Embedded AI Market Size & Share, by Offering (Hardware, Software, Services), Data Type (Sensor Data, Image & Video Data, Numeric Data, Categorial Data), End User (BFSI, IT & ITES, Retail & Ecommerce, Manufacturing, Energy & Utilities, Transportation & Logistics) - Global Supply & Demand Analysis & Growth Forecasts, Statistics Report 2024-2036

  • Report ID: 5715
  • Published Date: Feb 21, 2024
  • Report Format: PDF, PPT

Global Market Size, Forecast, and Trend Highlights Over 2024-2036

Embedded AI Market size is anticipated to reach USD 57 Billion by the end of 2036, growing at a CAGR of 8% during the forecast period, i.e., 2024-2036. In the year 2023, the industry size of embedded AI was USD 41 Billion. In recent years, the heightened demand for edge computing solutions, particularly within the Internet of Things (IoT) ecosystem, has emerged as a primary driver propelling the growth of embedded artificial intelligence (AI). Edge computing involves processing data closer to the source of generation, reducing latency and enhancing real-time decision-making capabilities. Edge computing, as a core growth driver for embedded AI, addresses the limitations of centralized cloud processing, which may introduce latency in data analysis. IoT devices, which generate vast amounts of data, necessitate rapid processing for applications such as smart homes, autonomous vehicles, and industrial automation. Embedded AI allows these devices to perform complex computations locally, ensuring timely responses and a seamless user experience. According to a report, the adoption of edge computing is projected to witness substantial growth, with the number of IoT devices surpassing 5.8 billion in 2021.

The surge in cyber threats and privacy concerns has accentuated the importance of processing sensitive data closer to its origin. Edge computing, powered by embedded AI, mitigates risks associated with data transmission to remote servers. This decentralized approach ensures that critical information remains on the device, bolstering privacy and security measures in applications like healthcare, where patient data confidentiality is paramount.


Embedded AI Market
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Embedded AI Market: Growth Drivers and Challenges

Growth Drivers

  • Proliferation of AI-Optimized Hardware - The proliferation of AI-optimized hardware, including dedicated AI chips and accelerators, is a significant catalyst for the growth of the embedded AI market. Traditional processors are often inadequate for handling the computational demands of AI algorithms. Hence, the development of specialized hardware, designed specifically for efficient AI execution, has become a cornerstone for embedding AI capabilities in various devices. The robust growth in the AI chipset market underscores the industry's recognition of the need for dedicated hardware to enhance the performance of embedded AI systems.
  • Integration of AI in Autonomous Vehicles - The integration of AI in autonomous vehicles is a pivotal growth driver for embedded AI. Advanced Driver-Assistance Systems (ADAS) and self-driving capabilities heavily rely on embedded AI for real-time decision-making and sensor fusion. The significant projected increase in the global autonomous vehicle market highlights the escalating demand for intelligent systems capable of processing vast amounts of data and making split-second decisions – a domain where embedded AI excels. A report stated that the global autonomous vehicle sales reached 37 million units by 2023.
  • Expansion in Healthcare IoT Devices - The expansion of healthcare IoT devices is a key driver for embedded AI applications in the healthcare sector. Wearable devices, remote patient monitoring, and other IoT-enabled healthcare solutions leverage embedded AI for tasks such as patient data analysis, predictive diagnostics, and personalized treatment plans. The substantial growth in the healthcare IoT market emphasizes the increasing adoption of smart, AI-infused devices to enhance patient care and optimize healthcare workflows.

Challenges

  • Power Consumption and Resource Constraints: Embedded devices, particularly those in IoT applications, often operate under strict power constraints and limited resources. Running sophisticated AI algorithms on resource-constrained devices can lead to increased power consumption, affecting the device's overall performance and battery life. This challenge can hinder the deployment of embedded AI in scenarios where energy efficiency is critical, such as wearable devices and remote sensors. Addressing these concerns is crucial to gaining user trust and ensuring compliance with privacy regulations. Failure to do so may limit the acceptance of embedded AI in certain applications, especially in healthcare and finance.
  • Integration Complexity and Standardization
  • Algorithmic Efficiency and Model Size

