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Artificial Intelligence Chips Market Size 2025-2029

The artificial intelligence (AI) chips market size is forecast to increase by USD 902.65 billion, at a CAGR of 81.2% between 2024 and 2029. The market is experiencing significant growth, driven by the increasing demand for advanced AI capabilities in consumer electronics, particularly in smartphones.

Major Market Trends & Insights

North America dominated the market and accounted for a 42% share in 2023.
The market is expected to grow significantly in Europe region as well over the forecast period.
Based on the Product, the ASIC's segment led the market and was valued at USD 10.49 billion of the global revenue in 2023.
Based on the End-user, the media and advertising segment accounted for the largest market revenue share in 2023.

Market Size & Forecast

Market Opportunities: USD 48.69 Billion
Future Opportunities: USD 902.65 Billion
CAGR (2024-2029): 81.2%
North America: Largest market in 2023

This growth is fueled by the integration of AI in various sectors, including data center infrastructure, edge AI processing, and natural language processing. Moreover, the ongoing development of AI model optimization, hardware security modules, and real-time processing is leading to advancements in AI chip architecture. These innovations enable better clock speed performance, system-on-a-chip design, and power efficiency metrics, making AI chips increasingly attractive for low latency applications. Additionally, the silicon fabrication process is undergoing significant improvements, with a focus on cryptographic acceleration, thermal management design, and chip packaging technology. These advancements will lead to more secure and efficient AI chips, further boosting the market's growth potential.

What will be the Size of the Artificial Intelligence (AI) Chips Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by the insatiable demand for more powerful and energy-efficient solutions. Companies are investing heavily in research and development to create chips that can handle high-bandwidth memory, computer vision, and high-throughput computing. For instance, a leading semiconductor manufacturer recently announced a 50% increase in sales for its AI inference engine, which utilizes a tensor processing unit and an on-chip memory system for efficient data processing. The GPUs segment is the second largest segment of the product and was valued at USD 9.87 billion in 2023.

For example, a leading cloud computing platform has integrated a secure boot process and a neural network accelerator into its AI chip architecture, enabling faster and more secure AI inference. This innovation is expected to significantly reduce the latency associated with AI model deployment and improve overall system performance. In conclusion, the AI chips market is a dynamic and evolving landscape, with ongoing innovations in energy-efficient design, high-bandwidth memory, computer vision chip, high-throughput computing, and other areas driving growth and expansion. Companies that can successfully navigate this complex and rapidly changing market will be well-positioned to capitalize on the opportunities it presents.

The convergence of AI and Internet of Things (IoT) technologies is also fueling market expansion, as more devices require AI processing capabilities to analyze and respond to data in real-time. However, the market faces a notable challenge: the dearth of technically skilled workers specialized in AI chips development. This shortage may hinder market growth and necessitates strategic partnerships and collaborations between industry players to overcome this obstacle.

Companies seeking to capitalize on the opportunities presented by the AI Chips Market must focus on attracting and retaining top talent while collaborating to address the skills gap. By doing so, they can effectively navigate the competitive landscape and stay ahead of emerging trends.

How is this Artificial Intelligence (AI) Chips Industry segmented?

The artificial intelligence (AI) chips industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  ASICs
  GPUs
  CPUs
  FPGAs


End-user

  Media and advertising
  BFSI
  IT and telecommunication
  Others


Processing Type

  Edge
  Cloud


Application

  Nature language processing (NLP)
  Robotics
  Computer vision
  Network security
  Others


Technology

  System on chip (SoC)
  System in package (SiP)
  Multi chip module (MCM)
  Others


Function

  Training
  Inference


Geography

  North America

    US

The AI Chipsets Market is segmented by Component (Central Processing Unit (CPU), Graphics Processing Unit (GPU), and Neural Network Processor (NNP)), by Application (Consumer Electronics, Automotive, Healthcare, Automation & Robotics), and by Geography.

The AI chip market size is projected to grow from USD 31.6 billion in the current year to USD 846.85 billion by 2035, representing a CAGR of 34.84%, during the forecast period till 2035

The artificial intelligence (chipset) market is projected to be valued at US$ 27.6 billion in 2024. It is expected to rise to US$ 287.0 billion by 2034. The demand for artificial intelligence chipsets is expected to grow at a CAGR of 26.4% over the forecast period.

