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Embedded AI Market Size

ID: MRFR//10733-HCR | 128 Pages | Author: Shubham Munde| May 2024

The growth and uptake of the market for embedded AI are driven by several market factors. These factors can be grouped into chip technology advancements, an increase in edge computing, the need for real-time decision-making and IoT (Internet of Things) devices.

Advanced chip technology is instrumental to the shaping of the embedded AI market. This makes them become more efficient; processors and microcontrollers advance as a result to have more power increased in them. It allows the incorporation of AI capabilities directly into embedded systems such as smartphones, smart appliances, and industrial machinery. Real-time analytics and decision-making at the edge are made possible by these embedded chips where AI algorithms may be optimized to run efficiently on them thus enabling. Businesses like these assists in advancing AI-embedded technologies via their hardware features necessary for it.

Embedded AI plays a crucial role in edge computing through which data is processed and analyzed closer to its source as opposed to depending on cloud-based services. Consequently, this approach reduces latency, minimizes bandwidth requirements, ensures privacy and security. This makes it possible for devices themselves do not require constant connectivity with cloud infrastructure while performing artificial intelligence functions at their ends.

The desire for real-time decision-making also influences the Embedded AI market.Real-time analysis of data is important in various applications that enhances efficiency hence effective operations. Embedded AI enables devices to process and analyze data on board without relying on external platforms or human intervention. This capability ensures immediate responses and prompt actions thus increasing productivity effectiveness as well as safety measures.

Another factor driving adoption of Embedded AI is rise in IoT devices. IoT devices are connected objects that collect data that can be exchanged over the internet. These generate so much information that requires processing or analysis within short periods. Embedded AI in IoT devices help in on-device inference and analytics thus reducing the need for continued data transfer to the cloud. Because of this, different industries have come up with their own definitions of what it means to be intelligent.

Covered Aspects:

Report Attribute/Metric Details
Market Size Value In 2022 USD 9.1 Billion
Market Size Value In 2023 USD 10.41 Billion
Growth Rate 14.50% (2023-2032)

Embedded AI Market Overview

Embedded AI Market Size was valued at USD 9.1 Billion in 2022. The embedded AI market industry is projected to grow from USD 10.41 Billion in 2023 to USD 30.78 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 14.50% during the forecast period (2023 - 2032). Growing demand for automation and smart devices is the key market drivers enhancing the market growth.

Embedded AI Market Size

Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Embedded AI Market Trends

Increased integration with IoT is driving the market growth

The growing integration with IoT is driving the market CAGR for embedded AI. IoT devices' intelligence and capacities are increased through the integration of AI. These devices have the capacity to process and analyze data locally, which enables them to make decisions in the present without the need for a constant internet connection or centralized cloud servers. IoT devices with AI capabilities, such as thermostats, can expertly learn user preferences, optimize energy use, and fine-tune settings for improved comfort, for instance, in smart homes. The user experience is significantly improved by this additional intelligence, thus increasing the value of IoT items.

Additionally, IoT devices generate a lot of data, which makes quick data analysis necessary for many applications. IoT devices can handle localized data locally thanks to embedded AI, which improves response times and lowers latency. Take industrial settings as an example, where AI-driven sensors may quickly identify anomalies or equipment breakdowns and urge fast action to save expensive downtime. Furthermore, real-time data processing has important ramifications for mission-critical applications like autonomous vehicles and healthcare monitoring, where a split-second choice could mean the difference between life and death.

In addition, energy economy is a major challenge for many IoT applications, particularly those that depend on battery power or are installed in remote areas. Intelligent power management is an area where embedded AI excels in improving device performance. AI systems, for instance, can determine when it is necessary to turn on sensors or send data, thus reducing overall energy use. This is particularly useful in fields like environmental monitoring and precision agriculture, where equipment may need to run over extended periods of time in remote locations.

