AI Chipsets Market Size, Share, Forecast, & Trends Analysis by Offering, Technology, Vertical

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AI Chipsets Market by Offering (Hardware and Software), Technology (Machine Learning, Natural Language Processing, Context-aware Processing), Vertical (Automotive & Transportation, Consumer Electronics, Healthcare), and Geography-Global Forecast to 2031.

The research report titled 'AI Chipsets Market by Offering (Hardware and Software), Technology (Machine Learning, Natural Language Processing, Context-aware Processing), Vertical (Automotive & Transportation, Consumer Electronics, Healthcare), and Geography-Global Forecast to 2031' provides an in-depth analysis of global AI chipsets market across five major geographies and emphasizes on the current market trends, market sizes, market shares, recent developments, and forecasts till 2031.

The global AI chipsets market is projected to reach $260.2 billion by 2031, at a CAGR of 27.2% from 2024-2031.

The growth of the AI chipsets market is driven by the rapid advancements in AI technology, growing demand for edge computing, and the rise of autonomous systems and robotics. However, the complexity of AI algorithms and the lack of technical expertise and AI standards may restrain the growth of this market.

Furthermore, the increasing demand for AI-enabled devices and the development of smart robots are expected to offer significant growth opportunities for players operating in the AI chipsets market. However, the complexity of AI workloads and the high power consumption of AI chipsets may hinder the growth of this market.

Integration of legacy systems with modern AI technology and the proliferation of autonomous vehicles are prominent trends in this market.

The global AI chipsets market is segmented into offering (hardware {processor [graphics processing units, field-programmable gate arrays, application-specific integrated circuits, central processing units, and digital signal processor], memory, and network} and software), technology (machine learning {deep learning, supervised learning, unsupervised learning, reinforcement learning, and other machine learning types}, natural language processing, context-aware processing, computer vision, predictive analysis, and other technologies), and vertical (automotive & transportation {connected vehicles, smart infotainment, freight information system, smart traffic management, smart parking, passenger information management, and other automotive & transportation applications}, smart factories {asset monitoring, workforce management, robotics & automation, inventory management, and other smart factory applications}, smart cities {waste management, smart utilities, smart building, smart public safety, smart education, and other smart city applications}, smart retail {store analytics, smart dressing rooms, video surveillance & safety, and other smart retail applications}, consumer electronics {smartphones, smart speakers, wearable devices, gaming consoles, and other consumer electronics applications}, healthcare {medical imaging, clinical decision support systems, remote patient monitoring, and other healthcare applications}, and other verticals). The study also evaluates industry competitors and analyzes the market at the regional and country levels.

Based on offering, the global AI chipsets market is segmented into hardware and software. Further, the hardware market is segmented into processors, memory, and network. The processors segment is subsegmented into graphics processing units, field-programmable gate arrays, application-specific integrated circuits, central processing units, and digital signal processors. In 2024, the hardware segment is expected to account for the larger share of 76% of the global AI chipsets market. In 2024, the graphics processing units segment is expected to account for the largest share of 47% of the global AI chipset processors market. The growth of the AI chipsets hardware market is driven by the growing integration of AI in various sectors such as healthcare, automotive, retail, and manufacturing. These chipsets are essential for processing the large volumes of data required for AI algorithms to function effectively. The proliferation of AI-driven devices such as smartphones, smart speakers, autonomous vehicles, and smart cameras is fueling the demand for AI chipsets. These devices require specialized hardware to deliver AI-powered features and functionalities effectively.

Furthermore, various key players are launching various AI chipsets. For instance:

In March 2024, NVIDIA Corporation (U.S.) launched its latest generation of AI chips and software designed to power AI models.
In March 2024, Cerebras Systems Inc. (U.S.) launched a third-generation AI processor. The WSE-3 chip doubles the performance of its predecessor, 56 times larger than the largest GPU, and features 1.2 trillion transistors and 400,000 computing cores.

Additionally, the hardware segment is projected to register the highest CAGR during the forecast period.

Based on technology, the global AI chipsets market is segmented into machine learning, natural language processing, context-aware processing, computer vision, predictive analysis, and other technologies. Further, the machine learning market is segmented into deep learning, supervised learning, unsupervised learning, reinforcement learning, and other machine learning types. In 2024, the machine learning segment is expected to account for the largest share of 53.0% of the global AI chipsets market. Machine learning enables AI chipsets to adapt to changing workloads and environments. Through techniques like dynamic voltage and frequency scaling (DVFS) or adaptive clocking, chipsets can adjust their operating parameters in real time based on workload characteristics, leading to improved performance and power efficiency.

