Generative AI Chipset Market Size, Share and Trends 2024 to 2034

Generative AI Chipset Market Size and Forecast 2024 to 2034

The global generative AI chipset market size accounted for USD 49.26 billion in 2024 and is anticipated to reach around USD 792.25 billion by 2034, expanding at a CAGR of 32.02% from 2024 to 2034. The increasing popularity of AI technology and its pervasion in every sector like healthcare, finance, consumer electronics, and automotive creates lucrative opportunities to expand; moreover, the rise of big data analytics and 5G technology needs robust hardware chips fuelling the growth of the generative AI chipset market globally.

Generative AI Chipset Market Key Takeaways

• North America dominated the global generative AI chipset market with the largest market share of 44% in 2023.
• Asia Pacific is expected to host the fastest-growing market in the forecasted years.
• By chipset type, the GPU segment accounted for the largest market share of 42% in 2023.
• By chipset type, the ASIC segment will grow rapidly in the market over the studied period.
• By application, the deep learning segment dominated the global market in 2023.
• By application, the generative adversarial networks (GANs) segment is projected to grow at a significant CAGR in the market over the forecast period.
• By end use, the consumer electronics segment contributed the biggest market share of 23% in 2023.
• By end use, the automotive segment will register the fastest growth in the market over the forecast period.

U.S. Generative AI Chipset Market Size and Growth 2024 to 2034

The U.S. generative AI chipset market size is exhibited at USD 16.26 billion in 2024 and is predicted to be worth around USD 266.18 billion by 2034, growing at a CAGR of 32.23% from 2024 to 2034.

North America held the dominant share of the global generative AI chipset market in 2023. The growth of this region is due to the presence of major tech companies like NVIDIA, intel etc. are well established in the North America along with significant investment in the research and development of AI and its application in various field.

• In June 2024, Advanced Micro Devices, Inc. (U.S.) unveiled the AMD Ryzen AI 300 Series processors, which feature powerful NPUs delivering 50 TOPS of AI-processing power for next-generation AI PCs. These processors are powered by the new Zen5 architecture, equipped with 12 high-performance CPU cores, and include advanced AI architecture for enhanced gaming and productivity.

Asia Pacific is expected to host the fastest-growing generative AI chipset market in the forecasted years. The growth of this region is due to the strong emergence of sectors like consumer electronics and automotive, where applications of AI are indispensable, along with rapid industrialization in economically evolving countries like India, Japan, and China. In particular, China is investing heavily in the research and development of AI and its integration with various technologies. Moreover, emerging startups focusing on innovative AI integrate ideas in various sectors.

Market Overview

The generative AI chipset market is proliferating due to various reasons, such as rising demand for AI-based solutions in every sector like healthcare, finance, consumer electronics, etc., along with rapid digital transformation among various countries like India and China, which further supports the market to grow exponentially on a large scale. In data centers and edge devices, the growth of cloud computing is fuelling the demand for AI-based solutions.

Artificial Intelligence (AI) algorithms are becoming very advanced since the datasets become complex, which need to be managed effectively to gain insights to make forward decisions. Autonomous vehicles and robotics need real-time processing solutions, which can be achieved by AI-powered features. Region-wise, North America dominates the global generative AI chipset market; on the contrary, the Asia Pacific region is considered to be the fastest-growing region in the foreseeable future.

AI Impact on the Generative AI Market

Artificial Intelligence (AI) can significantly improve the production of the generative AI chipset market with the help of tools to improve the design and functionality of the AI chipsets. Processes can also be faster and more efficient if AI is used in the manufacturing of chipsets by automatic features. It reduces time, which increases business efficiency and enhances chip performance. AI also plays an important role in interfacing optimization and model training for the chips, offering them the ability to handle more complicated tasks in a more efficient way, which further improves the performance of chips.

Generative AI Chipset Market Growth Factors

• Increasing adoption of AI powered solutions in the various sectors like healthcare, finance, automotive fuelling the generative AI chipset market further.
• Increased expansion of data centers, including edge computing and cloud computing.
• Increasingly, Edge AI devices like smart cameras and applications like Internet of Things (IoT) require highly configured chips, propelling the market's growth.
• Increasing use of AI-based solutions in consumer electronics such as smartphones and wearables.
• Growing adoption in customized application-specific integrated circuits, that is, ASIC.
• Chip manufacturers are collaborating with major tech giants in the market.
• Need for AI chips that are highly efficient and low maintenance.

Market Scope

Market Dynamics

Driver

Rise of generative AI

The major driving factor for the generative AI chipset market is the rise of generative AI, like the recent launch of ChatGPT, which has become immensely popular. With such a rising popularity, AI chipsets should also be available in proportion to that. Since AI chipsets are widely used in a range of products like smartphones, wearables, healthcare tools, etc, manufacturers acknowledged this trend, and the production of AI chipsets also witnessed a sudden surge in the past years, propelling the market globally. Another factor is the increasing prevalence of big data analytics, which is the major reason for the market's growth. The rising need to handle huge datasets using Natural Language Processing (NLP) and predictive maintenance requires robust and highly configured AI chips.

Restraint

Substantial investment

The major restraining factor for the generative AI chipset market is the substantial initial invested needed to integrate innovative and evolving AI technology into existing infrastructures. Also, skilled workforce requires to manage such complex tasks is limited. Development and implementation are crucial part of the AI technology, restraining the markets growth despite of having number of benefits.

