Edge AI Market Size, Share and Trends 2025 to 2034

Revenue, 2024

USD 21.19 Bn

Forecast Year, 2034

USD 143.06 Bn

CAGR, 2025 - 2034

21.04%

Report Coverage

Global

What is Edge AI Market Size?

The global edge AI market size is calculated at USD 25.65 billion in 2025 and is anticipated to reach around USD 143.06 billion by 2034, growing at a solid CAGR of 21.04% over the forecast period 2025 to 2034. The edge AI market growth is attributed to the increasing demand for real-time data processing and the rapid advancements in edge computing technologies.

Market Highlights

• North America dominated the global edge AI market with the largest market share of 40% in 2024.
• Asia Pacific is projected to host the fastest-growing market in the coming years.
• By component, the software segment held a significant presence in the market in 2024.
• By component, the edge cloud infrastructure segment is expected to grow rapidly in the market during the forecast period of 2025 to 2034.
• By end-user, the smart cities segment accounted for a considerable share of the market in 2024.
• By end-user, the automotive segment is anticipated to grow with a significant CAGR in the market during the studied years.

Market Overview

The accelerating adoption of 5G technology is significantly driving the growth of the edge AI market. Edge AI, which involves processing data locally at the edge of a network rather than in a centralized data center, allows for real-time data analytics and decision-making with minimal latency. This technology is crucial for applications such as smart cities, autonomous vehicles, and industrial automation, where immediate data processing is required.

Additionally, the International Telecommunication Union (ITU) highlights that 5G technology enhances the performance of edge AI solutions, supporting innovations across various sectors, including healthcare and manufacturing.

Edge AI Market Growth Factors

• Advancements in AI and machine learning algorithms enhance the capabilities of edge computing.
• The emergence of smart homes and connected devices increases the demand for localized AI processing.
• Expanding use of IoT devices generates higher volumes of data that require local processing.
• Government initiatives and funding aimed at promoting edge computing infrastructure support market growth.
• Growing need for enhanced data security and privacy fuels the deployment of edge-based solutions.
• Increasing demand for real-time data processing drives the adoption of Edge AI technologies.
• The rising adoption of autonomous systems in various sectors necessitates efficient edge AI integration.

Edge AI Market Outlook

• Industry Growth Overview: Between 2025 and 2030, this market is expected to grow significantly due to the rapid deployment of edge AI in the healthcare sector coupled with rising emphasis of market players for developing advanced edge AI solutions for the manufacturing industry.
• Major Investors: Several AI companies and strategic investors are actively entering this industry, drawn by partnerships, R&D and investments. Various market players brands such as Alphabet Inc., Amazon.com, Inc, Gorilla Technology Group, Intel Corporation and some others have started investing rapidly for developing edge AI platforms for numerous end-user industries.
• Startup Ecosystem: Numerous startup companies are engaged in developing edge AI platforms to cater the needs of end-users. The prominent startup brands dealing in edge AI solution consists of Edge Impulse, Tenstorrent, Haptik and some others.

Market Scope

Market Dynamics

Drivers

Surging demand for low-latency processing

Increasing demand for low-latency processing is anticipated to drive the demand for the edge AI market, especially in industries such as autonomous vehicles, robotics, and smart cities. This real-time data processing is vital in areas where a decision has to be made on a real, real-time basis. Current tech goliaths and automotive giants, including Intel and Nvidia, are also designing edge AI hardware and software platforms to optimize real-time choices required for automobiles, and smart city solutions are applying edge computing for far adaptive traffic control and infrastructure monitoring.

The IDC estimated that edge computing is going to grow its spending in the international market and is expected to reach USD 6 billion by 2024 due to the requirement for latency-sensitive computations across automotive and smart infrastructure sectors.

• In a September 2024 report, the International Telecommunication Union (ITU) highlighted the growing integration of Edge AI in global smart city projects. The ITU noted that Edge AI technologies are crucial for managing urban infrastructure and improving public safety by providing real-time analytics and decision-making capabilities.