The regular collection of sensitive data by IoT devices makes data privacy and security of the utmost significance. These issues are effectively addressed by embedded AI by enabling on-device data processing and encryption. This means that private information does not need to be sent to the cloud for analysis, reducing the possibility of data breaches or unwanted access. The IoT security architecture can be strengthened by using AI for device authentication, anomaly detection, and the identification of possible threats. As a result, the need for embedded AI solutions is anticipated to increase as IoT spreads across industries, thus boosting market growth over the course of the research period. Thus, driving the Web3 in E-Commerce & Retail market revenue.

Embedded AI Market Segment Insights

Embedded AI Offering Insights

The Embedded AI Market segmentation, based on Offering includes hardware, software and services. The software segment dominated the market in the Embedded AI Market. This is owing to the continuous advancements in AI algorithms, including developments in deep learning and neural networks.

Figure 1: Embedded AI Market, by Distribution channel, 2022 & 2032 (USD Billion)

Embedded AI Market, by Distribution channel, 2022 & 2032

Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Embedded AI Data Type Insights

The Embedded AI Market segmentation, based on data type, includes Sensor Data, Image and Video Data, Numeric Data, Categorical Data And Other Data Types (Iris & Facial Data, Time Series Data and Audio Data). The numeric data type generated the most revenue. Numerical data serves as the fundamental building block for training, enhancing, and implementing AI models within embedded systems.

Embedded AI Vertical Insights

The Embedded AI Market segmentation, based on vertical, includes BFSI, IT & ITLES, Retail & Ecommerce, Manufacturing, Energy & Utilities, Transportation & Logistics, Healthcare & Life Sciences, Media & Entertainment, Telecom, Automotive and Other Vertical (Government, Aerospace And Defense, Construction & Real Estate, Agriculture, Education and Travel & Hospitality). The automotive segment dominated the market in 2022. The incorporation of embedded AI to support features like adaptive cruise control and automated parking has been prompted by the growing interest in advanced driver assistance systems (ADAS), which has increased car safety and convenience.

Embedded AI Regional Insights

By region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. The North America embedded AI Market dominated this market in 2022 (45.80%). This is due to the region's strong technology ecosystem and high levels of innovation, which have provided a favorable environment for the creation and uptake of embedded AI solutions across a variety of industries. Further, the U.S. embedded AI market held the largest market share, and the Canada embedded AI market was the fastest growing market in the North America region.

Further, the major countries studied in the market report are The U.S., Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.



Source: Secondary Research, Primary Research, MRFR Database and Analyst Review

Europe embedded AI market accounts for the second-largest market share. This is because efforts like Industry 4.0 and industrial automation are receiving so much attention. Further, the German embedded AI market held the largest market share, and the UK embedded AI market was the fastest growing market in the European region

The Asia-Pacific embedded AI Market is expected to grow at the fastest CAGR from 2023 to 2032. This is due to the region's rising demand for applications involving automation, smart manufacturing, and the Internet of Things (IoT). Moreover, China’s embedded AI market held the largest market share, and the Indian embedded AI market was the fastest growing market in the Asia-Pacific region.

Embedded AI Key Market Players & Competitive Insights

Leading market players are investing heavily in research and development in order to expand their product lines, which will help the embedded AI market, grow even more. Market participants are also undertaking a variety of strategic activities to expand their global footprint, with important market developments including new product launches, contractual agreements, mergers and acquisitions, higher investments, and collaboration with other organizations. To expand and survive in a more competitive and rising market climate, embedded AI industry must offer cost-effective items.

Manufacturing locally to minimize operational costs is one of the key business tactics used by manufacturers in the global embedded AI industry to benefit clients and increase the market sector. In recent years, the embedded AI industry has offered some of the most significant advantages to medicine. Major players in the embedded AI market, including Google (US), IBM (US), Microsoft (US), AWS (US), NVIDIA (US), Intel (US), Qualcomm (US), Arm (UK), AMD (US), MediaTek (Taiwan), Oracle (US), Salesforce (US), NXP (Netherlands), Lattice (Oregon), Octonion (Switzerland), NeuroPace (US), Siemens (Germany), HPE (US), LUIS Technology (Germany), Code Time Technologies (Canada), HiSilicon (China), VectorBlox (Canada), Au-Zone Technologies (Canada), STMicroelectronics (Switzerland), SenseTime (Hong Kong), Edge Impulse (US), Perceive (US), Eta Compute (US), SensiML (US), Syntiant (US), Graphcore (UK), SiMa.ai (US), and others, are attempting to increase market demand by investing in research and development operations.

