Edge AI Processor Market Share, Analysis, Opportunities 2032

Report Description

Edge AI Processor Market

The global edge AI processor market size was USD 2.6 Billion in 2023 and is projected to reach USD 9.5 Billion by 2032, expanding at a CAGR of 15.7% during 2024–2032. The market growth is attributed to the rising integration of AI algorithms in consumer electronics and industrial automation.

The rapid adoption of 5G technology, which enhances edge AI applications with high-speed connectivity and low latency, is a major factor fueling the market. Edge AI presents numerous advantages. Apart from its operational speed, edge technology boasts several other merits, including enhanced energy efficiency. Less data is transmitted to and from the cloud by processing data locally through the edge, thereby reducing data latency and energy consumption.

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Regulations impacting the edge AI processor market encompass a variety of considerations related to data privacy, security, safety, and industry-specific standards. The European Union’s Cybersecurity Act establishes a framework for cybersecurity certification of ICT products, services, and processes, including those involving edge AI processors. In the US, the National Institute of Standards and Technology (NIST) provides a framework for improving critical infrastructure cybersecurity, which is relevant for manufacturers of edge AI processors to ensure robust security measures.

• In June 2022, Advanced Micro Devices (AMD) partnered with NIO, a China-based electric vehicle manufacturer. As part of this collaboration, NIO planned to utilize AMD's EPYC processor series to expedite AI deep learning training and shorten product development cycles.

Impact of AI on the Edge AI Processor Market

Edge AI represents a fusion of artificial intelligence and edge computing. AI algorithms are processed locally, either directly on the device or on a nearby server. AI processors, specialized chips that integrate artificial intelligence and machine learning capabilities, empower mobile devices to replicate human-like intelligence. These chips optimize deep learning AI tasks. The increasing adoption of AI-based products and services is expected to boost the edge AI processor market in the coming years.

Major Drivers

Increasing demand for edge AI processors in the electronics industry and the widespread adoption of AI technologies across various sectors drive the market. AI has emerged as a pivotal force behind recent breakthroughs in education, healthcare, sales, telecommunications, infrastructure, electronic devices, and numerous other fields. Additionally, the integration of voice assistants, such as Google Home, Siri, and Alexa, has revolutionized how users interact with their home appliances, enabling seamless control through voice commands. This trend is anticipated to expand into consumer goods, such as speakers and headphones, reshaping the market dynamics. Furthermore, the rising adoption of IoT solutions boosts the market, as these solutions rely on AI processors for data processing in real-time.

Existing Restraints

Security concerns remain a significant barrier to the adoption of edge AI processors, particularly in sectors such as healthcare and finance. Ensuring robust security measures to protect data privacy and integrity is crucial. Various issues in cloud computing, such as latency issues, privacy concerns, and bandwidth limitations, hamper the market. However, advancements in chip technology have made it possible to perform sophisticated computing tasks directly on edge-enabled devices due to their compact size. This makes edge computing indispensable in scenarios where low latency and data privacy are paramount. When centralized systems, such as the cloud, become inundated with vast data volumes, latency problems emerge, which potentially impede the fulfillment of real-time business needs.

Emerging Opportunities

Growing emphasis on energy efficiency and sustainability drives the demand for energy-efficient AI edge processors capable of delivering high performance while minimizing power consumption, particularly in battery-powered edge devices. Energy-efficient AI edge processors are designed to minimize power consumption during both idle and active states. These processors achieve high performance per watt by optimizing the hardware architecture, circuit design, and power management algorithms, leading to reduced energy consumption and operating costs for edge computing applications.

Scope of the Edge AI Processor Market Report

The market report includes an assessment of the market trends, segments, and regional markets. Overview and dynamics are included in the report. 

Regional Outlook

In terms of region, the edge AI processor market is classified as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa.

North America held a major share of the global market in 2023, owing to the rapid expansion of industries such as healthcare, automotive, manufacturing, retail, and telecommunications. These industries heavily deploy edge AI solutions to enable real-time data processing, enhance operational efficiency, and support innovative applications, such as autonomous vehicles, predictive maintenance, and personalized customer experiences. Concerns about data privacy and security are prompting organizations in North America to deploy edge computing solutions to process sensitive data locally, reducing the risk of data breaches and ensuring compliance with regulations.

