Dublin, August 8, 2025 (Globe Newswire) – “Device, Processor (CPU, GPU, and ASIC), Features, Features, Power Consumption (1 W, 1-3 W, > 3-5 W, > 3-5 W, > 3-5 W, > 3-5 W, > 3-5 W, > 3-5 W, > 3-5 W, > 3-5 W, > 3-5 W, > 10 W, and 10 W), Vertical and Regional Regions – 2030 “Report has been added. ResearchAndMarkets.com Provided.
The Edge AI hardware market is projected to reach US$589 billion by 2030.
This report will help market leaders/new entrants provide information on the closest approximation of the overall AI hardware market and sub-segment revenue. This report will help stakeholders understand the competitive environment, gain more insight into positioning their businesses better and planning strategies that are on the right market. The report also helps stakeholders understand the market pulse and provide information on key drivers, constraints, opportunities and challenges.
The Edge AI Hardware market is growing due to demand for real-time data processing, reduced latency, increased privacy and increased bandwidth efficiency. Advances in semiconductor technology, IoT, self-driving cars and smart devices will also drive this growth.
However, adoption has limitations such as the lack of processing power, memory and energy available to edge devices to run complex AI models. This requires intense optimizations that can negatively affect accuracy. Other limitations for adopting edge AI hardware nearby include security vulnerabilities, deployment costs, scaling, and maintenance of distributed edge systems.
This report is based on Qualcomm Technologies, Inc. (USA), Huawei Technologies Co., Ltd. We provide a detailed assessment of the market share, growth strategies and offerings of key players in the EDGE AI hardware market, including (China), Samsung (Korea), Samsung (Korea), Apple Inc. (US), Mediatek Inc. (TAIWAN).
Training function to record higher CAGRs during forecast periods
The training function of Edge AI registers a CAGR higher than the inference function as federated learning continues to be pending. This allows AI models to be trained directly on distributed edge devices. At the same time, you can comply with data privacy and regulations.
As the industry produces a wide range of types of large datasets, it requires constantly on device-based model updates to accommodate real-time learning and adaptation to local conditions. Furthermore, the potential for advancements in computing makes it easier to deploy the distributed training strategies needed with key examples of disaster response, healthcare, finance, and autonomous systems.
Smartphone devices that capture the largest market share during forecast periods
Smartphones dominate the Edge AI hardware market thanks to their vast global user base and wide availability of AI-enabled features. These devices are convenient and ubiquitous, offering features such as real-time language translation, facial recognition, and advanced photography. All of these require on-device processing to minimize latency and enhance user privacy.
Mobile 5G technology has accelerated the adoption of smartphones, allowing users to run more sophisticated and powerful AI applications while providing a seamless user experience without relying on cloud connectivity. As a result, device manufacturers will prioritize the development of advanced processing units on smartphones, cementing their status as the world's most popular edge AI device.
China accounts for the largest market share in the Asia-Pacific region during the forecast period
The Asia-Pacific region is expected to account for the largest market share throughout the forecast period. Market growth will be driven by support from the Chinese government and by new generation artificial intelligence development plans and various development plans manufactured in China. China's vast user base and significant advances in consumer electronics consumption and innovation are also contributing to this growth.
Furthermore, the large amount of data generated by the Chinese population creates an excellent environment for training and deployment of edge AI models. China's strategic approach to integrating AI into various industries (such as smart manufacturing, smart cities, autonomous vehicles) will further support and accelerate the expansion of the edge AI market in the region.
Important attributes:
| Report attributes | detail |
| Number of pages | 304 |
| Forecast period | 2025-2030 |
| Estimated market value for 2025 | 26.1 billion |
| Market value has been forecast by 2030 | 58.9 billion |
| Combined annual growth rate | 17.6% |
| Covered areas | global |
Market dynamics
driver
- Real-time data processing and reduced dependency on the cloud are required
- Development of dedicated AI processing units for edge device applications
- The need to optimize data management and reduce the burden on cloud infrastructure
Restraint
- Complexity associated with network implementation
opportunity
- Advances in Edge AI Hardware by Optimizing Generic AI Workloads
- Development of on-device visual processors for next-generation mobile AI applications
- Expanding edge computing integration across the robotics, automotive and industrial sectors
- Opportunities for ultra-low latency AI applications with 5G-powered edge infrastructure
assignment
- Balance between performance and power consumption of edge AI systems
- Develop cohesive edge AI standards across diverse industry requirements
- Lack of skilled labor
Technical analysis
Important Technology
Complementary technology
Adjacent Technology
Company Profile
- Qualcomm Technologies, Inc.
- Huawei Technologies Co. Ltd.
- Samsung
- Apple Inc.
- MediaTek Inc.
- Intel Corporation
- Nvidia Corporation
- IBM
- Micron Technology, Inc.
- Advanced Micro Devices, Inc.
- Meta
- Tesla
- Microsoft
- Axelera ai
- Imagination Technology
- Cambricon
- Tenstorrent
- Blaze
- General Vision Inc.
- mythology
- Zero ASIC Corporation
- Applied Brain Research (ABR)
- Horizon Robotics
- Ceva, Inc.
- GraphCore
- Sambanova Systems, Inc.
- Hilo
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Global Edge AI Hardware Market
