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Artificial Intelligence (AI) Semiconductor Market to Hit USD 174.48 Billion by 2032, at a CAGR of 15.2% | SNS Insider

2025-02-28 14:32:06 英文原文

作者：SNS Insider pvt ltd

Austin, Feb. 28, 2025 (GLOBE NEWSWIRE) -- AI in Semiconductor Market Size & Growth Insights:

According to the SNS Insider,“The Artificial Intelligence (AI) in Semiconductor Market Size was valued at USD 48.96 Billion in 2023 and is expected to reach USD 174.48 Billion by 2032 and grow at a CAGR of 15.2% over the forecast period 2024-2032.”

The market can gain further depth with data on AI adoption across industries, such as healthcare, where AI-driven diagnostics are becoming mainstream, and the automotive sector, where AI chips are increasingly integrated into autonomous vehicles. The consumer electronics industry is also witnessing significant AI penetration, enhancing smart device capabilities. Additionally, insights into R&D investment in AI chip development, the growing number of AI-focused startups, and the volume of AI semiconductor patents filed provide a clearer picture of innovation trends. These factors collectively shape the market’s trajectory, reflecting the rapid evolution of AI technologies and their expanding influence. Understanding the pace of AI integration and investment levels across sectors helps in assessing future market opportunities and competitive dynamics, making it crucial to analyze industry-specific adoption rates and technological advancements.

Get a Sample Report of Artificial Intelligence (AI) in Semiconductor Market Forecast @ https://www.snsinsider.com/sample-request/5641 

Leading Market Players with their Product Listed in this Report are:

  • Nvidia Corporation (Nvidia A100 Tensor Core GPU, Nvidia Jetson AGX Orin)
  • Intel Corporation (Intel Gaudi2 AI Accelerator, Intel Xeon Scalable Processors)
  • Advanced Micro Devices, Inc. (AMD Instinct MI300, AMD Ryzen AI)
  • Xilinx, Inc. (Xilinx Versal AI Core, Xilinx Alveo U50)
  • Google Inc. (Alphabet Inc.) (Google TPU v5e, Google Edge TPU)
  • Qualcomm Incorporated (Qualcomm Cloud AI 100, Qualcomm Snapdragon AI Engine)
  • IBM Corporation (IBM AIU (AI Unit), IBM Watson Machine Learning Accelerator)
  • Samsung Electronics Co., Ltd. (Samsung Exynos AI, Samsung HBM-PIM)
  • Huawei Technologies Co., Ltd. (Huawei Ascend 910, Huawei Kunpeng AI Processor)
  • Amazon Web Services, Inc. (AWS Inferentia, AWS Trainium)
  • Broadcom Inc. (Broadcom Trident AI Switch, Broadcom Jericho3-AI)
  • Texas Instruments (TI TDA4VM Processor, TI AM62A AI Vision Processor)
  • MediaTek Inc. (MediaTek Dimensity AI, MediaTek NeuroPilot)
  • Arm Holdings (Arm Cortex-M85, Arm Ethos-U65)
  • Synopsys, Inc. (Synopsys DSO.ai, Synopsys ARC EV Processors).

Artificial Intelligence (AI) Semiconductor Market Report Scope:

Report AttributesDetails
Market Size in 2023USD 48.96 Billion
Market Size by 2032USD 174.48 Billion
CAGRCAGR of 15.2% From 2024 to 2032
Report Scope & CoverageMarket Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segmentation• By Chip Type (Central Processing Units (CPUs), Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Tensor Processing Units (TPUs))
• By Application (AI Training, AI Inference, Edge AI, Cloud AI, Others)
• By End-use (Healthcare, Automotive, Consumer Electronics, Industrial Automation, Banking and Finance, Others)
Key Drivers• Expanding Adoption of AI Applications in Key Industries Fuels Growth of the Artificial Intelligence (AI) in Semiconductor Market.

• Strategic Partnerships and Collaborations Drive Innovation in AI Chip Development for the Semiconductor Market.

