Artificial Intelligence (AI) Chip Market by Chip Type (AI Accelerator Units and General-Purpose Chips), by Architecture (System on Chip (SOC), System in Package (SIP), Multi Chip Module, and Other Architecture), by Processing Type (Edge and Cloud), by Application (Natural Language Processing (NLP), Robotic Process Automation, Computer Vision, Network Security, and Others) and Others – Global Opportunity Analysis and Industry Forecast, 2025–2030
Industry: ICT & Media | Publish Date: 01-Feb-2025 | No of Pages: 547 | No. of Tables: 356 | No. of Figures: 301 | Format: PDF | Report Code : IC7
Artificial Intelligence (AI) Chip Market Overview
The global Artificial Intelligence (AI) Chip Market size was valued at USD 52.92 billion in 2024 and is predicted to reach USD 295.56 billion by 2030, registering a CAGR of 33.2% from 2025 to 2030.
The AI chip, also known as logic chips or AI accelerator refers to the market for specialized semiconductor chips designed to accelerate artificial intelligence (AI) and machine learning (ML) workloads. These chips find wide application with a large number of industries such as, automotive, industrial automation, healthcare, telecommunications, and retail and commerce markets. These AI accelerators or neural processing units (NPUs) are optimized for the performance-intensive tasks associated with AI algorithms, including image and speech recognition, natural language processing, predictive analytics, and many more.
It is an industry that has been rapidly developing in technology, being very competitive and focusing on developing energy-efficient and high-performance chips to cater to increasing demand regarding AI and ML applications in most industries.
Key players include tech giants such as NVIDIA, Intel, AMD, and Qualcomm, specialized AI chip start-ups and semiconductor companies. As per the Gartner, the revenues from semiconductors used in AI is projected to take a rapid upswing from about USD 44 billion in 2022 to USD 120 billion by 2027.
Rapid Adoption of Artificial Intelligence Boosts the Demand for AI Chips
The demand for AI chips is highly intensified by the rising adoption of artificial intelligence (AI) across industries as companies integrate AI into their operations to churn out high-performance output. For example, healthcare industry uses AI for diagnostics and personalized medicine, while on the automotive sector, AI helps to power autonomous driving and advanced driver-assistance systems (ADAS). In the finance industry, AI detects fraud and algorithmic trading, while the retail sector depends on it to analyze customer behavior and manage inventory.
The hardware also heavily relies on real-time data processing as an IoT device, further increasing the need for efficient AI chips. But demand for AI chips also comes from consumer electronics such as smartphones and smart home devices, wherein many AI workloads run for intelligent interaction.
As per the PwC AI Impact Index, the adoption maturity rate for the near term (3+ years) in retail is at 54%; followed by technology, communications, and entertainment at 47%; financial services at 41%; healthcare at 37%; and automotive at 35%.
Increasing Investment in Semiconductor Stimulates the Demand for AI Chips
The increasing investment by government bodies and leading companies' focus on helping the adoption of AI accelerators through policies, funding, and initiatives thus boosting the demand for AI chips.
According to Deloitte Insights, key semiconductor companies spent about USD 300 million to invest in AI tools while designing the chips in 2023. The number is projected to increase to USD 500 million by 2026. The government is also helping through grants, tax incentives, and funding for AI projects, among many others; it is also cutting barriers to entry and spurring innovation in this area. These effects are further amplified when combined with national AI strategies and public-private partnerships, encouraging the developmental imperatives in deploying advanced AI hardware required to support continued technological progress and development in AI applications worldwide.
As an example, the U.S. government is significantly investing in making computer chips with the introduction of new law “the Chips and Science Act”, which offers chipmakers USD 39 billion in grants, plus loans, guarantees, and tax breaks. This is a big gamble on chip production coming back to the U.S. Meanwhile, in Germany, Europe's largest chip factories with Intel and TSMC - each at around USD 11 billion - half of which investment is coming from the government itself - are being built.
The Integration of AI Processors into IoT Fuels the Artificial Intelligence (AI) Chip Market Trends
The proliferation of IoT devices generates massive data, increasing the need for AI chips to enable intelligent processing and analytics at the device level. These devices constantly gather data from industrial sensors, smart home gadgets, and wearable technologies that need immediate analysis to give actionable insights.
On-device AI chips for IoT-level implementation empower real-time analytics, predictive maintenance, and anomaly detection without reliance on centralized data processing. This capability enhances efficiency in operations for sectors such as manufacturing, healthcare, and transportation by reducing latency and optimizing resource utilization.
The spending in the IoT ecosystem is projected to expand from USD 726.6 billion in 2023 to over USD 1 trillion in 2026 at a compound annual growth rate (CAGR) of 10.4%, registering USD 805.7 billion, up by 10.6% from 2022.
Therefore, AI chips for IoT can scale energy-efficient performance levels and flexibility for deployment to intelligent cities or remote industrial sites. This is increasing with an increase in the cross-industry deployment of IoT, which raises the demand for specialized AI chips and further drives innovation and market opportunities for AI chip makers.