Category-wise Insights

Country-wise Insights

The artificial intelligence (AI) chip market is experiencing rapid growth, with projections indicating it will reach close to ** billion U.S. dollars by 2025. This surge reflects the increasing demand for AI technologies across various industries. The market's expansion is driven by advancements in machine learning, deep learning, and generative AI applications, which are reshaping how businesses operate and interact with customers. Nvidia leads the AI chip race Nvidia has emerged as a dominant player in the AI chip market, with its data center revenue skyrocketing in its 2025 fiscal year. The company's graphics processing units (GPUs) are crucial for training and running large language models, including OpenAI's ChatGPT. Nvidia's success helped propel it into the exclusive tech three trillion club, alongside industry giants like Apple and Microsoft. GPU market growth and AI applications The global GPU market, valued at **** billion U.S. dollars in 2024, has caught much of the world’s attention. This growth is largely fueled by the expanding AI market, particularly in machine learning and deep learning applications. The generative AI market is also contributing significantly, with projections suggesting it will reach surpass *** billion U.S. dollars by 2030. These trends underscore the increasing importance of AI chips in powering next-generation technologies and applications.

The Artificial Intelligence (AI) Chip Market was valued at USD 52.92 Bn in 2024, and it is projected to reach USD 295.56 Bn by 2030 with the CAGR of 33.2%.

Artificial Intelligence Chip Market size was valued at USD 30.96 Billion in 2023 and is projected to reach USD 504.01 Billion by 2031, growing at a CAGR of 46.03% during the forecast period 2024-2031.

Artificial Intelligence Chip Market: Definition/ Overview

An Artificial Intelligence (AI) chip is a specialized hardware component designed to efficiently perform tasks related to artificial intelligence, such as machine learning, natural language processing, and computer vision. These chips are engineered to handle complex computations, enabling faster execution of AI algorithms compared to traditional processors. They include various types, such as Graphics Processing Units (GPUs), Application-Specific Integrated Circuits (ASICs), and Field-Programmable Gate Arrays (FPGAs), each optimized for specific AI workloads. By utilizing parallel processing capabilities, AI chips significantly enhance the performance and efficiency of AI applications.

Global Artificial Intelligence Chipset Market has experienced tremendous growth in recent years and is poised to continue its strong expansion.

The entire market will rise very closely there It was predicted to USD 4.2 Billion by 2025 to USD 30.2 Billion by 2035, expanding at a CAGR of 21.6% during the forecast time. Electric vehicle (EV) manufacturers are now integrating AI chipsets into their vehicles to improve their autonomation abilities, committing themselves to utilize AI-based sensor fusion systems for improved navigation, and seeking out more AI-based Automotive Software solutions as they work to deploy AI more broadly. Also, new approaches like AI-on-chip, neuromorphic computing, and energy-efficient AI accelerators will lead to more innovations in automotive AI hardware.

Country-wise Insights

Competitive Outlook

Artificial Intelligence Chipsets Market size was valued at USD 27.36 Billion in 2024 and is projected to reach USD 152.63 Billion by 2031, growing at a CAGR of 26.44% from 2024 to 2031.

Global Artificial Intelligence Chipsets Market Drivers

Fast Growth in AI Applications: The need for AI chipsets is being driven by the widespread use of AI in a number of industries, including healthcare, automotive, finance, retail, and manufacturing. Artificial intelligence (AI) is finding widespread use in fields like robotics, autonomous driving, image identification, natural language processing, and predictive analytics. As a result, AI chip makers are facing enormous market opportunities.

Growing Need for Edge Computing: Real-time processing, lower latency, and bandwidth optimization are driving demand for edge computing, which processes data closer to the source or device than in centralized data centers. AI chipsets designed with edge computing in mind facilitate the effective integration of AI applications into gadgets like drones, IoT devices, autonomous cars, and smartphones.

Developments in AI Hardware Acceleration: The performance, energy efficiency, and scalability of AI are being enhanced by hardware acceleration technologies like neural processing units (NPUs), application-specific integrated circuits (ASICs), graphical processing units (GPUs), and field-programmable gate arrays (FPGAs). When it comes to performance, AI chipsets made especially for AI workloads are superior to standard CPU-based solutions.

Demand for AI in Data Centers and Cloud Computing: To increase the productivity of AI training and inference jobs and to speed up workloads, data centers and cloud computing providers are investing in AI chipsets. AI chipsets with high performance, scalability, and power efficiency that are tailored for data center and cloud environments make large-scale AI deployment possible.

