Artificial Intelligence (AI) Chips Market to Grow by USD 902.6 Billion by 2029, Driven by AI-Powered Smartphone Chips - Report on How AI is Redefining the Market Landscape - Technavio

NEW YORK, Feb. 3, 2025 /PRNewswire/ -- Report with market evolution powered by AI - The global artificial intelligence (AI) chips market size is estimated to grow by USD 902.6 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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              Artificial Intelligence (AI) Chips Market Scope



     Report Coverage                                            
     Details



     Base year                                                                                                                                                           2024



     Historic period                                            
     2019 - 2023



     Forecast period                                            
     2025-2029



     Growth momentum & CAGR                                                                                                                     Accelerate at a CAGR of 81.2%



     Market growth 2025-2029                                    
     USD 902649.3 million



     Market structure                                           
     Fragmented



     YoY growth 2022-2023 (%)                                                                                                                                           61.7



     Regional analysis                                          
     North America, Europe, APAC, South America, and Middle East and Africa



     Performing market contribution                                                                                                                      North America at 42%



     Key countries                                              
     US, Canada, China, UK, Germany, France, Japan, Italy, India, and Brazil



     Key companies profiled                                       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.

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 Trainium2 and A100 chip, designed for high computing and parallel processing. Quantum computing and generative AI are the next frontiers. Hardware components like CPUs, GPUs, FPGAs, and ASICs are essential for AI technologies. Energy efficiency is a key consideration, with AI chipmakers focusing on highbandwidth memory and system on chip designs. Cloud providers like Microsoft Azure, Amazon Web Services, and Google Cloud offer AI services, while edge computing enables real-time applications on Edge devices. Ethical concerns around AI use are rising, with specific integrated circuits and multichip modules being developed to address these issues. AI data centers and cognitive computing are powering AI applications in various sectors, including healthcare, retail, finance, automotive, and manufacturing. Patent filings for AI technologies continue, with potential applications in mobile health monitoring, elderly population care, and image recognition. The future of AI lies in the intersection of AI, robotics, and quantum computing, with potential use cases in autonomous vehicles, IoT devices, and Industry 4.0. The market for AI chips is expected to grow significantly, with investments in research and development and collaboration between tech giants and startups. However, system failure and malfunctioning remain challenges, with ongoing efforts to improve reliability.

The Internet of Things (IoT) market is experiencing significant growth due to the advantages it offers in various industries, including aerospace and defense, automotive, consumer electronics, healthcare, and more. IoT devices make decisions using data they receive, eliminating the need for human intervention. To enhance their capabilities, IoT device manufacturers integrate Human-Machine Interface (HMI) technologies into devices such as cameras, drones, smart speakers, smartphones, smart TVs, and others. This integration leads to the deployment of Artificial Intelligence (AI) chips in IoT devices, enabling power-efficient data processing and machine learning computation. The high demand for IoT devices and the integration of AI chips make the AI Chips Market a lucrative business opportunity.

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Market Challenges

    --  Artificial Intelligence (AI) is revolutionizing industries from
        healthcare to retail, finance, and automotive. However, the growing
        demand for advanced AI technologies, including deep learning and
        robotics, poses challenges for hardware components like AI chips.
        Traditional CPUs, GPUs, FPGAs, and ASICs struggle to meet the high
        computing requirements of AI algorithms and machine learning models.
        Leading tech companies like Advanced Micro Devices, Nvidia, and Huawei
        are investing in AI chip lines to address these challenges. For
        instance, Nvidia's A100 chip and Huawei's Ascend 910B chipset are
        designed for AI data centers, while the Trainium2 chip focuses on edge
        computing. Energy efficiency is another concern, as AI applications,
        such as generative AI and large language models, require massive data
        processing. Highbandwidth memory and quantum computing are potential
        solutions, but they present their own challenges. Moreover, ethical
        concerns surrounding AI technologies, such as system failure and
        malfunctioning, require careful consideration. Edge computing and
        centralized cloud servers offer alternatives for real-time applications
        and reducing latency. AI applications span various industries, including
        healthcare, retail, finance, and automotive. Ethical concerns and energy
        efficiency challenges must be addressed to ensure the widespread
        adoption of AI technologies. AI technologies like cognitive computing,
        machine intelligence, image recognition, and pose detection are
        transforming industries, from healthcare to retail, finance, automotive,
        and more. Patent filing and system failure are concerns, but the
        potential benefits far outweigh the challenges. AI technologies are also
        being integrated into everyday devices, such as mobile phones, personal
        computers, gaming consoles, and even wearable devices and smart homes.
        Theoretical and algorithmic basis, visual understanding, and automatic
        analysis are essential for these applications. In conclusion, the AI
        chip market is experiencing significant growth, driven by the increasing
        demand for AI technologies in various industries. However, challenges
        related to energy efficiency, ethical concerns, and system failure must
        be addressed to ensure the widespread adoption of AI technologies.
        Companies are investing in AI chip lines, such as Nvidia's A100 chip and
        Huawei's Ascend 910B chipset, to meet the demands of AI applications in
        industries like healthcare, retail, finance, and automotive. Edge
        computing and centralized cloud servers offer alternatives for real-time
        applications and reducing latency. The future of AI technologies is
        bright, with potential applications in manufacturing machines,
        processors, GPUs, FPGAs, CPUs, DSPs, microcontrollers, frame buffers,
        display devices, and programmable logic chips.
    --  The AI chips market is experiencing significant growth due to the
        potential revenue increases that companies can achieve through
        artificial intelligence implementation. However, the market's expansion
        is hindered by a shortage of skilled professionals with expertise in AI
        technology. The high research and development costs associated with AI
        integration and the lack of available talent pose challenges for
        enterprises. To address this issue, companies must carefully evaluate
        the benefits and requirements before implementing AI solutions. The
        scarcity of experienced AI professionals is currently the greatest
        barrier to the widespread adoption of AI within business operations.