Do you Have any Specific Queries or Need any Customize Research on Artificial Intelligence (AI) in Semiconductor Market, Request for Analyst Call @ https://www.snsinsider.com/request-analyst/5641 

Key Industry Segmentation Analysis

By Chip Type, Central Processing Units (CPUs) Dominating and Graphics Processing Units (GPUs) Fastest Growing

In 2023, Central Processing Units (CPUs) dominated the AI semiconductor market, holding the largest revenue share of 46%, with the growing use of AI-based applications in various businesses. Intel and AMD dominate this segment, with years of innovation under their belts in the area of AI-optimized CPUs, Intel’s Xeon Scalable Processors series and AMD’s Ryzen AI chips are just two examples of their growing expertise in increasing machine learning and data processing efficiency.

Graphics Processing Units (GPUs) are witnessing rapid expansion, with a projected CAGR of 16.64%, due to their ability to run deep learning and neural networks in parallel. Nvidia, the industry leader in this segment, has extended its dominance through AI-oriented products, such as the A100 and H100 Tensor Core GPUs for high-performance AI workloads, which are complemented by its Jetson AGX Orin platform for real-time AI at the edge— in robotics and autonomous systems especially.

By Application, AI Training segment Dominating and Edge AI Fastest Growing

In 2023, the AI Training segment led the AI semiconductor market with the largest revenue share of 39%, due to which attributed to the growing need for high-performance hardware for training complex AI models. Training AI requires complex algorithms on large datasets, which is why special chips like GPUs, TPUs, and FPGAs are needed. Exciting developments are formulating in this space, led by Nvidia, for example with their A100 and H100 Tensor Core GPUs, and Google, with their TPU v4.

The Edge AI segment is fastest growing with a projected CAGR of 17.19%, with a growing demand for low latency, AI-enabled devices that reduce dependence on cloud computing. Industry leaders such as Qualcomm and Nvidia have created advanced solutions such as the Qualcomm Snapdragon AI Engine and Nvidia’s Jetson Orin platform that can conduct real-time AI inferencing for use in maritimes, smart boats, autonomous vehicles, smart cameras, and general IoT applications.

By End Use, Consumer Electronics Dominating and Automotive Segment Fastest Growing

In 2023, the Consumer Electronics segment dominated the AI semiconductor market, securing the largest revenue share of 35%, due to the growing use of AI in smartphones, wearables, and smart home appliances. AI chips have become essential to powering capabilities like voice and facial recognition and real-time image processing, which improve the user experience. Top-tier brands such as Apple and Samsung have made their way into integrating AI-optimized processors such as the A16 Bionic chip and Exynos AI chips into their devices, bringing intelligent voice assistants and personalized functionalities.

The Automotive segment is projected to grow at the fastest rate, with a CAGR of 16.77%, driven by rising adoption of AI in Autonomous Vehicles and ADAS (Advanced Driver Assistance Systems). AI chips allow for the processing of data from LiDAR, radar, and cameras for safe and efficient real-time driving, and thus, AI semiconductors are crucial in the evolution of smart mobility.

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Regional Dynamics and Growth Trends in the AI Semiconductor Market: APAC Dominance and North America's Rapid Expansion

In 2023, the Asia Pacific (APAC) region dominated the Artificial Intelligence (AI) Semiconductor Market, capturing approximately 43% of the market share. This dominance is largely due to the presence of leading semiconductor manufacturers such as Samsung Electronics, TSMC, and Nvidia, along with strong demand for AI technologies across industries like consumer electronics, automotive, and healthcare. China and South Korea play a pivotal role, driving innovations in AI-powered consumer electronics and automated manufacturing.

North America emerged as the fastest-growing region in the AI Semiconductor Market in 2023, with a projected compound annual growth rate (CAGR) of 16.8% during the forecast period. This surge is driven by extensive AI research and development efforts led by tech giants and startups in the U.S. Companies like Nvidia, Intel, and Google are spearheading the development of advanced GPUs, TPUs, and specialized processors tailored for AI training and inference. For example, Nvidia’s H100 Tensor Core GPUs have become a key player in AI workloads, seeing widespread use in data centers and research facilities.

