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Embedded AI Market Size, Share & Trends Analysis Report By Offering, By Data Type (Sensor Data, Image And Video Data, Numeric Data, Categorial Data), By Vertical, By Region, And Segment Forecasts, 2025 - 2030
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Embedded AI Market Summary

The global embedded AI market size was estimated at USD 9,966.3 million in 2024, and is projected to reach USD 21,930.4 million by 2030, growing at a CAGR of 14.1% from 2025 to 2030. The rising need for intelligent and autonomous systems that offer personalized experiences, along with the expansion of connected devices and IoT ecosystems for improved communication, will further stimulate market growth.

The increasing demand for more powerful and energy-efficient processors is driven by the need to effectively manage complex AI algorithms and integrate with Image & Video Data-based AI services, enhancing scalability and providing users with opportunities to utilize embedded AI solutions.

The growing demand for advanced technologies that deliver personalized and adaptive experiences is driving the acceptance of embedded AI solutions in the market. The push for personalized interactions has led to the incorporation of AI capabilities into several embedded systems. By utilizing embedded AI, devices and applications can analyze user data, preferences, and behaviors to offer customized recommendations, suggestions, and responses, thereby boosting user satisfaction and engagement. In addition, embedded AI solutions can facilitate autonomous behavior in devices and systems, minimizing the need for continuous user input. This is especially valuable in areas like autonomous vehicles, smart home automation, and industrial automation, where AI algorithms can support intelligent decision-making and automated actions.

Offering Insights

The software segment led the market with the largest revenue share of 41.9% in 2024. Embedded AI software is vital in the market, offering essential algorithms, frameworks, and libraries that empower AI capabilities within embedded systems. This software harnesses the potential of AI in embedded devices, facilitating intelligent decision-making, real-time data analysis, and improved functionality across diverse industries. By enabling local data processing and interpretation, embedded AI software enhances device autonomy, boosts performance, and enriches user experiences. Moreover, the proliferation of connected devices and the rising demand for real-time data processing are fueling the need for sophisticated embedded AI solutions. This trend is evident in sectors such as automotive, healthcare, and industrial automation, where embedded AI software is revolutionizing operations and user interactions. As technology continues to evolve, the embedded AI software industry is expected to grow rapidly, driven by in

novations that enable smarter, more adaptable, and cost-effective solutions

The hardware segment is predicted to experience at the fastest CAGR over the forecast period. The growth is driven by the increasing demand for more powerful and energy-efficient processors capable of handling complex AI algorithms. As AI applications become more sophisticated and resource-intensive, the need for advanced hardware solutions, such as high-performance CPUs, GPUs, and specialized AI accelerators, is surging. This trend is further fueled by the growing adoption of autonomous and intelligent systems that require tailored experiences, prompting manufacturers to innovate and enhance their hardware offerings. In addition, the rise of edge computing is reshaping the landscape, as devices increasingly process data locally, reducing reliance on Image & Video Data services and enabling faster decision-making.

Global Embedded AI Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the global embedded AI market report based on offering, data type, vertical, and region:

Table of Contents

Chapter 1. Methodology and Scope

Chapter 2. Executive Summary

Chapter 3. Embedded AI Market Variables, Trends, & Scope

Chapter 4. Embedded AI Market: Offering Estimates & Trend Analysis

Chapter 5. Embedded AI Market: Data Type Estimates & Trend Analysis

Chapter 6. Embedded AI Market: Vertical Estimates & Trend Analysis

Chapter 7. Embedded AI Market: Regional Estimates & Trend Analysis

Chapter 8. Competitive Landscape

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