AI Chipset Market size was USD 14.84 Billion in 2022 and is expected to reach a value of USD 306.61 Billion in 2032 and register a revenue CAGR of 40% during the forecast period.

Edge Artificial Intelligence Chips Market is Segmented by Chipset (CPU, GPU, ASIC, FPGA, and Neuromorphic), Device Category (Consumer Devices, and Enterprise/Industrial Devices), End-User Industry (Manufacturing and Industrial 4. 0, Automotive and Transportation, and More), Process Node (≥14 Nm, 7-10 Nm, and ≤5 Nm), and Geography (North America, South America, Europe, Asia-Pacific, and Middle East and Africa).

The global artificial intelligence chipset market will reach USD 297.50 Billion by 2031, growing at a CAGR of 26.7%. Growing adoption of AI in cloud computing and data centers is a major factor driving market growth.

The AI chipset market is experiencing explosive growth, driven by the increasing demand for artificial intelligence across various sectors. The market, estimated at $50 billion in 2025, is projected to expand significantly over the next decade, fueled by advancements in deep learning, natural language processing, and computer vision. Major players like Nvidia, Intel, and AMD are heavily invested in research and development, constantly pushing the boundaries of processing power and efficiency. The proliferation of edge computing applications and the rise of autonomous systems are key drivers, demanding higher performance and lower latency solutions. While the high cost of development and deployment remains a restraint, the overall market potential is vast, encompassing applications ranging from autonomous vehicles and robotics to healthcare and finance. The market is segmented by chipset type (GPU, CPU, ASIC, FPGA), application (data centers, edge devices, automotive), and geography. Competition is fierce, with established players facing challenges from emerging startups specializing in niche AI hardware. The market's growth trajectory is strongly correlated with the overall progress in AI technologies and their adoption across diverse industries. The forecast period (2025-2033) anticipates a continued upward trend, with a Compound Annual Growth Rate (CAGR) of approximately 25%. This growth is projected to be driven by increased investments in AI infrastructure, expanding data center deployments, and the continuous evolution of more energy-efficient and powerful AI chipsets. Specific regional growth will vary, with North America and Asia-Pacific expected to dominate the market due to significant investments in AI research and development, alongside the concentration of major technology companies. However, other regions like Europe are also witnessing a rapid increase in adoption, fueled by government initiatives and the growing digital transformation across various sectors. The competitive landscape will likely consolidate as larger players acquire smaller companies, while simultaneously innovating and developing next-generation solutions to maintain their market share.

Stay updated with Market Research Intellect's Artificial Intelligence (AI) Chipset Market Report, valued at USD 40 billion in 2024, projected to reach USD 110 billion by 2033 with a CAGR of 12.5% (2026-2033).

In 2023, the size of the AI chip market in China increased to over *** billion yuan. The largest share of the AI chip market were GPUs. They are designed to be able to handle parallel computations, which makes them the ideal platform for machine learning and other AI applications.

Artificial Intelligence (AI) Chipset Market Outlook

According to our latest research, the global Artificial Intelligence (AI) Chipset market size reached USD 29.8 billion in 2024, demonstrating robust expansion driven by the rapid proliferation of AI-powered applications across industries. The market is expected to maintain a strong growth trajectory, registering a CAGR of 32.1% from 2025 to 2033. By 2033, the AI Chipset market is forecasted to attain a value of USD 356.7 billion. This impressive growth is primarily fueled by the surging demand for high-performance computing, accelerated adoption of AI in edge devices, and ongoing advancements in deep learning and neural network architectures.

One of the primary growth factors propelling the AI Chipset market is the exponential increase in data generation and the corresponding need for advanced analytics. Enterprises across sectors such as healthcare, automotive, and finance are leveraging AI algorithms to extract actionable insights, automate processes, and enhance decision-making. This surge in AI adoption necessitates powerful and efficient chipsets capable of handling complex computations at scale. Furthermore, the proliferation of IoT devices and the emergence of edge computing have accelerated the demand for AI chipsets that can process data locally, reducing latency and improving real-time responsiveness. As a result, chipset manufacturers are investing heavily in R&D to develop innovative architectures tailored for AI workloads, further fueling market growth.

