AI Accelerator Chips Market - Forecasts From 2025 To 2030

The AI Accelerator Chips Market is projected to grow at a CAGR of 26.79% during the projected period (2022-2030).  

An AI chip is a specialized integrated circuit designed to carry out AI functions quickly and effectively.  These chips are specifically designed to speed up complex algorithmic computations, which are essential for a range of artificial intelligence applications.  When compared to general-purpose processors, they obtain impressive performance gains by utilizing special neural network topologies, parallel processing capabilities, and optimized memory structures.  ________________________________________

AI Accelerator Chips Market Overview & Scope

The AI accelerator chips market is segmented by:

• Chip Type: The artificial intelligence accelerator chip market by chip type is categorized into GPU, ASIC, FPGA, CPU, and others. ASICs provide libraries and an instruction set for local data processing and parallel algorithm execution; they are non-configurable and customizable. They are the perfect option for AI data centers, where these chips serve as accelerators for algorithms related to machine learning and deep learning. ASIC-based AI chips are becoming popular since they can perform faster and better than GPUs, FPGAs, and CPUs.
• Processing Type: Cloud and edge are two segmentations for the processing type section. The cloud subsegment is expected to have the largest market share among these. Businesses can provide value to their clients by using Cloud Accelerator to establish a secure and functionally sound cloud environment. It speeds up the adoption of cloud computing while saving enterprises money and time.
• Application: Network security, robotics, computer vision, and natural language processing (NLP) are divisions of the application segment. It is projected that the natural language processing subsegment will hold a significant portion of the market. The natural language processing (NLP), for instance, is frequently used at work and home. Customers use voice commands on cell phones, virtual assistants, cars, etc, in daily life. 
• Industry Vertical: The AI accelerator chip market by industry vertical segment is divided into retail, communications, healthcare, financial services, automobile and transportation, and other categories. It is projected that the healthcare subsegment will hold a significant portion of the market. AI in healthcare has the potential to enhance quality of life and preventative care, offer more precise diagnosis and treatment strategies, and improve patient outcomes. 
• Region:  The market is segmented into five major geographic regions, namely North America, South America, Europe, the Middle East and Africa, and Asia-Pacific. North America is anticipated to dominate the market, and it will be growing at the fastest CAGR. 

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Top Trends Shaping the AI Accelerator Chips Market 

1. Enhancing Energy Efficiency in Generative AI Creates Growth Opportunities in Future Chips

• The increasing need for generative AI is mostly met by AI inference accelerators, which provide enhanced performance, scalability, and energy efficiency. These improvements make it possible to process complicated, regulation-intensive models more quickly, which is crucial for AI data centers looking to sustain operational effectiveness at scale. Accelerators play a crucial role in the changing environment of AI infrastructure by ensuring that data centers can meet demand while improving energy consumption and computational performance as generative AI models advance.

2. The market is expanding as a result of businesses' increasing use of cloud-based solutions.

• The market for cloud-based AI chipsets is expected to be driven by the growing number of data centers being established worldwide in a variety of industries, such as IT and telecom, automotive, etc. The cloud-based AI chipset is available from firms like Alibaba Group Holding Limited, Intel Corporation, NVIDIA Corporation, and others.  These major players are focusing on introducing cutting-edge cloud-based solutions to manage massive amounts of company data and file storage. 

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AI Accelerator Chips Market Growth Drivers vs. Challenges 

Drivers:

• Growth of Advanced Lithography-Driven AI Accelerator Chips to Increase Semiconductor Self-Sufficiency: EUV restrictions can be circumvented by 5nm devices created using developments in DUV lithography and Self-Aligned Octuple Patterning (SAOP). They are supporting the growth of the indigenous semiconductor industry and reducing reliance on foreign technologies. AI and semiconductor self-reliance are fueled by this technology-agnostic resilience. As a result, the industry becomes more competitive, promoting growth and reducing dependency on global supply networks.

Challenges:

Market expansion may be impeded by export controls and trade restrictions:  The market for AI accelerator chips is primarily threatened by export restrictions on essential raw materials, particularly rare earth and special metals. Restrictions on their availability can cause production schedule disruptions, cost increases, and delays in the release of new technologies because they are utilized to make high-end AI semiconductor chips. Such circumstances may hinder the development of AI accelerator chip designs and manufacturing for a variety of AI applications.

Increasing R&D Costs of Artificial Intelligence Chips Worldwide: High R&D costs, which can amount to billions of dollars, are necessary for the creation of AI accelerator chips because of the intricacy of the architecture, fabrication, and power-efficient optimization.  These protracted, costly development cycles are risky for businesses since market conditions shift quickly. 

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AI Accelerator Chips Market Regional Analysis 

• North America: Geographically, the market for artificial intelligence chips is anticipated to be dominated by North America. One of the main factors propelling market expansion in North America is the expanding use of AI technology in the IT sector. The US and Canada are home to important technology companies that are driving the region's artificial intelligence chip industry expansion. Moreover, in the global market for artificial intelligence (AI) chips, Europe might have the fastest rate of growth due to the increasing adoption of AI in various industries, such as robotics, healthcare, retail, finance, automotive, and autonomous vehicles.