Moreover, machine learning algorithms can be used to detect and mitigate hardware faults in AI chipsets. By analyzing sensor data and performance metrics, machine learning models can identify signs of hardware degradation or failure and take proactive measures to ensure reliability and uptime. These benefits drive the demand for AI chipsets for machine learning applications.

However, the natural language processing segment is projected to register the highest CAGR during the forecast period. This segment's growth is driven by the benefits of integrating NLP into AI chipsets. This process supports edge computing architectures, where data processing occurs locally on devices rather than in centralized data centers. This reduces reliance on cloud services and minimizes latency, making NLP applications more responsive and efficient. Moreover, AI chipsets with embedded NLP capabilities can operate effectively in diverse environmental conditions, including situations with limited resources or challenging operating environments. This robustness ensures reliable performance across various use cases and deployment scenarios.

Based on vertical, the global AI chipsets market is segmented into automotive & transportation, smart factories, smart cities, smart retail, consumer electronics, healthcare, and other verticals. In 2024, the consumer electronics segment is expected to account for the largest share of 59.0% of the global AI chipsets market. This segment's large market share can be attributed to the proliferation of IoT devices and connected ecosystems that drive the demand for AI chipsets in consumer electronics. These chipsets enable devices to analyze sensor data, communicate with other devices, and make intelligent decisions autonomously. AI chipsets enable consumer electronics products to offer personalized and immersive user experiences, and by analyzing user behavior, preferences, and contextual data, these chipsets can tailor product functionalities, recommendations, and interactions to individual users, enhancing satisfaction and engagement.

However, the healthcare segment is projected to register the highest CAGR during the forecast period. AI chipsets support the advancement of precision medicine and genomics by analyzing vast genomic datasets and identifying genetic variations associated with diseases and treatment responses. These chipsets enable healthcare providers to tailor medical treatments and interventions to individual patients based on their genetic profiles, leading to more personalized and effective care. Moreover, AI chipsets accelerate the drug discovery and development process by analyzing molecular structures, predicting drug interactions, and identifying potential drug candidates. These chipsets enable pharmaceutical companies to expedite the drug discovery pipeline, reduce development costs, and bring new therapies to market more quickly, addressing unmet medical needs. These benefits are expected to drive the demand for AI chipsets in the healthcare sector during the forecast period.

Based on geography, the AI chipsets market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. In 2024, North America is expected to account for the largest share of 46.0% of the global AI chipsets market. In the U.S., there are various semiconductor companies, research institutions, and technology giants. These companies have established themselves as pioneers in AI chip development and have made significant contributions to the field. Their expertise and research initiatives have propelled the growth of the market in North America. Moreover, companies in North America invest heavily in research and development (R&D) to maintain their competitive edge in the global AI chipsets market. These investments fuel innovation in semiconductor design, manufacturing processes, and AI algorithms, leading to the development of more advanced and efficient chipsets.

However, the market in Asia-Pacific is projected to register the highest CAGR of 30.0% during the forecast period. Asia-Pacific region has a large and diverse market with increasing demand for AI-powered applications in sectors such as healthcare, automotive, manufacturing, finance, retail, and consumer electronics. The region has a diverse startup ecosystem with a growing number of AI startups specializing in chip design, semiconductor manufacturing, and AI applications. These startups drive innovation, competition, and collaboration in the AI chipsets market, contributing to market growth.

Moreover, various state & regional governments and private enterprises in the Asia-Pacific region are investing heavily in AI research, development, and infrastructure. Initiatives such as China's "Made in China 2025", India's "India AI Mission," and Japan's "Society 5.0" aim to accelerate the adoption of AI technologies, including AI chipsets, across various industries.

The key players operating in the global AI chipsets market include Advanced Micro Devices, Inc. (U.S.), Amazon.com, Inc. (U.S.), Baidu, Inc. (China), Broadcom Inc. (U.S.), Google LLC (U.S.), International Business Machines Corporation (U.S.), MediaTek Inc. (Taiwan), Intel Corporation (U.S.), Micron Technology, Inc. (U.S.), Microsoft Corporation (U.S.), NVIDIA Corporation (U.S.), QUALCOMM Incorporated (U.S.), Samsung Securities Co., Ltd. (South Korea), Toshiba Corporation (Japan), and SoftBank Group Corp. (Japan).

Key Questions Answered in the Report:

What are the high-growth market segments in terms of offering, technology, and vertical?
What is the historical market size for the global AI chipsets market?
What are the market forecasts and estimates for 2024-2031?
What are the major drivers, restraints, opportunities, challenges, and trends in the global AI chipsets market?
Who are the major players in the global AI chipsets market, and what are their market shares?
What is the competitive landscape like?
What are the recent developments in the global AI chipsets market?
What are the different strategies adopted by major market players?
What are the trends and high-growth countries?
Who are the local emerging players in the global AI chipsets market, and how do they compete with other players?

