Edge AI Hardware Market Research Report 2025-2030 Opportunities Expand With Generative AI Optimization, On-Device Visual Processors, And 5G-Enabled Ultra-Low Latency Applications

(MENAFN- GlobeNewsWire - Nasdaq) The edge AI hardware market is expected to soar to USD 58.90 billion by 2030, from USD 26.14 billion in 2025, at a CAGR of 17.6%. The growth is fueled by the necessity for real-time data processing, improved latency, privacy, and bandwidth efficiency, alongside advancements in semiconductor technology, IoT, and smart devices. However, limitations include inadequate processing power and security concerns. Federated learning is driving a higher CAGR in training than inferred, while smartphones lead device use due to 5G. China dominates the Asia Pacific market, propelled by government support and tech innovation. The report includes insights from diverse industry experts and profiles key market players like Qualcomm, Huawei, and Samsung.

Dublin, Aug. 08, 2025 (GLOBE NEWSWIRE) -- The "Edge AI Hardware Market by Device, Processor (CPU, GPU, and ASIC), Function, Power Consumption (Less than 1 W, 1-3 W, >3-5 W, >5-10 W, and More than 10 W), Vertical and Region - Global Forecast to 2030" report has been added to ResearchAndMarkets.com's offering.
The edge AI hardware market is projected to reach USD 58.90 billion by 2030, up from USD 26.14 billion in 2025, at a CAGR of 17.6%

The report will help the market leaders/new entrants with information on the closest approximations of the revenue for the overall edge AI hardware market and the subsegments. The report will help stakeholders understand the competitive landscape and gain more insight to position their business better and plan suitable go-to-market strategies. The report also helps stakeholders understand the market's pulse and provides information on key drivers, restraints, opportunities, and challenges.

The edge AI hardware market is growing due to the demand for real-time data processing, reduced latency, enhanced privacy, and better bandwidth efficiency. Advancements in semiconductor technology, IoT, autonomous vehicles, and smart devices also drive this growth.

However, the adoption has limitations, including the lack of processing power, memory, and energy available on edge devices to run complex AI models. This requires intense optimization that may negatively impact accuracy. Other limitations to adopting edge AI hardware in the vicinity included security vulnerabilities, deployment costs, scaling, and maintenance in distributed edge systems.

The report provides an-depth assessment of market shares, growth strategies, and offerings of leading players in the edge AI hardware market, such as Qualcomm Technologies, Inc. (US), Huawei Technologies Co., Ltd. (China), SAMSUNG (South Korea), Apple Inc. (US), and MediaTek Inc. (Taiwan), among others.
Training function to record higher CAGR during forecast period
The training functionality in edge AI will register a higher CAGR than the inference function as federated learning continues to take hold, wherein AI models can be trained on distributed edge devices directly. At the same time, data privacy and regulations can be complied with.

With industries producing massive datasets of various types at the edge, there is a growing need for always-on, device-based model updates to accommodate real-time learning and adaptation to local conditions. Furthermore, the potential of computing advances makes deploying necessary, decentralized training strategies ever easier, with disaster response, healthcare, finance, and autonomous systems prime examples.
Smartphone devices to capture largest market share during forecast period
Smartphones dominate the market for edge AI hardware due to their vast global user base and the widespread availability of AI-enabled features. These devices have become handy and ubiquitous, offering capabilities such as real-time language translation, facial recognition, and advanced photography - all of which require on-device processing to minimize latency and enhance user privacy.

Mobile 5G technology has further accelerated smartphone adoption, enabling devices to run more sophisticated and powerful AI applications while providing a seamless user experience without relying on cloud connectivity. Consequently, device manufacturers prioritize the development of advanced processing units in smartphones, solidifying their status as the most popular edge AI devices in the world.
China to account for largest market share in Asia Pacific during forecast period
Asia Pacific is expected to account for the largest market share throughout the forecast period. The market's growth will be fueled by support from the Chinese government and various development plans, such as the New Generation Artificial Intelligence Development Plan and Made in China 2025. Credible companies such as Huawei and Baidu also invest in research and innovation. The vast user base in China, along with significant advancements in the consumption and innovation of consumer electronics, also contributes to this growth.

Moreover, the large volumes of data generated by the Chinese population create an excellent environment for training and deploying edge AI models. China's strategic approach to integrating AI into various industries - including smart manufacturing, smart cities, and autonomous vehicles - will further support and accelerate the expansion of the edge AI market in the region.
Key Attributes:

Report Attribute	Details
No. of Pages	304
Forecast Period	2025 - 2030
Estimated Market Value in 2025	26.14 Billion
Forecasted Market Value by 2030	58.9 Billion
Compound Annual Growth Rate	17.6%
Regions Covered	Global

Market Dynamics

Drivers

• Need for Real-Time Data Processing and Reduced Cloud Dependency
• Development of Dedicated Ai Processing Units for Edge Device Applications
• Necessity to Optimize Data Management and Reduce Cloud Infrastructure Load

Restraints

• Complexities Associated with Network Implementation

Opportunities

• Advancements in Edge Ai Hardware Through Generative Ai Workload Optimization
• Development of On-Device Visual Processors for Next-Generation Mobile Ai Applications
• Growing Integration of Edge Computing Across Robotics, Automotive, and Industrial Sectors
• Opportunities in Ultra-Low Latency Ai Applications with 5G-Powered Edge Infrastructure

Challenges

• Balancing Performance and Power Consumption in Edge Ai Systems
• Developing Cohesive Edge Ai Standards Across Diverse Industry Requirements
• Shortage of Skilled Workforce

Technology Analysis

Key Technologies

• IoT
• 5G
• Fog Computing

Complementary Technologies

• Generative Ai

Adjacent Technologies

• Blockchain

Company Profiles

• 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
• Google
• Microsoft
• Axelera Ai
• Imagination Technologies
• Cambricon
• Tenstorrent
• Blaize
• General Vision Inc.
• Mythic
• Zero Asic Corporation
• Applied Brain Research (Abr)
• Horizon Robotics
• Ceva, Inc.
• Graphcore
• Sambanova Systems, Inc.
• Hailo

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• Global Edge AI Hardware Market

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