics processing unit (GPU) segment is expected to be the largest during the forecast period

The graphics processing unit (GPU) segment is expected to account for the largest market share during the forecast period. GPUs are favored for their parallel processing capabilities, making them ideal for handling complex AI workloads in data centers, cloud environments, and high-performance computing applications. Major players such as NVIDIA, AMD, and Intel have established strong positions in this segment, driven by continuous innovation and robust demand from industries leveraging AI for deep learning, natural language processing, and computer vision. This dominance is set to persist as generative AI and large language models become more prevalent.

The edge segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the edge segment is predicted to witness the highest growth rate. The increasing need for real-time data processing and low-latency AI applications in autonomous vehicles, smart devices, and industrial automation is propelling demand for edge AI chips. These chips enable local processing, reducing reliance on cloud infrastructure and improving speed, privacy, and energy efficiency. As IoT adoption expands and more devices require on-device intelligence, the edge segment will experience significant acceleration.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. This dominance is attributed to the presence of leading technology companies, robust innovation ecosystems, and substantial investments in AI research and development. The region's early adoption of AI technologies across diverse sectors ranging from healthcare to automotive further bolsters demand. Additionally, supportive government initiatives and venture capital funding have fostered a favorable environment for AI chip innovation and commercialization, solidifying North America's leadership.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. Rapid digitalization, expanding industrial automation, and increasing investments in AI infrastructure are key drivers in this region. Countries like China, Japan, and South Korea are at the forefront of AI chip manufacturing and deployment, supported by strong government policies and a growing ecosystem of tech startups. The proliferation of smart devices and IoT applications, coupled with rising demand for affordable AI solutions, positions Asia Pacific as the fastest-growing region.

Key players in the market

Some of the key players in AI Chips Market include NVIDIA Corporation, Intel Corporation, Advanced Micro Devices, Inc. (AMD), Qualcomm Technologies, Inc., Alphabet Inc. (Google LLC), IBM Corporation, Samsung Electronics Co., Ltd., Huawei Technologies Co., Ltd., Baidu, Inc., Apple Inc., Microsoft Corporation, Amazon Web Services, Inc., Broadcom Inc., MediaTek Inc., Graphcore Limited, Rebellions Inc., SK Hynix Inc. and Sapeon Inc.

Key Developments:

In June 2025, AMD launched the AMD Instinct(TM) MI350 Series, delivering up to 4 x generation-on-generations AI compute improvement and up to 35x leap in inferencing performance. AMD also showcased its new developer cloud to empowering AI developers with seamless access to AMD Instinct GPUs and ROCm for their AI innovation. The company also previewed its next-gen "Helios" AI rack infrastructure, integrating MI400 GPUs, EPYC "Venice" CPUs, and Pensando "Vulcano" NICs for unprecedented AI compute density and scalability

In May 2025, NVIDIA announced that Taiwan's leading system manufacturers are set to build NVIDIA DGX Spark and DGX Station(TM) systems. Growing partnerships with Acer, GIGABYTE and MSI will extend the availability of DGX Spark and DGX Station personal AI supercomputers - empowering a global ecosystem of developers, data scientists and researchers with unprecedented performance and efficiency. Enterprises, software providers, government agencies, startups and research institutions need robust systems that can deliver the performance and capabilities of an AI server in a desktop form factor without compromising data size, proprietary model privacy or the speed of scalability.

In May 2025, At Embedded World Germany, Qualcomm Technologies, Inc. announced the entry into an agreement to acquire EdgeImpulse Inc., which will enhance its offering for developers and expand its leadership in AI capabilities to power AI-enabled products and services across IoT. The closing of this deal is subject to customary closing conditions. This acquisition is anticipated to complement Qualcomm Technologies' strategic approach to IoT transformation, which includes a comprehensive chipset roadmap, unified software architecture, a suite of services, developer resources, ecosystem partners, comprehensive solutions, and IoT blueprints to address diverse industry needs and challenges.