The Shortage of Semiconductor Hinders the AI Chip Market Expansion
The global chip deficit impacts the demand for AI chips, although the chips have become a necessity in different industries. Due to the low production rate, there are long waiting lists and difficulties in the supply chain – foundries are unable to meet the demand and those that do prioritize older nodes for other industries, thus reducing AI chip output.
Existing competition with countries in Asia through political tensions within the area worsens the problem. For example, own chip-making industry for a specification of an industry owned and developed independently. Europe, Japan, and India are also gradually raising their capacity for chip production at home. This is humiliating the geopolitical structures worldwide, and gearing up the tensions between countries, especially the U.S., and China. As per the Semiconductor Industry Association (SIA), the global semiconductor industry sales stood at USD 526, a decrease of 8.2% compared to the record-high USD 574.1 billion in 2022.
The Introduction of 2-nanometer (nm) Chipsets Creates Opportunity for The Market
The introduction of 2 nm chipset is a major opportunity for the growth of the AI chip sector by adding the limits to the semiconductor technologies. These ultra-miniature chips give high performance, low power consumption and increased packing density as compared to others and therefore suitable for the modern-day complex artificial intelligence processing.
This results in more detailed calculations performed abet and more complex tasks solved by a single AI chip as the 2nm chipsets are relatively smaller and more efficient. In 2023, Taiwan Semiconductor Manufacturing Company (TSMC) announced that its cutting-edge 2-nanometer (N2) chip manufacturing process will utilize advanced nanosheet transistor structures. This next-generation process is expected to begin mass production in 2025, positioning TSMC as the industry leader in terms of transistor density and energy efficiency.
This advancement gives the opportunity of inventing the new AI hardware for the new requirements of sectors including self-driving cars, Industry 4.0 and smart gadgets. The better features of 2nm AI chips will help spread more technologies with advanced AI chip which will help the chip industry to unlock more sophisticated and adaptive AI chip solutions in various fields.
Asia-Pacific Dominates the Global AI Chip Market Share
The Asia-Pacific continues to dominate a large percentage of the market, this is due to the highly developed semiconductor industry as well ongoing advancements by key players, such as TSMC, Samsung electronics, SMIC, and SK hynix among others.
Last June, Samsung Electronics Co., Ltd. completed an AI chip technology map to attract AI chip makers to its foundry business, which aims to continuously improve the production technology with a new 2-nanometer process next year.
Samsung’s strategy is to neutralize TSMC by improving its logic, memory and advance packaging solutions with the forecast of five times AI-related customers and nine times of the total revenue by 2028.
Furthermore, international investors’ shows interest in the Asia-Pacific AI chip sector, especially in the countries such as China, South Korea, Taiwan, Japan, and India, which is getting huge investments in the sector and enhancing the production capacities to meet high-growing global demands.
According to the Economist Intelligence Unit (EIU), Malaysia announced to increase its part in chip production more due to capital from global chip producing companies. Infineon Technologies AG, a German-based auto-mobile semiconductors producer, has two production locations in Malaysia and planned to invest USD 5. 8 billion investments to build a third chip testing facility in the nearby year 2023.
Moreover, the growth of giant enterprises, including Intel, Nvidia, and Intel in the Asia-Pacific district to design the newest chips for AI to increase rivalry boosts the market. For instance, Nvidia, AMD and Intel have introduced their next-generation artificial intelligence chip platforms in Taiwan which fuelled the competition in the at semiconductor market. Nvidia unveiled Rubin for 2026, meanwhile AMD and Intel demonstrated new accelerators and chips stressed on cost-efficiency and advanced techniques in the constantly transforming AI market.
North America Region Witnesses Fastest Growth in the AI Chip Market Demand
The North American region is a relatively fastest growing market for AI chips owing to the adoption of AI chips in the automotive sector to improve vehicle safety, work on autopilot, enhance navigation, and increase the efficiency of the engines.
In January 2024, Intel set it new model automotive parts to enter the market of semiconductors that power the brains of future cars through the latest AI-enabled chips. This considerably places Intel right into the middle of the automotive AI chip battlefield against market goliaths Qualcomm and Nvidia.
Further, the increasing attempts by the government to dedicate considerable capital into the sphere of AI is one of the principal drivers that is driving the artificial intelligence (AI) chip market growth. It assists in the application of grants to scientific and research activities and the support of co-operation between the government and private sectors, as well as improving legislation.
In June 2024 the Canadian government started a public debate on the distribution of a billion dollars. The government announced USD 1.46 billion to announced to be invested in artificial intelligence (AI) in its recent budget. The vision is to expand the Canadian owned data center for AI scientists and developers because currently Canada does not have enough data center locally to cater the growing need.
