Artificial Intelligence (AI) Edge Computing Market Report 2025

This report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.

The artificial intelligence (AI) edge computing market size has grown exponentially in recent years. It will grow from $20.29 billion in 2024 to $24.54 billion in 2025 at a compound annual growth rate (CAGR) of 20.9%. The growth in the historic period can be attributed to proliferation of IoT devices, advancements in edge computing technology, increasing demand for real-time data processing, growth of AI and machine learning applications, rising concerns over data privacy and security.

The artificial intelligence (AI) edge computing market size is expected to see exponential growth in the next few years. It will grow to $53.18 billion in 2029 at a compound annual growth rate (CAGR) of 21.3%. The growth in the forecast period can be attributed to expansion of 5G networks, adoption of edge AI in autonomous vehicles, emergence of Industry 4 initiatives, integration of AI into edge devices, accelerated deployment of edge computing infrastructure. Major trends in the forecast period include edge AI market consolidation, rise of edge AI as a service (AIAAS), shift towards decentralized AI architectures, rise of hybrid edge-cloud computing models, increasing focus on edge AI sustainability and energy efficiency.

The growing adoption of artificial intelligence (AI) automation in industrial machinery is expected to drive the growth of the AI edge computing market. AI automation involves using AI technologies to perform tasks and processes that typically require human input. AI edge computing supports this automation by enabling real-time data processing and decision-making at the network's edge, where the machinery operates. For example, in May 2022, a report by International Business Machines Corporation (IBM), a US-based technology company, highlighted that global AI adoption increased significantly, reaching 35%, up four points from the previous year. In 2022, 13% more companies were expected to adopt AI compared to 2021. Additionally, 35% of organizations reported adopting AI, while 42% were considering it, with two-thirds of companies (66%) either already using or planning to use AI to achieve their sustainability goals. As a result, the growing implementation of AI automation in industrial machinery is fueling the growth of the AI edge computing market.

Major companies operating in the artificial intelligence (AI) edge computing market are developing innovative products such as NVIDIA Jetson AGX Orin for edge AI applications. The NVIDIA Jetson AGX Orin is a high-performance system-on-module (SoM) designed for edge AI applications. For instance, in March 2022, Nvidia, a US-based software company, launched NVIDIA Jetson AGX Orin, specifically built for embedded systems and edge computing devices. The Jetson AGX Orin features the latest Orin system-on-chip (SoC), which is based on NVIDIA's Ampere architecture and includes multiple GPU cores, CPU cores, and specialized accelerators for AI inference and computer vision tasks. The NVIDIA Jetson AGX Orin is designed to provide high-performance AI capabilities in a compact and energy-efficient form factor, making it suitable for a wide range of edge AI applications in industries such as robotics, autonomous vehicles, and healthcare.

In August 2023, Sidus Space, a US-based satellite manufacturing and space data-as-a-service business, acquired Exo-Space for $0.468 million. The acquisition is expected to enhance Sidus Space's presence in the Earth and space industries and integrate edge computing with its satellite sensors. Exo-Space is a US-based company specializing in AI edge computing for software and space hardware.

Major companies operating in the artificial intelligence (AI) edge computing market are Apple Inc., Google LLC, Samsung Electronics Co. Ltd., Microsoft Corporation, Dell Technologies Inc., Huawei Technologies Co. Ltd., Siemens AG, General Electric Company (GE), Intel Corporation, Accenture PLC, IBM Corporation, Cisco Systems Inc., Oracle Corporation, Honeywell International Inc., SAP SE, Fujitsu Limited, Hewlett Packard Enterprise (HPE), NVIDIA Corporation, NEC Corporation, Advanced Micro Devices Inc. (AMD), MediaTek Inc., Baidu Inc., Xilinx Inc., RIGADO LLC, Amazon Web Services (AWS)

North America was the largest region in the artificial intelligence (AI) edge computing market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI) edge computing market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (AI) edge computing market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The artificial intelligence (AI) edge computing market includes revenues earned by entities by providing services such as edge AI development, edge device management, edge data processing and analytics, and edge security. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI) edge computing market also includes sales of edge computing devices, edge AI development kits, and edge AI management tools. 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).

Artificial intelligence (AI) edge computing refers to deploying AI algorithms and models on edge devices, such as sensors, cameras, or edge servers, located closer to the data source or end-user device. This approach brings AI capabilities directly to the network's edge, enabling real-time data processing, analysis, and decision-making without relying solely on centralized cloud servers.

The main components of artificial intelligence (AI) edge computing are hardware, software, and services. Artificial intelligence (AI) edge computing hardware refers to physical devices or components that are specifically designed to support AI inference and processing tasks at the edge of the network. They are used for industrial internet of things (IIoT), remote monitoring, content delivery, video analytics, augmented reality (AR) and virtual reality (VR), and other applications in various organizations such as large enterprises, and small and medium sized enterprises of automotive, healthcare, chemicals, oil and gas, manufacturing and robotics, public infrastructure, transportation and logistics, and other industry verticals.

The main components of artificial intelligence (AI) edge computing are hardware, software, and services. Artificial intelligence (AI) edge computing hardware refers to physical devices or components that are specifically designed to support AI inference and processing tasks at the edge of the network. They are used for industrial internet of things (IIoT), remote monitoring, content delivery, video analytics, augmented reality (AR) and virtual reality (VR), and other applications in various organizations such as large enterprises, and small and medium sized enterprises of automotive, healthcare, chemicals, oil and gas, manufacturing and robotics, public infrastructure, transportation and logistics, and other industry verticals.

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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