Chip Types Covered:

• Central Processing Unit (CPU)
• Graphics Processing Unit (GPU)
• Field Programmable Gate Array (FPGA)
• Application-Specific Integrated Circuit (ASIC)
• Other Chip Types

Processing Types:

• Edge
• Cloud
• On-premise

Functionalities Covered:

• Training
• Inference

Technology Nodes Covered:

• 10nm and Below
• 10nm to 20nm
• 20nm and Above

Memory Types Covered:

• DDR (DRAM)
• HBM (High-Bandwidth Memory)
• Other Memory Types

Applications Covered:

• Natural Language Processing (NLP)
• Computer Vision
• Generative AI
• Network Security
• Robotics
• Predictive Analysis
• Other Applications

End Users Covered:

• Consumer Electronics
• Data Centers
• Automotive
• Healthcare
• BFSI
• IT & Telecom
• Industrial
• Aerospace & Defense
• Retail
• Agriculture
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Technology Analysis
• 3.7 Application Analysis
• 3.8 End User Analysis
• 3.9 Emerging Markets
• 3.10 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global AI Chips Market, By Chip Type

• 5.1 Introduction
• 5.2 Central Processing Unit (CPU)
• 5.3 Graphics Processing Unit (GPU)
• 5.4 Field Programmable Gate Array (FPGA)
• 5.5 Application-Specific Integrated Circuit (ASIC)
  • 5.5.1 Neural Processing Units (NPUs)
  • 5.5.2 Tensor Processing Units (TPUs)
  • 5.5.3 Other Custom AI Accelerators
• 5.6 Other Chip Types

6 Global AI Chips Market, By Processing Type

• 6.1 Introduction
• 6.2 Edge
• 6.3 Cloud
• 6.4 On-premise

7 Global AI Chips Market, By Functionality

• 7.1 Introduction
• 7.2 Training
• 7.3 Inference

8 Global AI Chips Market, By Technology Node

• 8.1 Introduction
• 8.2 10nm and Below
• 8.3 10nm to 20nm
• 8.4 20nm and Above

9 Global AI Chips Market, By Memory Type

• 9.1 Introduction
• 9.2 DDR (DRAM)
• 9.3 HBM (High-Bandwidth Memory)
• 9.4 Other Memory Types

10 Global AI Chips Market, By Application

• 10.1 Introduction
• 10.2 Natural Language Processing (NLP)
• 10.3 Computer Vision
• 10.4 Generative AI
• 10.5 Network Security
• 10.6 Robotics
• 10.7 Predictive Analysis
• 10.8 Other Applications

11 Global AI Chips Market, By End User

• 11.1 Introduction
• 11.2 Consumer Electronics
• 11.3 Data Centers
• 11.4 Automotive
• 11.5 Healthcare
• 11.6 BFSI
• 11.7 IT & Telecom
• 11.8 Industrial
• 11.9 Aerospace & Defense
• 11.10 Retail
• 11.11 Agriculture
• 11.12 Other End Users

12 Global AI Chips Market, By Geography

• 12.1 Introduction
• 12.2 North America
  • 12.2.1 US
  • 12.2.2 Canada
  • 12.2.3 Mexico
• 12.3 Europe
  • 12.3.1 Germany
  • 12.3.2 UK
  • 12.3.3 Italy
  • 12.3.4 France
  • 12.3.5 Spain
  • 12.3.6 Rest of Europe
• 12.4 Asia Pacific
  • 12.4.1 Japan
  • 12.4.2 China
  • 12.4.3 India
  • 12.4.4 Australia
  • 12.4.5 New Zealand
  • 12.4.6 South Korea
  • 12.4.7 Rest of Asia Pacific
• 12.5 South America
  • 12.5.1 Argentina
  • 12.5.2 Brazil
  • 12.5.3 Chile
  • 12.5.4 Rest of South America
• 12.6 Middle East & Africa
  • 12.6.1 Saudi Arabia
  • 12.6.2 UAE
  • 12.6.3 Qatar
  • 12.6.4 South Africa
  • 12.6.5 Rest of Middle East & Africa

13 Key Developments

• 13.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 13.2 Acquisitions & Mergers
• 13.3 New Product Launch
• 13.4 Expansions
• 13.5 Other Key Strategies

14 Company Profiling

• 14.1 NVIDIA Corporation
• 14.2 Intel Corporation
• 14.3 Advanced Micro Devices, Inc. (AMD)
• 14.4 Qualcomm Technologies, Inc.
• 14.5 Alphabet Inc. (Google LLC)
• 14.6 IBM Corporation
• 14.7 Samsung Electronics Co., Ltd.
• 14.8 Huawei Technologies Co., Ltd.
• 14.9 Baidu, Inc.
• 14.10 Apple Inc.
• 14.11 Microsoft Corporation
• 14.12 Amazon Web Services, Inc.
• 14.13 Broadcom Inc.
• 14.14 MediaTek Inc.
• 14.15 Graphcore Limited
• 14.16 Rebellions Inc.
• 14.17 SK Hynix Inc.
• 14.18 Sapeon Inc.