Restraint

High initial costs of deployment

The high initial costs associated with deploying edge AI infrastructure are expected to impede the edge AI market growth. These costs are rather high for the SMEs, as they not be able enough to purchase the required equipment, application, and network. The implementation of edge AI systems also has operational costs, which are related to maintaining and upgrading the systems due to advancements in technologies.

Integrating such state-of-the-art systems requires capital and makes small business in developing economies usually struggle to acquire finances to install such systems. Moreover, high energy consumption by intelligence devices and the need to cool them increases operation costs, especially in regions with expensive power. This has made organizations adopt the edge AI market slowly due to high costs.

Opportunity

Increasing use of edge AI in smart cities

The development of smart cities is expected to create immense opportunities for the players competing in the edge AI market. The rise of smart cities is leading to greater utilization of Edge AI for efficiently managing urban infrastructure and services. Surveillance cameras and smart grid operations AI technologies are used to enhance the use of resources for safety issues.

Edge AI improves the smart city response time and powers real-time analysis, thereby improving the cities' sustainability and efficiency. The application of the edge AI market helps to make improvements in public services such as tracking and maintenance of vehicles to foster better commuters and lower costs. Additionally, the edge AI enables cities to optimize environmental monitoring so the signs of pollution and climate change can be countered in time.

Segment Insights

Component Insights

The software segment held a significant presence in the edge AI market in 2024 due to the increasing demand for sophisticated data processing and artificial intelligence on different applications, such as smart cities and Industries. The U. S. National Institute of Standards and Technology (NIST) identifies the sophistication of the AI software in improving the operational and decision-making capabilities at the edge. This highlights the implementation of sound edge computing as dependent on the development of software. Furthermore, advanced-edge AI software technology is highly utilized for the processing and analysis of data.

• NIST states that the adoption of AI software in facilities involved in edge computing platforms improves 40% operational efficiency in various industries, thus creating their demand.

The edge cloud infrastructure segment is expected to grow rapidly in the edge AI market during the forecast period of 2024 to 2034, owing to the increasing need for superior computing capacity and low latency applications. Furthermore, the progression of network technologies has put a significant emphasis on the growth of this segment for future technological enhancements as the deployment of distributed cloud solutions.

• According to the DOE, the market for edge cloud infrastructures is set to grow and reach the figure of USD 20 billion by the year 2026, as it is necessary for effective data processing and network configurations.

End-user Insights

The smart cities segment accounted for a considerable share of the edge AI market in 2024. This sector has incorporated edge AI technologies to improve the control of urban conurbations and optimize infrastructure capacity. Technologies of smart cities apply edge AI in traffic systems, security systems, energy systems, and environmental systems. The rise of smart sensors and integrated, real-time analytics is aimed at enhancing the efficiency of resources and improving standards of living in urban environments. Furthermore, smart cities are propelling the edge AI market as an increasing trend toward sustainable urban growth and optimal resource utilization.

The automotive segment is anticipated to grow with a significant CAGR in the edge AI market during the studied years, owing to the rising utilization of advanced-edge AI technology for ADAS, autonomous cars, and connected automobiles. Vehicle edge AI is important, as it helps process data captured from the vehicle's sensors and cameras, which improves the safety and efficiency of vehicle operations. According to the U. S. Department of Transportation, the incorporation of Edge AI in automotive applications is expected to improve car safety and foster data-driven autopilot vehicles. Furthermore, the rising trend in the investment of the automotive industry in edge AI to enhance safety and connectivity requirements further boosts the market.

Edge AI Market Companies

• ADLINK Technology Inc.
• Alphabet Inc.
• Amazon.com, Inc
• Gorilla Technology Group
• Intel Corporation
• International Business Machines Corporation
• Microsoft Corporation
• Nutanix, Inc.
• Synaptics Incorporated
• Viso.ai

Segments Covered in the Report

By Component

• Software
• Hardware
• Edge cloud Infrastructure
• Services

By End-user Industry

• Smart Cities
• Manufacturing
• Consumer Electronics
• Automotive
• Healthcare
• Government
• Energy
• IT & Telecom
• Retail
• Others

By Region

• North America
• Asia Pacific
• Europe
• Latin America
• Middle East & Africa