“Global Edge Artificial Intelligence Chips Market to reach a market value of USD 148.96 Billion by 2031 growing at a CAGR of 33.2%”
The Global Edge Artificial Intelligence Chips Market size is expected to reach $148.96 billion by 2031, rising at a market growth of 33.2% CAGR during the forecast period.
The rapid digital transformation in countries like China, Japan, and South Korea, coupled with the increasing demand for AI-powered applications in sectors such as manufacturing, automotive, and consumer electronics, has led to significant growth in the market. Therefore, the Asia Pacific region generated 28% revenue share in the market in 2023. The region’s large population base, expanding middle class, and rising disposable incomes have also boosted demand for consumer devices equipped with edge AI chips. Moreover, the growing focus on smart cities and Industry 4.0 initiatives in Asia Pacific has supported the growth of edge AI chip applications, making it a key contributor to the market’s overall revenue share.
The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In October, 2024, Advanced Micro Devices Inc. unveiled the MI325x AI chip, competing with Nvidia's Blackwell series in the AI hardware market. It offers improved processing power, energy efficiency, and compatibility with open-source frameworks. Built on a 3nm process, the MI325x features RDNA4 architecture for enhanced deep learning performance. In October, 2024, Qualcomm Incorporated unveiled the Snapdragon 8 Elite Mobile Platform, the world’s fastest mobile system-on-a-chip, featuring the second-gen Qualcomm Oryon CPU, Adreno GPU, and Hexagon NPU. These innovations enable game-changing performance, multi-modal generative AI, and enhanced camera, gaming, and browsing experiences while prioritizing user privacy and power efficiency.
Based on the Analysis presented in the KBV Cardinal matrix; Apple, Inc. is the forerunners in the Edge Artificial Intelligence Chips Market. Companies such as Amazon Web Services, Inc., NVIDIA Corporation and IBM Corporation are some of the key innovators in Edge Artificial Intelligence Chips Market. In August, 2021, IBM Corporation unveiled its Telum Processor at Hot Chips, designed for real-time AI-driven fraud prevention in enterprise workloads. With on-chip AI acceleration, it enables faster, scalable fraud prevention across sectors like banking and insurance. Telum aims to move businesses from detecting fraud to preventing it, improving efficiency and reducing latency.
In industrial automation, edge AI chips are deployed to optimize manufacturing processes, enhance predictive maintenance, and improve operational efficiency. By processing data locally on the factory floor, these chips enable real-time decision-making and immediate response to anomalies, minimizing downtime and reducing production costs. Integrating AI at the edge also facilitates the development of smart robots and autonomous systems that can perform complex tasks with high precision and adaptability. Therefore, the expansion of artificial intelligence worldwide drives the market's growth.
The expansion of 5G networks supports the development and deployment of new IoT applications across various industries. For example, edge AI chips can leverage 5G connectivity in healthcare to enable remote monitoring and telemedicine services, providing real-time health data analysis and improving patient outcomes. In manufacturing, 5G-enabled edge AI chips can facilitate real-time monitoring and predictive maintenance of machinery, reducing downtime and operational costs. As 5G networks expand globally, they will drive the adoption of edge AI chips, unlocking new opportunities and applications across multiple sectors. Hence, the growth of 5G networks and connectivity globally propels the market's growth.
The limited storage capabilities of edge AI chips can pose challenges for applications that generate and process large datasets. Storing and managing substantial amounts of data locally can be impractical, necessitating frequent data transfer to centralized storage systems. This can impact the efficiency of edge computing and reduce its effectiveness in scenarios where continuous data availability and real-time processing are critical. Addressing these limitations requires ongoing advancements in edge AI chip design and the development of innovative solutions to enhance their processing power and storage capacities. In conclusion, limited processing power and storage capabilities impede the market's growth.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Product Launches and Product Expansions.
On the basis of function, the market is segmented into training and inference. The inference segment recorded 64% revenue share in the market in 2023. Inference refers to running pre-trained AI models on edge devices to make real-time decisions or predictions. The increasing demand for real-time, low-latency processing in applications such as autonomous vehicles, industrial automation, and smart cities has driven the dominance of the inference segment. Edge AI chips optimized for inference can process data locally, reducing the reliance on cloud computing and enabling faster, more efficient decision-making.
Based on chipset, the market is divided into CPU, GPU, ASIC, and others. The GPU segment held 12% revenue share in the market in 2023. GPUs are particularly well-suited for parallel processing tasks, essential for AI and machine learning applications. Their ability to perform numerous calculations simultaneously makes them highly effective for data-intensive edge AI applications, such as image and video processing, natural language processing, and real-time analytics. The rising demand for AI-powered applications, coupled with the increasing adoption of edge computing for real-time data processing, has contributed to the growing share of GPUs in the market.
By device, the market is divided into consumer devices and enterprise devices. In 2023, the consumer devices segment registered 79% revenue share in the market. This dominance is primarily driven by the growing integration of AI technologies into consumer electronics such as smartphones, wearables, smart speakers, and home automation systems. Consumer devices require AI chips for tasks like voice recognition, facial recognition, and real-time data processing, enhancing user experiences through smart capabilities. The increasing consumer demand for smarter, more personalized devices and the growing adoption of AI-powered applications have significantly fueled the demand for edge AI chips in this segment.
Free Valuable Insights: Global Edge Artificial Intelligence Chips Market size to reach USD 148.96 Billion by 2031
The Edge Artificial Intelligence (AI) Chips market is highly competitive, driven by the need for faster processing at the edge of networks. Companies are focused on developing chips that can support real-time AI data analysis with low latency and power consumption. The market is shaped by advancements in semiconductor technologies, with players competing to offer energy-efficient, high-performance solutions for applications like autonomous vehicles, IoT, and industrial automation. Strong competition is fueled by demand for innovation, scalability, and integration into edge devices.
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region witnessed 35% revenue share in the market in 2023. This can be attributed to the strong presence of major technology companies, research institutions, and high levels of investment in AI and edge computing within the region. The increasing adoption of edge AI chips in consumer electronics, automotive applications, and enterprise devices has driven significant market demand. Additionally, North America’s advanced infrastructure, skilled workforce, and innovation in AI technologies have further contributed to the region’s dominant position in the market.
| Report Attribute | Details |
|---|---|
| Market size value in 2023 | USD 15.51 Billion |
| Market size forecast in 2031 | USD 148.96 Billion |
| Base Year | 2023 |
| Historical Period | 2020 to 2022 |
| Forecast Period | 2024 to 2031 |
| Revenue Growth Rate | CAGR of 33.2% from 2024 to 2031 |
| Number of Pages | 243 |
| Number of Tables | 343 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Competitive Landscape, Market Share Analysis, Porter’s 5 Forces Analysis, Company Profiling, Companies Strategic Developments, SWOT Analysis, Winning Imperatives |
| Segments covered | Function, Chipset, Device, Region |
| Country scope |
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| Companies Included | Advanced Micro Devices Inc., Samsung Electronics Co., Ltd. (Samsung Group), NXP Semiconductors N.V., Qualcomm Incorporated (Qualcomm Technologies, Inc.), NVIDIA Corporation, Intel Corporation, Infineon Technologies AG, IBM Corporation, Amazon Web Services, Inc. (Amazon.com, Inc.), Apple, Inc. |
By Function
By Chipset
By Device
By Geography
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