Scope of the Report:

AI Chipsets Market Assessment-by Offering

Hardware
- Processors
Graphics Processing Units (GPUs)
Field-programmable Gate Arrays (FPGAs)
Application-specific Integrated Circuits (ASICs)
Central Processing Units (CPUs)
Digital Signal Processor (DSP)
- Memory
- Network
Software

AI Chipsets Market Assessment-by Technology

Machine Learning
- Deep Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Other Machine Learning Types
Natural Language Processing
Context-aware Processing
Computer Vision
Predictive Analysis
Other Technologies

AI Chipsets Market Assessment-by Vertical

Automotive & Transportation
- Connected Vehicles
- Smart Infotainment
- Freight Information System
- Smart Traffic Management
- Smart Parking
- Passenger Information Management
- Other Automotive & Transportation Applications
Smart Factories
- Asset monitoring
- Workforce Management
- Robotics & Automation
- Inventory Management
- Other Smart Factory Applications
Smart Cities
- Waste Management
- Smart Utilities
- Smart Building
- Smart Public Safety
- Smart Education
- Other Smart City Applications
Smart Retail
- Store Analytics
- Smart Dressing Rooms
- Video Surveillance & Safety
- Other Smart Retail Applications
Consumer Electronics
- Smartphones
- Smart Speakers
- Wearable Devices
- Gaming Consoles
- Other Consumer Electronics Applications
Healthcare
- Medical Imaging
- Clinical Decision Support Systems
- Remote Patient Monitoring
- Other Healthcare Applications
Other Verticals

AI Chipsets Market Assessment-by Geography

North America
- U.S.
- Canada
Europe
- Germany
- U.K.
- France
- Italy
- Spain
- Netherlands
- Switzerland
- Sweden
- Denmark
- Rest of Europe
Asia-Pacific
- China
- Japan
- India
- South Korea
- Australia & New Zealand
- Indonesia
- Thailand
- Vietnam
- Malaysia
- Singapore
- Rest of Asia- Pacific
Latin America
- Mexico
- Brazil
- Rest of Latin America
Middle East & Africa
- UAE
- Israel
- Rest of Middle East & Africa

Product Code: MRICT - 1041152

1. Introduction

1.1 Market Definition & Scope
1.2 Currency & Limitations
- 1.2.1 Currency
- 1.2.2 Limitations

2. Research Methodology

2.1 Research Approach
2.2 Data Collection & Validation Process
- 2.2.1 Secondary Research
- 2.2.2 Primary Research/Interviews with Key Opinion Leaders from the Industry
2.3 Market Sizing and Forecasting
- 2.3.1 Market Size Estimation Approach
- 2.3.2 Growth Forecast Approach
2.4 Assumptions for the Study

3. Executive Summary

3.1 Market Overview
3.2 Market Analysis, by Offering
3.3 Market Analysis, by Technology
3.4 Market Analysis, by Vertical
3.5 Market Analysis, by Geography
3.6 Competitive Analysis

4. Market Insights

4.1 Overview
4.2 Factors Affecting Market Growth
- 4.2.1 Drivers
  - 4.2.1.1 Rapid Advancements in AI Technology
  - 4.2.1.2 Growing Demand for Edge Computing
  - 4.2.1.3 Rise of Autonomous Systems and Robotics
- 4.2.2 Restraints
  - 4.2.2.1 Complexity of AI Algorithms
  - 4.2.2.2 Lack of Technical Expertise and AI Standards
- 4.2.3 Opportunities
  - 4.2.3.1 Increasing Demand for AI-enabled Devices
  - 4.2.3.2 Development of Smart Robots
- 4.2.4 Challenges
  - 4.2.4.1 Complexity of AI Workloads
  - 4.2.4.2 High Power Consumption of AI Chipsets
- 4.2.5 Trends
  - 4.2.5.1 Integration of Legacy Systems with Modern AI Technology
  - 4.2.5.2 Proliferation of Autonomous Vehicles
4.3 Case Studies
4.4 Value Chain Analysis
4.5 Porter's Five Forces Analysis
- 4.5.1 Bargaining Power of Buyers
- 4.5.2 Bargaining Power of Suppliers
- 4.5.3 Threat of Substitutes
- 4.5.4 Threat of New Entrants
- 4.5.5 Degree of Competition

5. Global AI Chipsets Market, by Offering

5.1 Overview
5.2 Hardware
- 5.2.1 Processors
  - 5.2.1.1 Graphics Processing Units (GPUs)
  - 5.2.1.2 Field-programmable Gate Arrays (FPGAs)
  - 5.2.1.3 Application-specific Integrated Circuits (ASICs)
  - 5.2.1.4 Central Processing Units (CPUs)
  - 5.2.1.5 Digital Signal Processor (DSP)
- 5.2.2 Memory
- 5.2.3 Network
5.3 Software

