The Asia Pacific Machine Learning Chip Market is expected to witness market growth of 22.7% CAGR during the forecast period (2024-2031).
The China market dominated the Asia Pacific Machine Learning Chip Market by country in 2023, and is expected to continue to be a dominant market till 2031; thereby, achieving a market value of $3.33 billion by 2031. The Japan market is registering a CAGR of 21.9% during 2024-2031. Additionally, the India market is expected to showcase a CAGR of 23.6% during 2024-2031.
These chips are essential in the robotics and industrial automation sectors, where they control robotic arms, drones, and other automated systems. These chips enable robots to learn from their environment, adapt to new tasks, and make real-time decisions without human intervention. ML chips are increasingly integrated into smart factories, where they help streamline production processes and improve efficiency.
The adoption of these chips has been accelerating, driven by the growing demand for AI-powered applications across various industries. As the volume of data generated by businesses, devices, and consumers grows exponentially, the demand for efficient data processing solutions becomes more urgent. With their ability to handle large datasets and complex computations, these chips are essential in managing this data deluge. Companies across sectors adopt these chips to enable faster processing and real-time decision-making.
The significant growth in India's BFSI sector and the booming IT industry in China are critical drivers for expanding this market. India's banking sector, renowned for its stability, has witnessed remarkable growth. From FY 16 to FY 21, the percentage of people with bank accounts surged from 53% to 78%. The country boasts over 1.6 lakh bank branches, translating to approximately 15 branches per 100,000 people. The IT industry's expansion is closely tied to adopting ML technologies for data analysis, cybersecurity, automation, and software development. These applications require efficient and high-performance ML chips to handle extensive data processing and sophisticated computational tasks. The escalating growth of China's IT industry thus propels the demand for ML chips, fostering advancements and increasing the market's overall growth trajectory. Thus, the rising BFSI sector in India and the booming IT industry in China are pivotal in driving the growth of the machine learning chip market.
The China market dominated the Asia Pacific Machine Learning Chip Market by country in 2023, and is expected to continue to be a dominant market till 2031; thereby, achieving a market value of $3.33 billion by 2031. The Japan market is registering a CAGR of 21.9% during 2024-2031. Additionally, the India market is expected to showcase a CAGR of 23.6% during 2024-2031.
These chips are essential in the robotics and industrial automation sectors, where they control robotic arms, drones, and other automated systems. These chips enable robots to learn from their environment, adapt to new tasks, and make real-time decisions without human intervention. ML chips are increasingly integrated into smart factories, where they help streamline production processes and improve efficiency.
The adoption of these chips has been accelerating, driven by the growing demand for AI-powered applications across various industries. As the volume of data generated by businesses, devices, and consumers grows exponentially, the demand for efficient data processing solutions becomes more urgent. With their ability to handle large datasets and complex computations, these chips are essential in managing this data deluge. Companies across sectors adopt these chips to enable faster processing and real-time decision-making.
The significant growth in India's BFSI sector and the booming IT industry in China are critical drivers for expanding this market. India's banking sector, renowned for its stability, has witnessed remarkable growth. From FY 16 to FY 21, the percentage of people with bank accounts surged from 53% to 78%. The country boasts over 1.6 lakh bank branches, translating to approximately 15 branches per 100,000 people. The IT industry's expansion is closely tied to adopting ML technologies for data analysis, cybersecurity, automation, and software development. These applications require efficient and high-performance ML chips to handle extensive data processing and sophisticated computational tasks. The escalating growth of China's IT industry thus propels the demand for ML chips, fostering advancements and increasing the market's overall growth trajectory. Thus, the rising BFSI sector in India and the booming IT industry in China are pivotal in driving the growth of the machine learning chip market.
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.)
- Cerebras Systems Inc.
Market Report Segmentation
By Technology
- System-on-Chip (SoC)
- System-in-Package
- Multi-chip Module
- Other Technology
By Chip Type
- GPU Chip
- ASIC Chip
- CPU Chip
- FPGA Chip
- Flash-Based Chip
- Neuromorphic Chip
- Others
By Industry Vertical
- IT & Telecom
- Consumer Electronics
- BFSI
- Retail
- Automotive
- Healthcare
- Media & Advertising
- Robotics Industry
- Others
By Country
- China
- Japan
- India
- South Korea
- Australia
- 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 Machine Learning Chip Market by Technology
Chapter 6. Asia Pacific Machine Learning Chip Market by Chip Type
Chapter 7. Asia Pacific Machine Learning Chip Market by Industry Vertical
Chapter 8. Asia Pacific Machine Learning Chip 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.)
- Cerebras Systems Inc.
Methodology
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