Edge AI Market to Reach $73.8 Billion by 2031, Driven by AI at the Edge & Real-Time Processing | Exclusive report by DataM Intelligence

Leander, Texas and Tokyo, Japan - Dec.05.2025
As per DataM intelligence research report" Global Edge AI Market reached US$ 16.8 Billion in 2023 and is expected to reach US$ 73.8 Billion by 2031, growing with a CAGR of 20.6% during the forecast period 2024-2031." Low-latency processing and real-time analytics are accelerating adoption of edge AI across industries.

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United States: Recent Industry Developments

✅ In November 2025, NVIDIA announced the "Jetson Thor" module designed for humanoid robots and edge AI The module provides massive compute power in a small form factor for autonomous decision making It fuels the development of embodied AI in the U.S. robotics sector

✅ In October 2025, Qualcomm launched a new "AI Hub" for developers to deploy models on Snapdragon edge devices The platform optimizes large language models to run locally on phones and laptops It reduces reliance on the cloud and improves privacy for U.S. users

✅ In September 2025, Apple integrated a more powerful Neural Engine into the iPhone 17 specifically for on-device AI The hardware upgrade allows for real-time translation and image generation without internet It mainstream consumer Edge AI in the U.S. market

✅ In August 2025, Kinara raised funding to scale its dedicated Edge AI processors for smart retail cameras The chips enable real-time analytics of shopper behavior without sending video to the cloud It improves operational efficiency for U.S. retailers while respecting privacy

Japan: Recent Industry Developments

✅ In December 2025, Renesas Electronics released a new microcontroller with a built-in AI accelerator for motor control The chip uses "TinyML" to detect anomalies in factory motors before they fail It brings predictive maintenance to the edge of Japan's manufacturing lines

✅ In November 2025, Sony Semiconductor Solutions launched a new image sensor with integrated AI processing The sensor can identify objects and extract data directly on the chip It reduces data transmission costs for IoT devices in Japan's smart cities

✅ In October 2025, SoftBank Corp deployed "Edge AI Servers" at its 5G base stations across Tokyo The infrastructure enables low-latency AI applications like autonomous driving assistance It creates a distributed AI computing grid in Japan

✅ In September 2025, Preferred Networks partnered with a Japanese chipmaker to develop a low-power edge training chip The chip allows devices to learn and adapt to their environment locally It advances Japan's capability in decentralized AI learning

Edge AI Market: Drivers
The edge AI market is expanding as demand for real-time data processing, low latency, and enhanced privacy drives adoption in industrial, healthcare, automotive, and IoT applications. Edge AI enables AI computations locally on devices rather than relying solely on cloud infrastructure. Technological advancements in AI chips, low-power processors, and edge computing platforms are improving performance and scalability. Rising adoption of autonomous systems, smart devices, and predictive maintenance is driving market growth. Growing focus on data security, bandwidth optimization, and operational efficiency further strengthens adoption.

Collaboration among AI hardware developers, software vendors, and industrial solution providers is accelerating edge AI deployment. Growth in connected devices, robotics, and industrial automation expands application areas. Integration with cloud platforms, machine learning models, and IoT ecosystems enhances decision-making and analytics capabilities. Expansion of smart cities, intelligent transportation, and healthcare monitoring applications is broadening market potential. With continuous technological innovation and rising adoption of connected devices, the edge AI market is poised for long-term growth.

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Edge AI Market: Major Players
ADLINK Technology Inc., Alphabet Inc., Amazon.com, Inc., Gorilla Technology Group, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Nutanix, Inc. Synaptics Incorporated and Viso.ai.

Segment Covered in the Edge AI Market:
By Component
Hardware dominates with 35% share, driven by AI accelerators, sensors, and embedded chips required for on-device processing. Software holds 28%, including AI frameworks, analytics platforms, and model deployment tools. Edge cloud infrastructure captures 22%, supporting hybrid AI workloads and real-time data processing across distributed networks. Services contribute 15%, encompassing integration, consulting, and managed AI solutions. Together, these components enable scalable, low-latency Edge AI deployments across industries.

By Technology
Machine learning leads with 40% share, powered by deep learning and traditional ML models for predictive analytics, anomaly detection, and automation. Computer vision accounts for 25%, enabling object detection, video analytics, and quality inspection in real-time environments. Natural language processing holds 20%, supporting voice recognition, chatbots, and sentiment analysis at the edge. Predictive analytics captures 10%, optimizing operations and energy usage in industrial and commercial applications. Other AI technologies contribute 5%, spanning emerging algorithms and custom solutions.

By End-User
Consumer electronics dominate with 30% share, driven by smart devices, wearables, and home automation integrating Edge AI capabilities. Manufacturing holds 25%, leveraging predictive maintenance, process optimization, and real-time quality control. Automotive captures 20%, used in autonomous vehicles, driver assistance, and fleet management. Healthcare accounts for 12%, deploying Edge AI for patient monitoring, diagnostics, and imaging. Energy, government, and other sectors hold 13%, adopting AI for monitoring, security, and operational efficiency.

Regional Analysis
North America leads with 38% share, driven by strong adoption of AI-enabled consumer electronics, autonomous vehicles, and industrial automation across the U.S. and Canada. Europe holds 25%, supported by Germany, France, and the UK integrating Edge AI in manufacturing, automotive, and healthcare. Asia Pacific captures 28%, led by China, Japan, South Korea, and India, focusing on smart cities, industrial IoT, and AI-driven electronics. South America holds 5%, adoption primarily in Brazil and Argentina for manufacturing and telecommunication applications. Middle East & Africa account for 4%, driven by early adoption in smart infrastructure, energy management, and government projects.

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