Edge AI Hardware Market

Global Edge AI Hardware Market Size (2024 to 2029)

The Global Edge AI Hardware Market was worth US$ 1288.98 billion in 2023 and is anticipated to reach a valuation of US$ 4109.99 billion by 2029 from US$ 1563.79 billion in 2024, and it is predicted to register a CAGR of 21.32% during the forecast period 2024-2029.

MARKET SCENARIO

Edge AI Hardware is a collection of devices and equipment for processing and powering artificial intelligence-based robotics and gadgets. These gadgets and gear are utilized to incorporate and further develop man-made consciousness gadget handling by handling information in the equipment. This procedure does not need the use of cloud computing or cloud technologies. This feature allows the gadget to make decisions on its own. The act of adopting a neural network model, usually created with deep learning, and deploying it onto computer devices is known as inference. This gadget will then seek for and identify whatever it has been trained to detect in the incoming data. While deep learning inference can be done on the cloud, edge AI is becoming increasingly important due to bandwidth constraints, privacy issues, and the necessity for real-time processing.

Computing infrastructure is brought closer to the source of incoming data using edge intelligence solutions. It also brings users closer to the systems, allowing the user to make real-time data-driven decisions. Speed and performance, improved security standards, scalability, dependability, offline capabilities, better data management, and privacy are just a few benefits of AI hardware acceleration for edge devices. AI accelerators can significantly improve an AI model's on-device inference or execution speed, as well as be used to perform special AI-based tasks that cannot be performed on a CPU.

MARKET DRIVERS

The increasing need for faster and more efficient edge hardware devices that require less interval in AI applications, together with product innovations, is estimated to drive market growth during the forecast period. 

Growing expenditures in R&D efforts for creating gadgets, as well as increased concerns about privacy and security, are allowing the industry to expand. For example, a survey of 200 IT and IT security leaders by the Cloud Security Alliance (CSA) found that a large number of respondents cited data privacy and security as their top concern, which has boosted demand for Edge AI Hardware, which eliminates the need for companies to share their private data with public cloud service providers, particularly in the healthcare sector, which is presenting an excellent opportunity to the market.

Jumpy gadgets with minimal latency and real-time operation are becoming more popular. This reduces latency and enables real-time autonomous decision-making. Edge AI allows for real-time data creation, learning, and inference, which might help applications that require processing. Between detecting a potential collision and making steering and braking changes, autonomous vehicles (AVs) have a very limited time. A limitless amount of data gathered by an IoT device is sent to the cloud, where machine learning (ML) models are performed, and the processed data is returned to the device with no delay in response.

MARKET RESTRAINTS

A lack of on-device training restrains the global edge AI hardware market.

Machine learning models for edge AI are currently pre-trained and utilized for inference. Users are given pre-trained models, which fine-tune themselves based on the data provided by the users. Training a model takes a lot of computing resources, and because edge AI has limited access to training data, it's more prone to uncertainty and unpredictability.

REPORT COVERAGE

SEGMENTAL ANALYSIS

Global Edge AI Hardware Market Analysis By Device

• Cameras
• Robots
• Smart Phones

Camera’s segment is expected to have the dominant share in the global edge AI hardware market during the forecast period. Surveillance cameras are becoming more popular as a result of their safety and security characteristics, and some of the most common Edge AI Hardware devices utilized by the government for security purposes are surveillance cameras and drones.

The robot segment is expected to have a significant share and growth in the global edge AI hardware market during the forecast period. Inputs to robots are analog signals in the form of voice waveforms or pictures, and they require specialized hardware with sensors and effectors.

The smartphone segment is expected to have a significant share in the global edge AI hardware market during the forecast period. The hardware that makes this cutting-edge technology possible is a new kind of processor called neural processing units, or NPUs, which is essential for speeding up the performance of machine learning models. NPUs are AI-specific processors that rewrite the rules for what can be done with neural networks on mobile devices.

