Artificial Intelligence (AI) Chips Market to Grow by USD 902.65 Billion (2025-2029), Driven by AI Chip Innovation for Smartphones, AI Driving Transformation - Technavio

NEW YORK, Jan. 18, 2025 /PRNewswire/ -- Report on how AI is redefining market landscape - The global artificial intelligence (AI) chips market size is estimated to grow by USD 902.65 billion from 2025-2029, according to Technavio. The market is estimated to grow at a CAGR of over 81.2% during the forecast period. Increased focus on developing AI chips for smartphones is driving market growth, with a trend towards convergence of AI and IoT. However, dearth of technically skilled workers for ai chips development poses a challenge. Key market players include Advanced Micro Devices Inc., Baidu Inc., Broadcom Inc., Cerebras, Fujitsu Ltd., Google LLC, Graphcore Ltd., Huawei Technologies Co. Ltd., Intel Corp., International Business Machines Corp., MediaTek Inc., Microchip Technology Inc., NVIDIA Corp., NXP Semiconductors NV, Qualcomm Inc., SambaNova Systems Inc., Samsung Electronics Co. Ltd., SenseTime Group Inc., Taiwan Semiconductor Manufacturing Co. Ltd., and Tesla Inc..

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Market Driver

Artificial Intelligence (AI) is revolutionizing industries from healthcare to retail, finance, and automotive with deep learning and machine learning algorithms. The demand for AI technologies is driving the growth of AI chips market. Companies like Advanced Micro Devices, Nvidia, and Huawei are leading the way with AI chip lines, such as the Trainium2 chip and Ascend 910B chipset. These chips are designed to handle the high computing requirements of AI technologies, including quantum computing and generative AI. Major cloud providers like Microsoft Azure, Amazon Web Services, and Google Cloud are investing in AI data centers to offer AI services to businesses and developers. Edge computing is also gaining popularity for real-time applications, reducing latency and improving data processing efficiency. Energy efficiency is a key consideration for AI chip manufacturers, as AI applications consume vast amounts of power. AI chip lines include CPUs, GPUs, FPGAs, and ASICs, each optimized for specific applications. Ethical concerns around AI use are also driving the development of specific integrated chips for AI applications. AI technologies are being integrated into various industries, from healthcare to manufacturing, with applications ranging from image recognition to cognitive computing. Patent filings for AI technologies are on the rise, with companies seeking to protect their intellectual property. However, system failure and malfunctioning remain concerns, as AI systems can have significant impacts on businesses and individuals. The AI chip market is expected to continue growing, with applications in mobile phones, personal computers, gaming consoles, and embedded systems. The future of AI technologies lies in the integration of AI chips into various devices, from wearable devices to smart homes and connected cars, enabling personalized health, real-time analysis, and more. 

The Internet of Things (IoT) market is experiencing significant growth due to the advantages it offers in various industries such as aerospace and defense, automotive, consumer electronics, healthcare, and more. IoT devices, which include cameras, drones, smart speakers, smartphones, smart TVs, and others, are making decisions based on data received without human intervention. To enable power-efficient data processing and machine learning computation in these devices, AI chips are being integrated. This trend is driving the demand for AI chips in the IoT market, enabling devices to perform complex tasks and improve overall efficiency. 

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 Market Challenges

• Artificial Intelligence (AI) is revolutionizing industries from healthcare to retail, finance, and automotive. However, the increasing demand for AI technologies, including deep learning and machine learning, poses challenges for hardware components like AI chips. Advanced Micro and Nvidia lead the market with their AI chip lines, such as Trainium2 and A100 chip, respectively. These chips power AI algorithms and technologies, enabling applications like image recognition, pose detection, and behavioral patterns analysis. However, developing AI chips comes with challenges. Energy efficiency is crucial as AI applications require high computing power. Quantum computing and highbandwidth memory are potential solutions, but patent filings and system failure risks exist. AI data centers and centralized cloud servers face latency issues, necessitating edge computing and Edge devices. Ethical concerns surrounding AI use also arise. Major cloud providers like Microsoft Azure, Amazon Web Services, and Google Cloud offer AI services, but energy efficiency and latency remain concerns. AI applications in healthcare, retail, finance, and automotive require real-time data processing, making AI chip lines, GPUs, FPGAs, CPUs, ASICs, and DSP essential. The future of AI lies in cognitive computing, machine intelligence, and AI data centers, but challenges persist in ensuring energy efficiency, reliability, and ethical use.
• The AI chips market is witnessing significant expansion due to the potential financial gains that businesses can reap from artificial intelligence. However, the absence of a sufficient workforce with specialized AI knowledge presents a substantial challenge to market growth. Companies must meticulously evaluate the integration of AI, considering its high research and development costs. The scarcity of skilled professionals in this field is currently the most significant barrier for enterprises looking to implement AI in their operations.