The International Business Machines Corporation, or simply IBM, is a global technology company with its headquarters in Armonk, New York. With operations in more than 175 nations, IBM is present all over the world. The business offers a range of services, including infrastructure, hosting, and consulting, in addition to manufacturing and selling system hardware and software. Artificial intelligence (AI), analytics, automation, cloud computing, blockchain, IT infrastructure, cybersecurity, and software development are all included in IBM's broad range of products. IBM offers services such cloud solutions, networking, security, technology consulting, business resilience services, application services, and technology support services as a complement to this. Its clientele comes from a variety of industries, including the automotive, banking, financial, energy, electronics, utilities, and life sciences; as well as the manufacturing, consumer goods, retail, and telecommunications industries. The corporation operates throughout the Asia-Pacific area, the Americas, Europe, the Middle East, and Africa.

Since its founding in 1968, Intel has played a crucial role in advancing computing technology. As a pioneer in its field, the business has contributed significantly to the development of revolutionary technology that promotes societal advancement and improves quality of life. Artificial intelligence (AI), the 5G network revolution, and the rise of the intelligent edge are just a few of the technical inflection points that Intel is currently on the verge of, all of which will collectively alter the direction of technology. These changes are mostly fueled by a combination of silicon and software, with Intel at the center of these revolutionary advancements. The business' broad range of products provides all-encompassing solutions that meet the changing needs of a data-centric world. Intel continuously creates innovative technologies and goods to serve a variety of markets, from edge computing and 5G networks to cloud computing, artificial intelligence, and driverless vehicles. These goods act as the cornerstones of a world that is becoming more intelligent and interconnected.

Key Companies in the Embedded AI market include

Embedded AI Industry Developments

May 2023: The newest Jetson AGX Orin Industrial module from NVIDIA enhances computing capabilities for demanding situations. The NVIDIA Jetson AGX Xavier Industrial and the commercial Jetson AGX Orin modules were this advanced module's predecessors, and they both built on their successes. It significantly improves computing performance and was created for ruggedized systems. The Jetson AGX Orin Industrial module has a configurable power range of 15–75 watts and boasts remarkable 248 TOPS of AI performance.

October 2022: IBM introduced three new libraries as part of the expansion of its embeddable AI software lineup. These libraries were designed to make it easier and faster for IBM Ecosystem partners, customers, and developers to construct their AI-driven solutions and sell them in a more effective and economical way.

Embedded AI Market Segmentation

Embedded AI Offering Outlook

  • Hardware

  • Software

  • Services

Embedded AI Data Type Outlook

  • Sensor Data

  • Image and Video Data

  • Numeric Data

  • Categorical Data

  • Other Data Types

    • Iris & Facial Data

    • Time Series Data

    • Audio Data

Embedded AI Vertical Outlook

  • BFSI

  • IT & ITLES

  • Retail & Ecommerce

  • Manufacturing

  • Energy & Utilities

  • Transportation & Logistics

  • Healthcare & Life Sciences

  • Media & Entertainment

  • Telecom

  • Automotive

  • Other Vertical

  • Government

  • Aerospace And Defense

  • Construction & Real Estate

  • Agriculture

  • Education

  • Travel & Hospitality

Embedded AI Regional Outlook

  • North America

  • U.S.

  • Canada

  • Europe

  • Germany

  • France

  • UK

  • Italy

  • Spain

  • Rest of Europe

  • Asia-Pacific

    • China

    • Japan

    • India

    • Australia

    • South Korea

    • Australia

    • Rest of Asia-Pacific

  • Rest of the World

    • Middle East

    • Africa

    • Latin America

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