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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 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 (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.

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

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

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.

The global AI chip market revenue is expected to reach USD 117.50 billion by 2029 from USD 23.19 billion in 2023, at a CAGR of 31.05% from 2023 to 2029.

AI Chip Market is projected to reach USD 501.97 billion by 2033, growing at a CAGR of 35.50% from 2025-2033.

Global artificial intelligence chip market to reach $164.07 billion by 2029 at 41.6% CAGR, driven by growing demand for smart homes, cities, and intelligent devices.

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

Explore global AI chip market trends, forecasts & growth drivers. Insightful analysis for investors, OEMs & tech leaders in AI semiconductors.

North America Artificial Intelligence Chip market size will be USD 8633.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 37.7% from 2024 to 2031. North America has emerged as a prominent participant, and its sales revenue is estimated to reach USD 85653.0 Million by 2031. This growth is mainly attributed to the region's growing government innitiativs.

AI Chip Market Outlook

According to the latest research, the global AI chip market size in 2024 stood at USD 20.7 billion, reflecting robust momentum across various industry verticals. The market is expected to register a remarkable CAGR of 35.2% from 2025 to 2033, reaching a projected value of USD 273.7 billion by 2033. This extraordinary growth is primarily driven by the surging adoption of artificial intelligence in consumer electronics, automotive, healthcare, and financial services, as well as the ongoing advancements in high-performance computing and edge AI applications.

One of the most significant growth factors for the AI chip market is the exponential increase in data generation and the corresponding need for accelerated processing power. As enterprises and consumers generate massive volumes of structured and unstructured data, AI-driven analytics and decision-making become indispensable. AI chips, particularly GPUs, ASICs, and FPGAs, are engineered to handle complex computations and parallel processing tasks that traditional CPUs cannot efficiently manage. The proliferation of AI-based applications, such as natural language processing, computer vision, and robotics, further intensifies the demand for specialized hardware capable of delivering low-latency, high-throughput performance. Additionally, the integration of AI chips in edge devices is enabling real-time analytics and inference at the source, reducing reliance on cloud infrastructure and enhancing data privacy and security.

Another pivotal driver is the rapid evolution of AI algorithms and machine learning models, which necessitate more sophisticated and energy-efficient hardware. The ongoing shift from general-purpose processors to application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs) is enabling organizations to optimize their AI workloads for both training and inference. Innovations in chip design, such as system-on-chip (SoC) and multi-chip module (MCM) architectures, are delivering improved computational density and power efficiency, making AI chips more accessible for a wider range of applications. This progress is also supported by substantial investments from both established semiconductor giants and emerging startups, fostering a highly competitive and innovative market landscape.

In addition, the adoption of AI chips is being accelerated by strategic collaborations and ecosystem partnerships between chip manufacturers, cloud service providers, and end-user industries. Major technology companies are investing heavily in AI research and development, leading to the introduction of next-generation chipsets optimized for deep learning and neural network acceleration. The increasing deployment of AI chips in autonomous vehicles, smart manufacturing, and healthcare diagnostics is creating new avenues for market expansion. Governments and regulatory bodies are also recognizing the transformative potential of AI, resulting in supportive policies and funding initiatives aimed at fostering AI innovation and infrastructure development.

From a regional perspective, Asia Pacific is emerging as the fastest-growing market, driven by the rapid digital transformation in countries such as China, Japan, and South Korea. North America remains the largest market, benefiting from strong investment in AI research, a robust technology ecosystem, and the presence of leading semiconductor companies. Europe is also witnessing significant growth, fueled by advancements in automotive AI and industrial automation. Meanwhile, Latin America and the Middle East & Africa are gradually adopting AI technologies, primarily in telecommunications and financial services, contributing to the overall global expansion of the AI chip market.

Chip Type Analysis

The chip type segment of the AI chip market encompasses GPUs, ASICs, FPGAs, CPUs, and a variety of other specialized processors, each playing a pivotal role in advancing artificial intelligence

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 (AI) chip market size reached approximately USD 19.60 Billion in 2024. The market is further projected to grow at a CAGR of 28.80% between 2025 and 2034, reaching a value of USD 246.27 Billion by 2034.

AI Inference Chip Market size was valued at USD 31,003.61 Million in 2024 and is projected to reach USD 167,357.01 Million by 2032, growing at a CAGR of 28.25% from 2026 to 2032.The rising demand for data centers is fueled by the need for greater computing power and data storage, combined with limited power availability and attractive investment returns. As AI adoption increases, data centers are playing a more critical role in processing inference tasks, which require chips capable of delivering real-time performance and energy efficiency. This shift is accelerating the need for advanced AI inference chips. The trend is further reinforced by the growing popularity of edge computing and system-on-chip (SoC) designs, where AI accelerators like NPUs and TPUs are embedded directly into consumer devices. This integration allows for on-device inference, reducing reliance on external chips and reshaping demand toward more compact and energy-efficient hardware solutions.

The AI chip market size was valued at USD 125.16 billion in 2024 and is set to exceed USD 1.28 trillion by 2037, expanding at over 19.6% CAGR during the forecast period i.e., between 2025-2037. Asia Pacific industry is estimated to dominate majority revenue share by 2037, on the back of intensifying adoption of AI based technologies and growing investments to establish AI startups, especially in countries such as China, Japan and India.