The Asia Pacific Edge Artificial Intelligence Chips Market is expected to witness market growth of 33.9% CAGR during the forecast period (2024-2031).
The China market dominated the Asia Pacific Edge Artificial Intelligence Chips Market by country in 2023, and is expected to continue to be a dominant market till 2031; thereby, achieving a market value of $12.59 billion by 2031. The Japan market is exhibiting a CAGR of 33.1% during 2024-2031. Additionally, the India market is expected to experience a CAGR of 34.8% during 2024-2031.
Edge AI chips are found in smartphones, smart speakers, and home automation devices in consumer electronics. These chips facilitate features like voice recognition, facial recognition, and augmented reality, making devices more intuitive and interactive. For example, smartphones with AI chips can offer enhanced camera functionalities, such as scene detection and image stabilization. Edge AI chips are crucial for predictive maintenance, quality control, and operational optimization in the industrial sector. They enable machines to process data locally and make real-time decisions, reducing downtime and improving efficiency. For example, in manufacturing, AI chips can detect product defects on the assembly line, ensuring higher-quality output.
The adoption of edge AI chips is gaining momentum as industries recognize their potential to revolutionize operations and enhance performance. One of the primary reasons for the widespread adoption of edge AI chips is their scalability and flexibility. These chips can be integrated into various devices and systems, allowing businesses to scale their AI capabilities according to their needs. This flexibility is particularly beneficial for industries with diverse operational requirements.
As India transitions towards Industry 4.0, the use of AI and IoT in manufacturing processes will increase. Edge AI chips are pivotal in facilitating smart manufacturing systems, which include automation, robotics, and predictive analytics. These chips enable real-time monitoring, decision-making, and process optimization at the edge, allowing Indian manufacturers to enhance productivity and reduce operational costs. The rising domestic demand for consumer electronics, coupled with the rapid expansion of the electronics manufacturing sector, creates a fertile ground for the growth of edge artificial intelligence chips market in India. In Conclusion, China and India are on a path to revolutionizing their economies through advanced technologies like 5G, AI, and IoT.
The China market dominated the Asia Pacific Edge Artificial Intelligence Chips Market by country in 2023, and is expected to continue to be a dominant market till 2031; thereby, achieving a market value of $12.59 billion by 2031. The Japan market is exhibiting a CAGR of 33.1% during 2024-2031. Additionally, the India market is expected to experience a CAGR of 34.8% during 2024-2031.
Edge AI chips are found in smartphones, smart speakers, and home automation devices in consumer electronics. These chips facilitate features like voice recognition, facial recognition, and augmented reality, making devices more intuitive and interactive. For example, smartphones with AI chips can offer enhanced camera functionalities, such as scene detection and image stabilization. Edge AI chips are crucial for predictive maintenance, quality control, and operational optimization in the industrial sector. They enable machines to process data locally and make real-time decisions, reducing downtime and improving efficiency. For example, in manufacturing, AI chips can detect product defects on the assembly line, ensuring higher-quality output.
The adoption of edge AI chips is gaining momentum as industries recognize their potential to revolutionize operations and enhance performance. One of the primary reasons for the widespread adoption of edge AI chips is their scalability and flexibility. These chips can be integrated into various devices and systems, allowing businesses to scale their AI capabilities according to their needs. This flexibility is particularly beneficial for industries with diverse operational requirements.
As India transitions towards Industry 4.0, the use of AI and IoT in manufacturing processes will increase. Edge AI chips are pivotal in facilitating smart manufacturing systems, which include automation, robotics, and predictive analytics. These chips enable real-time monitoring, decision-making, and process optimization at the edge, allowing Indian manufacturers to enhance productivity and reduce operational costs. The rising domestic demand for consumer electronics, coupled with the rapid expansion of the electronics manufacturing sector, creates a fertile ground for the growth of edge artificial intelligence chips market in India. In Conclusion, China and India are on a path to revolutionizing their economies through advanced technologies like 5G, AI, and IoT.
List of Key Companies Profiled
- Advanced Micro Devices Inc.
- Samsung Electronics Co., Ltd. (Samsung Group)
- NXP Semiconductors N.V.
- Qualcomm Incorporated (Qualcomm Technologies, Inc.)
- NVIDIA Corporation
- Intel Corporation
- Infineon Technologies AG
- IBM Corporation
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Apple, Inc.
Market Report Segmentation
By Function
- Inference
- Training
By Chipset
- CPU
- ASIC
- GPU
- Other Chipset
By Device
- Consumer Devices
- Enterprise Devices
By Country
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Asia Pacific Edge Artificial Intelligence Chips Market by Function
Chapter 6. Asia Pacific Edge Artificial Intelligence Chips Market by Chipset
Chapter 7. Asia Pacific Edge Artificial Intelligence Chips Market by Device
Chapter 8. Asia Pacific Edge Artificial Intelligence Chips Market by Country
Chapter 9. Company Profiles
Companies Mentioned
- Advanced Micro Devices Inc.
- Samsung Electronics Co., Ltd. (Samsung Group)
- NXP Semiconductors N.V.
- Qualcomm Incorporated (Qualcomm Technologies, Inc.)
- NVIDIA Corporation
- Intel Corporation
- Infineon Technologies AG
- IBM Corporation
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Apple, Inc.
Methodology
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