Global Edge AI Hardware Market Analysis By Processors

• CPU
• GPU
• ASIC
• FPGA

CPU segment is expected to have the Dominant share in the Global Edge AI Hardware Market during the forecast period. Due to the rising usage of AI-enabled devices, it is most typically employed in computers, smartphones, and other devices, and it is also utilized for edge AI smartphones, such as Qualcomm's snapdragon 845 and 855.

GPU segment is expected to have a significant share and growth in the Global Edge AI Hardware Market during the Forecast Period. GPUs, which were initially designed to speed up graphics processing, may now be used to substantially speed up deep learning computations. New GPUs have been designed and tuned expressly for deep learning, and they are a vital element of a modern artificial intelligence infrastructure.

The ASIC segment is expected to have rapid growth in the Global Edge AI Hardware Market during the Forecast Period. An ASIC chip is a computer chip that is intended to do certain tasks. As a result, ASIC processors are already being designed to test and train AI algorithms explicitly. ASICs can be utilized to carry out a specific AI algorithm function. The chips are capable of handling the job in parallel.

FGPA segment is expected to have a significant share in the Global Edge AI Hardware Market during the Forecast Period. FPGAs are frequently employed in situations where data must travel across many networks with little delay. They're particularly beneficial for removing memory buffering and overcoming I/O bottlenecks, which are two of the most common performance constraints in AI systems. FPGAs may speed up the whole AI workflow by speeding up data input.

Global Edge AI Hardware Market Analysis By Power Consumption

• Less Than 1 W
• 1 – 3 W
• 3 – 5 W
• 5 – 10 W
• 10 W

The 10W Power consumption component segment is expected to have the dominant share in the global edge AI hardware market during the forecast period because of the growing need for good recognition, as well as technical developments in hardware devices such as smartphones and product innovations

Global Edge AI Hardware Market Analysis By End User

• Consumer Electronics
• Automotive
• Government
• Aerospace & Defense
• Healthcare

Consumer Electronics segment is expected to have the dominant share in the global edge AI hardware market during the forecast period. This is because user's spending and demand for consumer gadgets are increasing. Smartphones, smart wearables, and other electronic gadgets are in high demand. Furthermore, the emergence of new edge AI use cases might lead to a significant increase in consumer electronics in the edge AI hardware industry.

The government is expected to have a significant share and growth in the global edge AI hardware market during the forecast period. Because of the growing demand for cameras and the government's use of surveillance cameras for law enforcement, AI-based surveillance cameras are being employed in important applications such as behavior analysis, face recognition, and people counting.

REGIONAL ANALYSIS

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East and Africa

North America is expected to have the dominant share in the global edge AI hardware market during the forecast period.

Because of the high rate of adoption of IoT devices and the growing demand for quicker processing, North America dominates the market. The market in this region is likewise growing due to a strong technological background.

Asia-Pacific is expected to have a significant share and growth in the global edge AI hardware market during the forecast period. The use of AI processor-enabled smartphones is predicted to rise as smartphone penetration rises in China, Japan, India, and South Korea. Furthermore, because governments in different nations have tightened control over the Internet and digital communication, the area is also the most important market for surveillance cameras. The presence of numerous major suppliers in the automotive, electronics, and semiconductor industries, all of which are heavily investing in AI technology, is propelling the edge AI hardware market in the area forward. Furthermore, the presence of a high number of manufacturing enterprises makes the region an appealing market for AI-enabled industrial robots.

KEY MARKET PLAYERS

Companies playing a prominent role in the global edge AI hardware market include Apple Inc., Google LLC (Alphabet Inc.), Huawei Technologies Co. Ltd., Intel Corporation, International Business Machines Corporation (IBM), MediaTek Inc., Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung Electronics Co. Ltd. (Samsung), and Others.

RECENT HAPPENINGS IN THE MARKET

• Open Five and Edge Cortix are cooperating on a custom AI gas pedal SoC. Working together to bring a revolutionary high-performance, low-power edge AI processor to market.
• Excelero, a high-performance software-defined storage firm located in Tel Aviv, has been bought by NVIDIA. The purchase is in line with the semiconductor giant's plans to develop its HPC and AI capabilities.