6. Global AI Chipsets Market, by Technology

6.1 Overview
6.2 Machine Learning
- 6.2.1 Deep Learning
- 6.2.2 Supervised Learning
- 6.2.3 Unsupervised Learning
- 6.2.4 Reinforcement Learning
- 6.2.5 Other Machine Learning Types
6.3 Natural Language Processing
6.4 Context-aware Processing
6.5 Computer Vision
6.6 Predictive Analysis
6.7 Other Technologies

7. Global AI Chipsets Market, by Vertical

7.1 Overview
7.2 Automotive & Transportation
- 7.2.1 Connected Vehicles
- 7.2.2 Smart Infotainment
- 7.2.3 Freight Information System
- 7.2.4 Smart Traffic Management
- 7.2.5 Smart Parking
- 7.2.6 Passenger Information Management
- 7.2.7 Other Automotive & Transportation Applications
7.3 Smart Factories
- 7.3.1 Asset monitoring
- 7.3.2 Workforce Management
- 7.3.3 Robotics & Automation
- 7.3.4 Inventory Management
- 7.3.5 Other Smart Factory Applications
7.4 Smart Cities
- 7.4.1 Waste Management
- 7.4.2 Smart Utilities
- 7.4.3 Smart Building
- 7.4.4 Smart Public Safety
- 7.4.5 Smart Education
- 7.4.6 Other Smart City Applications
7.5 Smart Retail
- 7.5.1 Store Analytics
- 7.5.2 Smart Dressing Rooms
- 7.5.3 Video Surveillance & Safety
- 7.5.4 Other Smart Retail Applications
7.6 Consumer Electronics
- 7.6.1 Smartphones
- 7.6.2 Smart Speakers
- 7.6.3 Wearable Devices
- 7.6.4 Gaming Consoles
- 7.6.5 Other Consumer Electronics Applications
7.7 Healthcare
- 7.7.1 Medical Imaging
- 7.7.2 Clinical Decision Support Systems
- 7.7.3 Remote Patient Monitoring
- 7.7.4 Other Healthcare Applications
7.8 Other Verticals

8. AI Chipsets Market, by Geography

8.1 North America
- 8.1.1 U.S.
- 8.1.2 Canada
8.2 Europe
- 8.2.1 Germany
- 8.2.2 U.K.
- 8.2.3 France
- 8.2.4 Italy
- 8.2.5 Spain
- 8.2.6 Netherlands
- 8.2.7 Switzerland
- 8.2.8 Sweden
- 8.2.9 Denmark
- 8.2.10 Rest of Europe
8.3 Asia-Pacific
- 8.3.1 China
- 8.3.2 Japan
- 8.3.3 India
- 8.3.4 South Korea
- 8.3.5 Australia & New Zealand
- 8.3.6 Indonesia
- 8.3.7 Thailand
- 8.3.8 Vietnam
- 8.3.9 Malaysia
- 8.3.10 Singapore
- 8.3.11 Rest of Asia- Pacific
8.4 Latin America
- 8.4.1 Mexico
- 8.4.2 Brazil
- 8.4.3 Rest of Latin America
8.5 Middle East & Africa
- 8.5.1 UAE
- 8.5.2 Israel
- 8.5.3 Rest of Middle East & Africa

9. Global AI Chipsets Market - Competitive Landscape

9.1 Overview
9.2 Key Growth Strategies
- 9.2.1 Market Differentiators
- 9.2.2 Synergy Analysis: Major Deals & Strategic Alliances
9.3 Competitive Dashboard
- 9.3.1 Industry Leader
- 9.3.2 Market Differentiators
- 9.3.3 Vanguards
- 9.3.4 Contemporary Stalwarts
9.4 Vendor Market Positioning
9.5 Market Share Analysis

10. Company Profiles

10.1 Advanced Micro Devices Inc.
10.2 Amazon.com Inc.
10.3 Baidu Inc.
10.4 Broadcom Limited
10.5 Google LLC
10.6 International Business Machines Corporation
10.7 MediaTek Inc.
10.8 Intel Corporation
10.9 Micron Technology
10.10 Microsoft Corporation
10.11 NVIDIA Corporation
10.12 Qualcomm Technologies, Inc.
10.13 Samsung Electronics
10.14 Toshiba Corporation
10.15 Softbank Group

(Note: SWOT Analysis of the Top 5 Companies Will Be Provided)

11. Appendix

11.1 Available Customization
11.2 Related Reports