Opportunity

Implementation of AI in smartphones

The significant opportunity that the generative AI chipset market holds is the implementation of AI in smartphones. Technical advancements in AI have resulted in the integration of AI chipsets into smartphones. Apple, Samsung, and other manufacturers are also adopting this trend, propelling the market due to the integration of AI chipsets, which provides better security and privacy for data transmission, and sensitive data cannot be easily decrypted by unauthorized accessor. AI chipset also reduces overall power consumption and increases the efficiency and performance of smartphones.

• In February 2024, Qualcomm announced the Fast Connect 7900 product range which is the first AI-optimized Wi-Fi 7 System. It redefines user-connected Experience and enhances it. It will set a new bar for high performance, low latency, and low-power connectivity. Fast Connect 7900 is the first to integrate Ultra-Wideband, Bluetooth, and Wi-Fi technologies on a single chip.

Chipset Type Insights

The GPU segment accounted for the largest share of the generative AI chipset market in 2023 and is expected to maintain its position throughout the forecast period. In industries like gaming, autonomous systems, and entertainment, GPUs are widely used due to their capacity to handle parallel tasks efficiently. Therefore, GPUs are the preferred choice in many industries for running a complex AI model. Their flexibility, along with high computational power, fuelled the demand further as they are used to deploy and train AI models.

• In February 2024, Intel announced that they would extend the benefits of the AI PC to commercial customers with the new Intel vPro platform. The new processor will deliver enhanced power efficiency, leadership performance, and available built-in Intel Arc GPUs.

The ASIC segment will grow rapidly in the generative AI chipset market over the studied period. The growth of this segment is attributed to various factors like the rising demand for customized AI solutions in various sectors like finance, healthcare, and edge computing, where efficient use of energy is a critical aspect that needs to be considered largely. Moreover, ASIC provides superior performance ability and energy efficiency as compared to the traditionally used processors.

Application Insights

The deep learning segment dominated the global generative AI chipset market in 2023. The growth of this segment is fuelled by the widespread adoption of deep learning modules by various sectors like finance and healthcare, where time-sensitive operations have taken place. Deep learning can be used to process complex tasks like image recognition, speech recognition, predictive analytics, and natural language processing. All this is possible due to the high-performance AI chipsets.

The generative adversarial networks (GANs) segment is projected to grow at a significant CAGR in the generative AI chipset market over the forecast period. The growth of this segment is attributed to its incredible applications in the creative industries and in cybersecurity. GAN has a significant ability to generate realistic data like images and videos, which is efficiently used in the creative areas.

End-use Insights

The consumer electronics segment led the global generative AI chipset market. The growth of this segment is due to the increasing dependency on AI for various features like voice assistance, customized recommendations, and speech and image recognition in smart devices like smartphones, smart homes, and wearables.

The automotive segment will register the fastest growth in the generative AI chipset market over the forecast period. The growth of this segment is due to the manufacturers investing heavily in the integration of AI into existing and rapidly evolving technologies. By doing this, vehicle makers want to enhance the efficiency of the vehicle at its highest level, fuelling the segment's growth further. Also, systems like ADAS are increasingly being used in the automobile industry, which requires high-performance AI chipsets.

Generative AI Chipset Market Companies

• Advanced Micro Devices, Inc.
• Apple Inc.
• Arm Holdings plc
• Broadcom Inc.
• Cerebras Systems
• Google Inc.
• Graphcore
• Intel Corporation
• Micron Technology, Inc.
• Mythic AI
• NVIDIA Corporation
• Qualcomm Technologies, Inc.
• Xilinx Inc.

Recent Developments

• In May 2024, Google (U.S.) announced Trillium, its sixth-generation TPU, designed to enhance training and serving times for AI workloads. The Trillium TPU boasts increased clock speed and larger matrix multiply units, powering the next wave of AI models.
• In March 2024, NVIDIA Corporation (U.S.) introduced the NVIDIA Blackwell platform, enabling organizations to build and operate real-time GenAI systems with six transformative technologies for accelerated computing. The platform supports AI training and real-time large language model (LLM) inference for models with up to 10 trillion parameters.
• In February 2024, Qualcomm revealed an advanced 5G Modem-RF System that harnesses integrated AI to enable the next generation of 5G. It is the most advanced modem-to-antenna platform, which has artificial intelligence and unparalleled power efficiency, spectrum flexibility, and performance. It enables readiness for 5G advancement across various product segments
• In November 2023, NVIDIA Corporation launched the upgraded HGX H200 platform, built on the Hopper architecture and featuring the H200 Tensor core GPU. This GPU, the first to incorporate HBM3e memory, offers an impressive 141 GB of memory with a blazing speed of 4.8 terabytes per second.

Segments Covered in the Report

By Chipset Type 

• CPU
• GPU
• FPGA
• ASIC
• Others

By Application

• Machine Learning
• Deep Learning
• Reinforcement Learning
• Generative Adversarial Networks (Gans)
• Natural Language Understanding (NLU)

By End-use

• Consumer Electronics
• Automotive
• Healthcare
• Retail
• Manufacturing
• Banking, Financial Services, And Insurance (BFSI)
• Telecommunication
• Others (Energy, Government, Etc.)

By Geography

• North America
• Asia Pacific
• Europe
• Latin America
• Middle East and Africa