Table of Contents - Major Points

1. Introduction

2. Executive Summary

3. Research Methodology

4. Market Dynamics Impact Analysis

5. Statistical Insights and Trends Reporting

5.1 Research and Development (R&D) Expenditure (2023)

5.2 AI-Enabled Device Penetration

5.3 Energy Efficiency Improvements (2023)

5.4 Global Semiconductor Supply Chain Data

6.  Competitive Landscape

7. Artificial Intelligence (AI) in Semiconductor Market Segmentation, by Chip Type

8. Artificial Intelligence (AI) in Semiconductor Market Segmentation, by Application

9. Artificial Intelligence (AI) in Semiconductor Market Segmentation, by End-use

10. Regional Analysis

11. Company Profiles

12. Use Cases and Best Practices

13. Conclusion

Access More Research Insights of AI Semiconductor Market Growth & Outlook Report 2024-2032@ https://www.snsinsider.com/reports/artificial-intelligence-in-semiconductor-market-5641 

[For more information or need any customization research mail us at info@snsinsider.com]

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

 

            

            

          

          

            
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摘要
                          

            

              The Artificial Intelligence (AI) Semiconductor Market is witnessing significant growth driven by advancements in AI technology and increasing demand across various sectors such as consumer electronics, automotive, healthcare, and more. Key players like Nvidia, Intel, Google, Samsung Electronics, Qualcomm, and others are at the forefront of developing specialized processors tailored for AI applications.

### Key Highlights:

1. **Market Dynamics:**
   - **Drivers:** Rising adoption of AI in consumer electronics, autonomous vehicles, ADAS (Advanced Driver Assistance Systems), healthcare diagnostics, and smart manufacturing.
   - **Restraints:** High costs associated with R&D and the need for advanced cooling solutions to manage heat dissipation from powerful processors.

2. **Regional Analysis:**
   - **Asia Pacific (APAC):** Dominates the market due to strong demand in consumer electronics and automotive industries, coupled with significant investments by leading semiconductor manufacturers like Samsung Electronics and TSMC.
   - **North America:** Fastest-growing region driven by extensive R&D efforts from tech giants such as Nvidia, Intel, and Google.

3. **Chip Type Segmentation:**
   - **GPUs (Graphics Processing Units):** Leading segment due to their versatility in handling complex AI algorithms and machine learning tasks.
   - **TPUs (Tensor Processing Units):** Specialized processors designed for high-speed training and inference of deep neural networks.
   - **FPGAs (Field-Programmable Gate Arrays):** Increasingly important for applications requiring flexibility and reconfigurability.

4. **Application Segmentation:**
   - **AI Training:** Dominated by GPUs, with advancements in TPUs from companies like Google.
   - **Edge AI Inference:** Growing rapidly due to demand for low-latency devices that perform real-time processing without relying on cloud computing.

5. **End-Use Segmentation:**
   - **Consumer Electronics:** Largest market segment driven by integration of AI chips in smartphones, wearables, and smart home appliances.
   - **Automotive:** Fastest-growing segment due to increasing adoption of ADAS and autonomous driving technologies.

### Key Players and Innovations:

1. **Nvidia:**
   - Released the H100 Tensor Core GPUs for high-performance data center workloads in AI training and inference.
   
2. **Intel:**
   - Developing integrated chipsets with built-in AI capabilities for edge computing devices.

3. **Google:**
   - Continues to innovate TPUs, enhancing performance for deep learning applications.

4. **Qualcomm:**
   - Focused on Edge AI solutions like the Snapdragon Neural Processing Engine (SNPE) for smartphones and IoT devices.

5. **Samsung Electronics:**
   - Integrating advanced AI processing capabilities into their Exynos chipsets for improved smartphone functionalities.

### Future Outlook:

The market is expected to continue expanding due to:
- Increasing demand for smart, connected devices.
- Advancements in machine learning and deep neural networks.
- Growing importance of real-time data processing and analysis in various industries.
- Rising investments by tech giants and startups in R&D for AI semiconductor technologies.

### Strategic Recommendations:

1. **Investment in R&D:**
   - Focus on developing more efficient, energy-saving processors tailored for specific AI applications.
   
2. **Partnerships and Collaborations:**
   - Form strategic alliances with leading tech companies to accelerate innovation and market penetration.
   
3. **Regional Expansion:**
   - Target emerging markets like India and Southeast Asia where there is high demand for AI-driven consumer electronics.

4. **Focus on Edge Computing:**
   - Develop processors optimized for edge computing to address growing concerns over latency and data privacy in cloud-based systems.

### Conclusion:

The Artificial Intelligence (AI) Semiconductor Market presents significant opportunities for growth and innovation across various sectors. Leading companies are continuously pushing the boundaries of what is possible with AI technology, driving advancements that will shape the future of industries ranging from consumer electronics to automotive and healthcare.
            

        


        

            
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