Edge AI Market Report 2026

The edge artificial intelligence (AI) market size has grown exponentially in recent years. It will grow from $29.08 billion in 2025 to $37.51 billion in 2026 at a compound annual growth rate (CAGR) of 29%. The growth in the historic period can be attributed to growing adoption of on device computing solutions, increasing demand for low latency data processing, rising deployment in industrial automation, expansion of smart devices and internet of things (IOT) applications, growing focus on real time decision making.

The edge artificial intelligence (AI) market size is expected to see exponential growth in the next few years. It will grow to $102.97 billion in 2030 at a compound annual growth rate (CAGR) of 28.7%. The growth in the forecast period can be attributed to increasing integration of artificial intelligence (AI) at the network edge, rising demand for privacy preserving and secure data processing, growing adoption in autonomous systems and smart infrastructure, expansion of edge computing platforms and devices, rise in investment for efficient and scalable AI deployments. Major trends in the forecast period include technology driven innovations in edge computing hardware and software, advancements in artificial intelligence (AI) model optimization for edge devices, developments in low power and high performance processing systems, rising research and development in real time analytics and inference, innovation in distributed and federated AI architectures.

The increasing adoption of Internet of Things (IoT) devices is expected to drive the expansion of the edge artificial intelligence (AI) market. IoT devices consist of a network of interconnected gadgets, including smartphones, sensors, wearables, smart home appliances, and security cameras, which communicate and share data over the internet without human intervention. The demand for IoT-connected devices is growing due to the need for real-time data, as they improve efficiency, enable remote monitoring, and support smarter decision-making across various sectors. Edge AI boosts IoT device utilization by allowing real-time data processing and decision-making directly on the devices, reducing latency and dependence on cloud infrastructure. It enhances device performance, reliability, and scalability, encouraging wider deployment across industries. For example, in September 2024, IoT Analytics, a Germany-based research firm specializing in IoT insights, reported that the number of connected IoT devices reached 16.6 billion in 2023, marking a 15% increase from 14.4 billion in 2022. Consequently, the growing adoption of IoT devices is fueling the growth of the edge AI market.

Major companies operating in the edge artificial intelligence (AI) market are emphasizing the development of advanced technological platforms, such as integrated edge computing solutions, to facilitate real-time, energy-efficient AI inference directly on devices and sensors while minimizing latency and operational costs. Full-scale onboard CO₂ capture systems involve integrated carbon capture technologies installed directly on ships, vehicles, or industrial machinery that actively capture and store carbon dioxide emissions at the source during operation. For example, in February 2025, Arm Holdings Ltd., a UK-based semiconductor design firm, introduced the Armv9 edge AI platform. It features a highly efficient Cortex-A320 CPU that delivers a tenfold improvement in machine learning performance compared to its predecessor, alongside the Ethos-U85 NPU. The platform includes an expanded Arm Kleidi for IoT software toolkit, offering up to a 70% performance enhancement for AI frameworks and seamless integration with popular tools like Llama.cpp, simplifying development for more than 20 million developers. Additionally, it incorporates advanced Armv9.2 security capabilities, such as Pointer Authentication and Memory Tagging Extension, providing a critical security foundation for exposed edge devices managing sensitive data in industrial and smart city environments.

In March 2025, Qualcomm Technologies, Inc., a US-based provider of semiconductor products and wireless technology solutions, acquired Edge Impulse Inc. for an undisclosed sum. Through this acquisition, Qualcomm seeks to enhance its edge AI and IoT ecosystem by incorporating Edge Impulse’s comprehensive edge AI development platform into Qualcomm’s hardware and software portfolio, thereby expanding developer support and speeding up AI deployment across a variety of edge devices. Edge Impulse Inc. is a US-based company offering an edge AI platform that allows developers to create, optimize, and deploy machine learning models directly on connected devices.

Major companies operating in the edge artificial intelligence (AI) market are Amazon Web Services Inc., Google LLC, Intel Corp., Qualcomm Incorporated, NVIDIA Corporation, NXP Semiconductors N.V., Renesas Electronics Corporation, Arm Limited, Ambarella Inc., CEVA Inc., TensTorrent Inc., EdgeCortix Inc., Samsung Electronics Co. Ltd., Horizon Robotics Inc., Mythic Inc., BrainChip Holdings Ltd., Texas Instruments Incorporated, Kneron Inc., Syntiant Corporation, Blaize Inc., Azure LLC, Edge Impulse Inc., Luxonis Inc., MediaTek NeuroPilot.

North America was the largest region in the edge artificial intelligence (AI) market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the edge artificial intelligence (AI) market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the edge artificial intelligence (AI) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

Tariffs have influenced the edge artificial intelligence market by increasing the cost of imported hardware components such as edge servers, gateways, and sensor devices. this has slowed deployment particularly in regions like north america and europe that rely on global supply chains. the software and services segments are less affected but experience indirect cost pressures. positive impacts include driving local manufacturing investments and encouraging innovation in cost-efficient edge solutions.

Edge artificial intelligence (AI) involves implementing AI capabilities directly on local devices and edge computing systems where data is produced, rather than depending entirely on centralized cloud infrastructure. Its main goal is to facilitate real-time data processing, low-latency decision-making, and improved data privacy through on-device intelligence. It also enables quicker response times, lowers bandwidth consumption, and ensures robust operations across connected digital ecosystems.

The key components of edge artificial intelligence include hardware, software, edge-cloud infrastructure, and services. Hardware consists of devices that process and run AI tasks at the network edge. Platform types include thin edge devices, thick edge or edge gateways, and enterprise or near-edge systems. Deployment modes include cloud and on-premises. Applications include autonomous vehicles and robotics, predictive maintenance, intelligent surveillance, personalization, remote monitoring, and diagnostics, across industries such as smart cities, manufacturing, consumer electronics, automotive, healthcare, government, energy, IT and telecommunications, retail, and others.

The edge artificial intelligence (AI) consists of revenues earned by entities by providing services such as on device machine learning processing, real time analytics at the network edge, intelligent data filtering, embedded artificial intelligence model deployment, and edge computing optimization. The market value includes the value of related goods sold by the service provider or included within the service offering. The edge artificial intelligence (AI) includes sales of edge processors, artificial intelligence enabled chips, embedded artificial intelligence software platforms, and edge computing hardware systems. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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