Competitive Landscape
The promising players operating in the global AI chip industry includes NVIDIA Corporation, Advanced Micro Devices, Inc. (AMD), Intel Corporation, Alphabet Inc., Amazon Web Services, Inc. (AWS), International Business Machines (IBM) Corporation, Alibaba Group Holding Limited, Apple Inc., Meta Platforms, Inc., Microsoft Corporation, Huawei Technologies Co., Ltd., MediaTek Inc., Qualcomm Incorporated, Samsung Electronics, and Cerebras Systems Inc., among others. These companies are engaged in various business strategies such as product launch and partnership across various regions to maintain their dominance in the global market.
|
Date |
COMPANY |
RECENT DEVELOPMENTS |
|
Jun-24 |
NVIDIA |
NVIDIA launched its latest AI chip Rubin soon after its predecessor, "Blackwell," at COMPUTEX in Taipei. With this launch NVIDIA aims to stay way ahead of its competitors such as AMD and Intel in the rapidly growing market for AI chips. |
|
Jun-24 |
AMD |
AMD launched its latest AI accelerator chips, the AMD Instinct MI300X series, featuring CDNA 3 architecture and up to 4TB/s memory bandwidth through HBM stacking. This is aimed at challenging NVIDIA’s Rubin, as these chips promise up to 8x better AI training performance and pave the way for CDNA 4 in 2025 with projected 35x better AI inference performance. |
|
May-24 |
Alphabet |
Google launched its Trillium chip, an AI accelerator aimed at boosting data center performance by 5x, emphasizing its commitment to innovating in the market for efficient cloud and data center operations. |
|
May-24 |
AWS |
AWS with NinjaTech AI AWS to launch advanced AI agents named "Ninja," powered by Amazon's Trainium and Inferentia2 chips. These agents excel in tasks such as research, meeting scheduling, and coding assistance, leveraging AWS's SageMaker for scalability and efficiency in training large language models. |
|
Apr-24 |
Intel |
Intel launched new Gaudi 3 AI chip aims to rival Nvidia's dominant H100 GPU in the AI sector, boasting superior power efficiency and scalability up to eight chips per motherboard. Amidst heightened competition and supply chain concerns post-Taiwan earthquake, Intel's stock rose while Nvidia's fell. |
Artificial Intelligence (AI) Chip Market Key Segments
By Chip Type
-
AI Accelerator Units
-
GPU
-
ASIC
-
FPGA
-
TPU
-
NPU
-
Other Accelerator Units
-
-
General-Purpose Chips
By Architecture
-
System on Chip (SOC)
-
System in Package (SIP)
-
Multi Chip Module
-
Other Architecture
By Processing Type
-
Edge
-
Cloud
By Application
-
Natural Language Processing (NLP)
-
Robotic Process Automation
-
Computer Vision
-
Network Security
-
Other Applications
By End User
-
Media and Advertising
-
BFSI
-
IT and Telecommunication
-
Retail
-
Healthcare
-
Automotive
-
Other End Users
By Region
-
North America
-
The U.S.
-
Canada
-
Mexico
-
-
Europe
-
The UK
-
Germany
-
France
-
Italy
-
Spain
-
Denmark
-
Finland
-
Netherlands
-
Norway
-
Russia
-
Sweden
-
Rest of Europe
-
-
Asia-Pacific
-
China
-
Japan
-
India
-
South Korea
-
Australia
-
Indonesia
-
Singapore
-
Taiwan
-
Thailand
-
Rest of Asia-Pacific
-
-
Rest of World
-
Latin America
-
Middle East
-
Africa
-
Key Players
-
NVIDIA Corporation
-
Advanced Micro Devices, Inc. (AMD)
-
Intel Corporation
-
Alphabet Inc.
-
Amazon Web Services, (AWS) Inc.
-
International Business Machines (IBM) Corporation
-
Alibaba Group Holding Limited
-
Apple Inc.
-
Meta Platforms, Inc.
-
Microsoft Corporation
-
Huawei Technologies Co., Ltd.
-
MediaTek Inc.
-
Qualcomm Incorporated
-
Samsung Electronics
-
Cerebras Systems Inc.
REPORT SCOPE AND SEGMENTATION:
|
Parameters |
Details |
|
Market Size Value in 2024 |
USD 52.92 Billion |
|
Revenue Forecast in 2030 |
USD 295.56 Billion |
|
Value Growth Rate |
CAGR of 33.2% from 2025 to 2030 |
|
Analysis Period |
2024–2030 |
|
Base Year Considered |
2024 |
|
Forecast Period |
2025–2030 |
|
Market Size Estimation |
Billion (USD) |
|
Growth Factors |
|
|
Companies Profiled |
15 |
|
Market Share |
Available for 10 companies |
|
Customization Scope |
Free customization (equivalent up to 80 working hours of analysts) after purchase. Addition or alteration to country, regional, and segment scope. |
|
Pricing and Purchase Options |
Avail customized purchase options to meet your exact research needs. |
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