Global Edge Artificial Intelligence Chips Market Size, Share & Trends Analysis Report By Function, By Chipset (CPU, ASIC, GPU, and Other Chipset), By Device (Consumer Devices and Enterprise Devices), By Regional Outlook and Forecast, 2024 - 2031

Global Edge Artificial Intelligence Chips Market Size, Share & Trends Analysis Report By Function, By Chipset (CPU, ASIC, GPU, and Other Chipset), By Device (Consumer Devices and Enterprise Devices), By Regional Outlook and Forecast, 2024 - 2031

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.

Market Growth Factors

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.

Market Restraining Factors

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.

Function Outlook

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.

Chipset Outlook

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.

Device Outlook

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.

Regional Outlook

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.

Recent Strategies Deployed in the Market

• Dec-2024: Apple, Inc. teamed up with Broadcom to develop its first AI-focused server chip, code-named Baltra, using TSMC’s advanced N3P process. This move reduces reliance on Nvidia and aligns Apple with other tech giants creating custom AI hardware.
• Oct-2024: Infineon Technologies is enhancing its AI software portfolio with the launch of DEEPCRAFT, a brand for Edge AI and Machine Learning solutions. DEEPCRAFT includes existing products like DEEPCRAFT Studio and Ready Models and will expand to offer a broader range of Edge AI software, models, and solutions for diverse applications.
• Sep-2024: Qualcomm Incorporated unveiled the Snapdragon X Plus 8-core chip, expanding its AI PC processor range. Featuring eight CPU cores, it offers 61% faster performance with lower power consumption. The chip includes an Adreno GPU and NPU for AI tasks, promising enhanced performance, AI experiences, and improved battery life for affordable Copilot+ PCs.
• Aug-2024: Samsung Electronics Co., Ltd. unveiled new LPDDR5X DRAM chips that are 9% thinner than previous models and offer 21% better heat resistance. These chips enhance performance, particularly for AI tasks, and improve airflow in mobile devices. They support Galaxy AI applications and are also suitable for smartwatches and IoT devices, with future 6-layer and 8-layer modules planned.
• Jun-2024: Intel Corporation revealed innovative technologies and structures expected to greatly speed up the AI environment in various areas such as the data center, cloud, network, edge, and PC. With increased processing capabilities, cutting-edge energy efficiency, and a reduced total cost of ownership (TCO), customers can now take full advantage of the AI system opportunity.

List of Key Companies Profiled

• 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.

Global Edge Artificial Intelligence Chips Market Report Segmentation

By Function

• Inference
• Training

By Chipset

• CPU
• ASIC
• GPU
• Other Chipset

By Device

• Consumer Devices
• Enterprise Devices

By Geography

• North America
• US
• Canada
• Mexico
• Rest of North America
• Europe
• Germany
• UK
• France
• Russia
• Spain
• Italy
• Rest of Europe
• Asia Pacific
• China
• Japan
• India
• South Korea
• Singapore
• Malaysia
• Rest of Asia Pacific
• LAMEA
• Brazil
• Argentina
• UAE
• Saudi Arabia
• South Africa
• Nigeria
• Rest of LAMEA