Another significant factor contributing to the expansion of the Artificial Intelligence Chipset market is the increasing integration of AI functionalities in consumer electronics and smart devices. Smartphones, smart speakers, home automation systems, and wearable devices are now equipped with AI-powered features such as voice recognition, image processing, and predictive analytics. This trend has created a massive demand for AI chipsets optimized for low power consumption and high computational efficiency. Moreover, the automotive industry is rapidly embracing AI for applications like autonomous driving, advanced driver assistance systems (ADAS), and in-vehicle infotainment, further amplifying the need for specialized AI hardware. The convergence of AI with 5G connectivity and cloud computing is expected to unlock new use cases, reinforcing the market's upward trajectory.

The evolving regulatory landscape and government initiatives aimed at promoting AI innovation are also playing a pivotal role in shaping the AI Chipset market. Countries across North America, Europe, and Asia Pacific are implementing policies and funding programs to foster AI research and development, enhance digital infrastructure, and ensure cybersecurity. These efforts are encouraging collaborations between academia, industry, and government agencies, resulting in the creation of cutting-edge AI chipsets that meet stringent performance and security standards. However, the market is not without challenges, as issues related to data privacy, ethical AI deployment, and the high cost of advanced chipsets may pose hurdles to widespread adoption. Nonetheless, the overall outlook remains positive, with significant opportunities for growth and innovation.

Regionally, North America continues to dominate the AI Chipset market, accounting for the largest revenue share in 2024, followed closely by Asia Pacific and Europe. The presence of leading technology companies, robust investment in AI research, and a mature digital ecosystem have positioned North America at the forefront of AI hardware innovation. Meanwhile, Asia Pacific is witnessing the fastest growth, driven by rapid industrialization, government support, and the proliferation of AI startups. Europe is also making significant strides, particularly in sectors such as automotive and healthcare. Latin America and the Middle East & Africa are emerging markets with untapped potential, expected to contribute to the global market's expansion in the coming years.

Artificial Intelligence (AI) Chipset Market Outlook

The AI chipset market size is projected to grow from USD 10.5 billion in 2023 to an impressive USD 102.3 billion by 2032, at a compound annual growth rate (CAGR) of 29.4%. This market growth can be attributed to the increasing integration of AI across various sectors including healthcare, automotive, and consumer electronics, driven by the rising demand for high-speed data processing and efficient computing capabilities.

The first major growth factor driving the AI chipset market is the rapid advancements in AI technologies such as machine learning, natural language processing, and computer vision. These advancements are facilitating more sophisticated and efficient AI applications, necessitating the development of highly specialized AI chipsets to handle the complex computations involved. For instance, the growing adoption of AI in healthcare for predictive diagnostics and personalized medicine is creating a significant demand for AI chipsets capable of processing large volumes of data at high speeds.

Another critical factor contributing to the expansion of the AI chipset market is the proliferation of smart devices and the Internet of Things (IoT). The integration of AI with IoT devices has led to the creation of smarter and more autonomous systems, requiring advanced chipsets to manage these functionalities. Smart home devices, wearable tech, and autonomous vehicles all rely on AI chipsets for efficient operation, driving the market forward. The increasing investment in AI and IoT by tech giants and startups alike further accelerates this trend, fostering innovation and expanding the market landscape.

Additionally, the rising demand for AI-driven customer experiences in various sectors such as retail and finance is significantly boosting the AI chipset market. Retailers are increasingly leveraging AI for personalized shopping experiences, demand forecasting, and inventory management, while financial institutions utilize AI for fraud detection, credit scoring, and customer service automation. This surge in AI applications requires robust and efficient AI chipsets, spurring market growth. Moreover, the continuous development and deployment of AI technologies by leading global corporations are setting new benchmarks for performance, driving further advancements in AI chipsets.

AI-enabled Cybersecurity Chipsets are becoming increasingly vital in securing digital infrastructures as the integration of AI technologies expands across various sectors. These chipsets are designed to enhance security measures by providing real-time threat detection and response capabilities. With the rise of sophisticated cyber threats, AI-enabled cybersecurity chipsets offer a robust solution by leveraging machine learning algorithms to identify and mitigate potential vulnerabilities. As organizations continue to adopt AI-driven systems, the demand for these specialized chipsets is expected to grow, ensuring the protection of sensitive data and maintaining the integrity of critical operations.