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AI Accelerator Chips Market Competitive Landscape

The market is moderately fragmented, with many key players including NVIDIA, AMD, Intel, Google, Qualcomm, Tesla, Baidu, Huawei, Samsung, and Others. 

• Product Launch: In June 2024, AMD Ryzen AI 300 Series CPUs with potent NPUs and 50 TOPS AI processing capacity were introduced by Advanced Micro Devices, Inc. for use in next-generation AI PCs. It has 12 powerful CPU cores and a strong AI design for work and gaming. These processors are driven by the new Zen5 architecture.
• Sustainable product launch: In May 2024, the sixth-generation TPU Trillium, which has better training and serving times for AI workloads, was unveiled by Google (US).  It features larger matrix multiply units and faster clock speeds. 

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AI Accelerator Chips Market Segmentation:  

By Chip Type

• GPU
• ASIC
• FPGA
• CPU
• Other 

By Processing Type

• Edge
• Cloud 

By Application

• Natural Language Processing
• Computer Vision
• Robotics
• Network Security

By Industry

• Automotive
• Consumer Electronics
• Healthcare
• Manufacturing
• Others

By Region

• North America
  • USA
  • Mexico
  • Others
• South America
  • Brazil
  • Argentina
  • Others
• Europe
  • United Kingdom
  • Germany
  • France
  • Spain
  • Others
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Others
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Taiwan
  • Others

1. EXECUTIVE SUMMARY 

2. MARKET SNAPSHOT

2.1. Market Overview

2.2. Market Definition

2.3. Scope of the Study

2.4. Market Segmentation

3. BUSINESS LANDSCAPE 

3.1. Market Drivers

3.2. Market Restraints

3.3. Market Opportunities 

3.4. Porter’s Five Forces Analysis

3.5. Industry Value Chain Analysis

3.6. Policies and Regulations 

3.7. Strategic Recommendations 

4. TECHNOLOGICAL OUTLOOK

5. AI ACCELERATOR CHIPS MARKET BY CHIP TYPE

5.1. Introduction

5.2. GPU

5.3. ASIC

5.4. FPGA

5.5. CPU

5.6. Other 

6. AI ACCELERATOR CHIPS MARKET BY PROCESSING TYPE 

6.1. Introduction

6.2. Edge

6.3. Cloud 

7. AI ACCELERATOR CHIPS MARKET BY APPLICATION

7.1. Introduction

7.2. Natural Language Processing

7.3. Computer Vision

7.4. Robotics

7.5. Network Security

8. AI ACCELERATOR CHIPS MARKET BY INDUSTRY 

8.1. Introduction

8.2. Automotive

8.3. Consumer Electronics

8.4. Healthcare

8.5. Manufacturing

8.6. Others

9. AI ACCELERATOR CHIPS MARKET BY GEOGRAPHY 

9.1. Introduction

9.2. North America

9.2.1. By Chip Type

9.2.2. By Processing Type

9.2.3. By Application

9.2.4. By Industry

9.2.5. By Country

9.2.5.1. USA

9.2.5.2. Canada

9.2.5.3. Mexico

9.3. South America

9.3.1. By Chip Type

9.3.2. By Processing Type

9.3.3. By Application

9.3.4. By Industry

9.3.5. By Country

9.3.5.1. Brazil

9.3.5.2. Argentina

9.3.5.3. Others

9.4. Europe

9.4.1. By Chip Type

9.4.2. By Processing Type

9.4.3. By Application

9.4.4. By Industry

9.4.5. By Country

9.4.5.1. United Kingdom

9.4.5.2. Germany

9.4.5.3. France

9.4.5.4. Spain

9.4.5.5. Others

9.5. Middle East and Africa

9.5.1. By Chip Type

9.5.2. By Processing Type

9.5.3. By Application

9.5.4. By Industry

9.5.5. By Country

9.5.5.1. Saudi Arabia

9.5.5.2. UAE

9.5.5.3. Others

9.6. Asia Pacific

9.6.1. By Chip Type

9.6.2. By Processing Type

9.6.3. By Application

9.6.4. By Industry

9.6.5. By Country

9.6.5.1. China

9.6.5.2. Japan

9.6.5.3. India

9.6.5.4. South Korea

9.6.5.5. Taiwan

9.6.5.6. Others

10. COMPETITIVE ENVIRONMENT AND ANALYSIS

10.1. Major Players and Strategy Analysis

10.2. Market Share Analysis

10.3. Mergers, Acquisitions, Agreements, and Collaborations

10.4. Competitive Dashboard

11. COMPANY PROFILES

11.1. NVIDIA Corporation 

11.2. Intel Corporation 

11.3. Google  

11.4. AMD  

11.5. Qualcomm Technologies, Inc. 

11.6. ARM Holdings 

11.7. Graphcore 

11.8. MediaTek 

11.9. Huawei Technologies Co., Ltd. 

11.10. IBM Corporation 

12. APPENDIX

12.1. Currency 

12.2. Assumptions

12.3. Base and Forecast Years Timeline

12.4. Key benefits for the stakeholders

12.5. Research Methodology 

12.6. Abbreviations 

NVIDIA Corporation

Intel Corporation

Google 

AMD 

Qualcomm Technologies, Inc.

ARM Holdings

Graphcore

MediaTek

Huawei Technologies Co., Ltd.

IBM Corporation