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Segment Overview

This artificial intelligence (AI) chips market report extensively covers market segmentation by

1. Product 
• 1.1 ASICs
• 1.2 GPUs
• 1.3 CPUs
• 1.4 FPGAs
2. End-user 
• 2.1 Media and advertising
• 2.2 BFSI
• 2.3 IT and telecommunication
• 2.4 Others
3. Geography 
• 3.1 North America
• 3.2 Europe
• 3.3 APAC
• 3.4 South America
• 3.5 Middle East and Africa
4. Processing Type
5. Application
6. Technology

1.1 ASICs- Artificial Intelligence (AI) chips market is witnessing significant growth due to the increasing adoption of application-specific integrated circuits (ASICs) in data centers. ASICs are customized chips that offer faster performance compared to GPUs and FPGAs. They are specifically designed for parallel processing, making them ideal for AI applications. Google's Tensor Processing Unit (TPU) is a prime example of ASIC-based AI chips. TPU is a network of hardware and software that can learn specific tasks by analyzing large data sets. It is already being used in applications like Google Search and Google Street View. Data centers are incorporating TPUs at the back end of servers to manage data effectively. TPU's instruction set allows TensorFlow programs to be changed, enabling the development of new algorithms. TensorFlow is an open-source machine learning library with a data flow graph structure, where nodes represent arithmetical operations, and edges denote multidimensional arrays. ASIC-based AI chips are expected to continue gaining market share due to their higher performance and speed compared to GPUs, FPGAs, and CPUs.

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Research Analysis

Artificial Intelligence (AI) Chips Market: The global AI Chips Market is experiencing significant growth due to the increasing adoption of AI technologies in various industries such as healthcare, retail, finance, automotive, and IoT devices. AI Chips are specialized hardware components designed to accelerate AI algorithms, including deep learning and machine learning. These chips are essential for powering AI applications in robotics, autonomous vehicles, and high-performance computing systems. The market includes various types of chips such as Specific Integrated Chips (SICs), CPUs, FPGAs, and GPUs. Advanced Micro, Trainium2 chip, and other players are developing innovative AI Chips to address the growing demand for AI hardware. AI Chips are also being integrated into quantum computing systems, cloud, and edge computing infrastructure. The market's growth is driven by the increasing use of AI in various applications, such as generative AI, supercomputers, and highbandwidth memory. However, ethical concerns regarding AI technologies and the need for energy-efficient and cost-effective solutions pose challenges to the market's growth. In summary, the AI Chips Market is poised for significant growth due to the increasing adoption of AI technologies in various industries and the development of specialized hardware components to accelerate AI algorithms. However, ethical concerns and the need for energy-efficient and cost-effective solutions present challenges to the market's growth.

Market Research Overview

Artificial Intelligence (AI) Chips Market: Overview The Artificial Intelligence (AI) Chips Market is a rapidly growing sector that focuses on developing specialized hardware components to support AI algorithms, deep learning, and machine learning applications. These chips are designed to enhance the performance and energy efficiency of AI technologies, including quantum computing, neural networks, and cognitive computing. AI Chips are integral to various industries, including robotics, healthcare, retail, finance, automotive, and manufacturing, where real-time data processing and low latency are essential. The market includes a range of hardware components, such as CPUs, GPUs, FPGAs, ASICs, DSPs, and microcontrollers, each optimized for specific AI applications. Deep learning and machine learning algorithms require high computing power and large amounts of data processing. AI chips, such as the Trainium2 chip, are designed to address these requirements, offering high bandwidth memory and parallel computing capabilities. Advanced AI technologies, such as generative AI and large language models, are driving the demand for more powerful and energy-efficient chips. Edge computing and Edge devices are also gaining popularity, as they enable data processing closer to the source, reducing latency and increasing the speed of real-time applications. Ethical concerns surrounding AI and data privacy are also influencing the market, as companies invest in AI chip lines that prioritize security and data protection. The market is expected to continue growing, driven by the increasing adoption of AI technologies in various industries and the development of new AI applications, such as computer vision, pose detection, and behavioral pattern recognition. Patent filings and system failure or malfunctioning issues are ongoing challenges in the market, as companies race to innovate and improve the performance and reliability of their AI chips. The market is highly competitive, with players such as Nvidia, Ascend, and Microsoft Azure offering a range of AI chip solutions for various applications. In summary, the AI Chips Market is a dynamic and evolving sector, driven by the increasing adoption of AI technologies and the need for specialized hardware components to support their growing demands for high computing power, energy efficiency, and data processing capabilities. The market includes a range of hardware components, from CPUs and GPUs to FPGAs and ASICs, each optimized for specific AI applications and industries, including healthcare, retail, finance, automotive, and manufacturing. Ethical concerns, patent filings, and system reliability are ongoing challenges, but the market is expected to continue growing, driven by the increasing adoption of AI technologies and the development of new applications, such as computer vision, pose detection, and behavioral pattern recognition.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

• Product
• ASICs
• GPUs
• CPUs
• FPGAs
• End-user
• Media And Advertising
• BFSI
• IT And Telecommunication
• Others
• Geography
• North America
• Europe
• APAC
• South America
• Middle East And Africa
• Processing Type
• Application
• Technology

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

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