The AI chipset market also exhibits strong regional growth trends. North America, with its technological prowess, leads the market, followed by Asia Pacific, which is witnessing rapid adoption of AI technologies across various industries. Europe is also showing significant growth, driven by advancements in AI research and development. The Middle East and Africa, along with Latin America, are gradually catching up, leveraging AI to boost their respective economic sectors. This regional diversification not only expands the market reach but also enriches the global AI ecosystem, fostering innovation and competition.

Component Analysis

The AI chipset market is segmented by component into hardware, software, and services. The hardware segment, which includes processors, memory, and network devices, holds a significant market share. The growing demand for high-performance processors like GPUs, TPUs, and FPGAs is driving this segment. These processors are essential for handling the intensive computational tasks associated with AI applications. For instance, GPUs are widely used in training deep learning models, while TPUs are optimized for inference tasks in AI applications. The continuous advancements in semiconductor technologies further enhance the performance capabilities of these processors, contributing to the growth of the hardware segment.

The software segment encompa

Edge Artificial Intelligence (AI) Chip Market Outlook

The global market size for Edge Artificial Intelligence (AI) Chips was estimated at USD 3.8 billion in 2023 and is projected to reach USD 18.7 billion by 2032, reflecting a compound annual growth rate (CAGR) of 19.6% during the forecast period. This remarkable growth is driven by the increasing demand for real-time processing capabilities, the proliferation of IoT devices, and the need for efficient and low-latency data processing at the edge.

One of the primary growth factors in the edge AI chip market is the rising need for real-time data processing and analytics. Traditional cloud computing models, while powerful, often introduce latency that is unacceptable for applications requiring immediate decision-making. Edge AI chips bring computational power closer to the data source, enabling faster data processing and reduced latency. This is particularly crucial for applications in healthcare, autonomous driving, and industrial automation where split-second decisions are critical.

Another significant growth driver is the exponential increase in connected devices, commonly referred to as the Internet of Things (IoT). As IoT devices continue to proliferate globally, the volume of data generated at the edge of networks is skyrocketing. Edge AI chips are uniquely positioned to handle this influx by enabling localized data processing, reducing the need for bandwidth, and alleviating the load on centralized data centers. This capability not only enhances efficiency but also supports the scalability of IoT ecosystems.

The advancements in AI technologies and algorithms are further propelling the market. Today's edge AI chips are equipped with sophisticated machine learning and deep learning capabilities, enabling them to perform complex tasks such as image and speech recognition, anomaly detection, and predictive maintenance. These advancements are opening up new possibilities across various sectors, from healthcare diagnostics to smart retail solutions, thereby expanding the market's potential.

Regionally, North America is expected to dominate the edge AI chip market, owing to the presence of major technology companies, substantial R&D investments, and early adoption of advanced technologies. Europe and Asia Pacific are also significant markets, with Asia Pacific anticipated to witness the fastest growth. This is driven by rapid industrialization, the growing implementation of smart city projects, and increasing investments in AI and IoT technologies in countries like China, Japan, and South Korea.

Component Analysis

The edge AI chip market is segmented by component into hardware, software, and services. Hardware components, including processors, accelerators, and memory modules, constitute the backbone of edge AI solutions. These hardware components are essential for performing intensive computations directly at the source of data generation. The evolution of specialized AI processors, such as neural processing units (NPUs) and tensor processing units (TPUs), has significantly enhanced the performance and efficiency of edge AI systems.

Software plays a pivotal role in the functionality and versatility of edge AI chips. This segment encompasses AI frameworks, development kits, and runtime environments that enable developers to design, train, and deploy AI models on edge devices. The continual evolution of AI software, with improvements in algorithms and support for a wide range of hardware platforms, is critical for unlocking the full potential of edge AI technology. Additionally, software solutions often incorporate features for model optimization, energy efficiency, and security, which are paramount for edge deployments.

The services component includes consulting, integration, and maintenance services that facilitate the deployment and operation of edge AI solutions. As organizations adopt edge AI technologies, the need for expert guidance and support becomes essential. Service providers offer bespoke solutions tailored to the specific needs of different industries, ensuring seamless integration with existing systems and workflows. Moreover, ongoing maintenance services are vital for optimizing performance, ensuring reliability, and addressing any technical issues that may arise.

The synergy between hardware, software, and services is crucial for the successful deployment of edge AI solutions. Hardware advancements provide the necessary computational power, software optimizes performance and functionality, and services en

Artificial Intelligence Chip Market Report, size , Growth, Industry analysis by Technology, By Hardware, By Industry & Forecast, 2020-2027