The market in Europe is expected to expand at a significant pace during the forecast period. Europe is home to major semiconductor companies, research institutions, and technology startups that are driving innovation in edge computing and artificial intelligence. These advancements are spurring the development of specialized AI processors tailored for edge computing deployments. The increasing demand for autonomous systems, such as autonomous vehicles, small drones, and industrial robots, propels the need for high-performance edge AI processors capable of real-time sensor fusion, perception, and decision-making. Companies in Europe are investing in developing advanced-edge AI solutions to address these evolving demands, thereby boosting the market in the region.

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Edge AI Processor Market Segment Analysis

Type Analysis

On the basis of type, the edge AI processor market is categorized into central processing unit (CPU), graphic processing unit (GPU), and application specific integrated circuit (ASIC)).

The central processing unit (CPU) segment is projected to hold a large market share during the projected period. CPUs are designed to handle a wide range of tasks across various applications. They are capable of executing instructions for arithmetic, logic, control, and input/output operations. One of the key advantages of CPUs is their versatility and flexibility. They efficiently execute diverse tasks, making them suitable for a wide range of applications beyond AI processing, such as operating systems, software applications, and system management. CPUs excel in handling tasks that require sequential processing, where each instruction is executed one after another. This makes them suitable for control flow or decision-making algorithms commonly found in traditional computing tasks.

The application specific integrated circuit (ASIC) segment is expected to register a considerable CAGR in the coming years. ASICs are designed and fabricated to perform a particular function or set of tasks with high efficiency and performance. ASICs offer better performance and energy efficiency for the targeted application as compared to general-purpose processors. ASICs achieve optimized performance metrics, such as throughput, latency, and power consumption, by eliminating unnecessary features and focusing solely on the required functionality.

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Device Type Analysis

Based on device type, the global market is fragmented into consumer devices, enterprise devices, and others.

The consumer devices segment held a large share of the market in 2023. Consumer devices refer to products designed for personal or household use by individuals. These devices include smartphones, tablets, smart speakers, wearable devices, smart appliances, and gaming consoles.

Edge AI processors in consumer devices enable various AI-driven features and functionalities, such as voice assistants, facial recognition, gesture control, augmented reality (AR), and virtual reality (VR). The demand for edge AI processors in consumer devices is driven by the growing adoption of AI-powered applications and services that enhance user experience, convenience, and personalization.

The enterprise devices segment is anticipated to expand at a substantial CAGR during the forecast period. Enterprise devices are used within businesses, organizations, and institutions to support operations, productivity, and decision-making processes. These devices include edge servers, industrial IoT (IIoT) devices, networking equipment, surveillance cameras, and medical devices.

Edge AI processors in enterprise devices enable real-time data processing, predictive analytics, anomaly detection, and intelligent automation to improve operational efficiency, optimize resource utilization, and enhance security. Enterprises across various industries, such as manufacturing, healthcare, retail, transportation, and logistics, are adopting edge AI processors to capitalize on the benefits of edge computing and AI-driven insights.

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End-use Analysis

Based on end-use, the edge AI processor market is segregated into automotive & transportation, healthcare, consumer electronics, retail & e-commerce, manufacturing, and others.

The automotive & transportation segment is projected to hold a large market share during the projected period. Edge AI processor is used in autonomous vehicles, connected cars, intelligent transportation systems, and vehicle-to-everything (V2X) communication. Edge AI processors enable various tasks, such as real-time sensor fusion, object detection, path planning, and driver monitoring, which enhances safety, efficiency, and convenience in automotive and transportation applications.

The healthcare segment is expected to register a considerable CAGR in the coming years. In the healthcare sector, edge AI processors support applications such as remote patient monitoring, medical imaging analysis, predictive analytics, and personalized medicine. Edge AI processor enables real-time analysis of patient data, early detection of diseases, decision support for clinicians, and optimization of healthcare workflows, leading to improved patient outcomes and cost savings.