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Segment Overview

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

    --  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
        --  Edge
        --  Cloud
    --  Application
        --  Nature Language Processing
        --  Robotics
        --  Computer Vision
        --  Network Security
        --  Others
    --  Technology
        --  System On Chip
        --  System In Package
        --  Multi Chip Module
        --  Others

1.1 ASICs- Artificial Intelligence (AI) chips are experiencing significant growth due to the increasing adoption of application-specific integrated circuits (ASICs) in data centers. ASICs are customized, non-configurable chips that offer faster performance than GPUs and FPGAs. Google's Tensor Processing Unit (TPU) is an example of an ASIC designed for deep neural networks. TPUs provide higher performance and speed compared to GPUs, FPGAs, and CPUs. The TPU is a network of software and hardware that learns specific tasks by analyzing large data sets. TensorFlow, an open-source machine learning library, is used with TPUs to develop new algorithms. ASIC-based AI chips are gaining market share due to their ability to offer superior performance and speed in data center applications. The use of ASICs in cloud-based data centers is driving the growth of the AI chips market.

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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. Deep learning and machine learning algorithms are driving the demand for AI chips, which are specialized hardware components designed to accelerate AI computations. AI chips include specific integrated circuits like CPUs, GPUs, FPGAs, and system on chips. Quantum computing is also expected to revolutionize AI technologies, leading to the development of advanced AI chips. The market is witnessing innovation with the introduction of new AI chips like Trainium2, designed for high-performance AI applications. Industries such as healthcare, retail, finance, automotive, and IoT devices are major consumers of AI chips. Ethical concerns surrounding AI are also pushing the need for more advanced AI chips to ensure transparency and accountability. The market is segmented into cloud and edge computing, with the edge computing segment expected to grow due to the increasing demand for real-time AI processing. Highbandwidth memory is another crucial component in the development of advanced AI chips. The market is expected to grow significantly in the coming years, with new applications and use cases emerging in robotics, autonomous vehicles, and generative AI.

Market Research Overview

Artificial Intelligence (AI) Chips Market: Overview The AI Chips Market is a rapidly growing sector driven by the increasing demand for advanced AI technologies, including deep learning and machine learning, in various industries. AI Chips are specialized hardware components designed to accelerate AI algorithms and technologies, such as neural networks, quantum computing, and cognitive computing. These chips are integral to powering AI applications in robotics, computer vision, natural language processing, and other fields. The market for AI Chips encompasses a range of hardware components, including CPUs, GPUs, FPGAs, ASICs, DSPs, and microcontrollers. Companies are investing heavily in research and development to create more energy-efficient and high-performance AI chips to meet the demands of real-time applications and big data processing. Key trends in the AI Chips Market include the development of AI chip lines, such as Nvidia's A100 chip and Ascend 910B chipset, and H200 chipset, as well as the integration of highbandwidth memory and other advanced technologies. The market is also seeing the emergence of edge computing and the use of AI in centralized cloud servers and edge devices, such as mobile phones and IoT devices. Applications of AI Chips span various industries, including healthcare, retail, finance, automotive, and manufacturing. Ethical concerns surrounding AI and the potential for system failure or malfunctioning are also driving the need for more advanced and reliable AI chips. The market is expected to continue growing as AI technologies become increasingly integrated into everyday life, from health monitoring and personalized health to smart homes, connected cars, and manufacturing machines. The theoretical and algorithmic basis of AI technologies, including deep learning and machine learning, continue to evolve, with advancements in image recognition, pose detection, behavioral patterns, and structured data analysis. Patent filing and innovation are key drivers in the AI Chips Market, with companies investing in research and development to stay ahead of the competition. The market for AI Chips is diverse and dynamic, with applications ranging from mobile phones and embedded systems to personal computers, gaming consoles, and data centers. The future of AI Chips lies in their ability to provide high computing power, parallel processing, and energy efficiency, making them essential for powering the next generation of AI technologies and applications.

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
        --  Edge
        --  Cloud
    --  Application
        --  Nature Language Processing
        --  Robotics
        --  Computer Vision
        --  Network Security
        --  Others
    --  Technology
        --  System On Chip
        --  System In Package
        --  Multi Chip Module
        --  Others

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

About Technavio

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