Embedded AI: Key Insights

Base Year

2023

Forecast Year

2024-2036

CAGR

~8%

Base Year Market Size (2023)

~ USD 41 Billion

Forecast Year Market Size (2036)

~ USD 57 Billion

Regional Scope

  • North America (U.S., and Canada)
  • Latin America (Mexico, Argentina, Rest of Latin America)
  • Asia-Pacific (Japan, China, India, Indonesia, Malaysia, Australia, Rest of Asia-Pacific)
  • Europe (U.K., Germany, France, Italy, Spain, Russia, NORDIC, Rest of Europe)
  • Middle East and Africa (Israel, GCC North Africa, South Africa, Rest of Middle East and Africa)
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Embedded AI Segmentation

Offering (Hardware, Software, Services)

The software segment in embedded AI market is estimated to gain the largest revenue share of about 62% in the year 2036. The rapid advances in artificial intelligence (AI) and machine learning are significant drivers for the growth of the software segment. The exponential increase in the number of ML applications on platforms like GitHub reflects the expanding landscape of AI-driven solutions. As machine learning algorithms become more sophisticated and accessible, software developers can integrate these capabilities into a wide array of applications, ranging from data analytics to automation. According to a report, the number of machine learning (ML) applications on GitHub has grown from around 8,000 in 2015 to over 200,000 in 2021. The emergence and widespread adoption of low-code and no-code development platforms are transforming the software development landscape. As the demand for software solutions continues to grow, these platforms enable developers with varying skill levels to create applications rapidly.

End User (BFSI, IT & ITES, Retail & Ecommerce, Manufacturing, Energy & Utilities, Transportation & Logistics)

The IT & ITES segment in embedded AI market is expected to garner a significant revenue share in the year 2036. The widespread adoption of remote work has become a significant growth driver for the IT & ITES (Information Technology and IT-enabled Services) segment. The shift towards remote work, accelerated by global events, has highlighted the importance of robust IT infrastructure, cloud solutions, and digital collaboration tools. As organizations continue to embrace flexible work arrangements, the demand for IT services to support remote work environments, including cybersecurity, cloud computing, and communication technologies, is on the rise. The escalating frequency and sophistication of cyber threats have made cybersecurity a critical growth driver for the IT & ITES segment. As organizations become increasingly digitized, the potential impact of cyber-attacks on business operations, data integrity, and customer trust has grown substantially. Cloud computing offers scalability, flexibility, and cost-effectiveness, making it a fundamental enabler for digital transformation initiatives.

Our in-depth analysis of the global embedded AI market includes the following segments:

          Offering

  • Hardware
  • Software
  • Services

 

 

          End User

  • BFSI
  • IT & ITES
  • Retail & Ecommerce
  • Manufacturing
  • Energy & Utilities
  • Transportation & Logistics

          Data Type

  • Sensor Data
  • Image & Video Data
  • Numeric Data
  • Categorial Data

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Embedded AI Industry - Regional Synopsis

APAC Market Forecast

The embedded AI market in the Asia Pacific region is projected to hold the largest revenue share of 43% by the end of 2036. The rapid growth of e-commerce and digital transformation in the retail sector is a significant driver for embedded AI in the Asia-Pacific region. Embedded AI technologies contribute to personalized recommendations, supply chain optimization, and fraud detection in e-commerce platforms. The Asia-Pacific e-commerce sales are expected to reach USD 3.5 trillion by 2025. The emphasis on smart cities and urban development initiatives is a key growth driver for embedded AI in the Asia-Pacific region. As countries invest in building sustainable and technologically advanced cities, embedded AI technologies contribute to intelligent infrastructure, efficient energy management, and enhanced public services. The digitization of healthcare and the integration of AI are driving forces for embedded AI in the Asia-Pacific region.

North American Market Statistics 

The embedded AI market in the North America region is projected to hold the second largest revenue share during the forecast period. In North America, a thriving ecosystem of research institutions, universities, and technology companies collaborates to push the boundaries of AI capabilities. The synergy between academic research and private-sector innovation creates an environment conducive to the growth of embedded AI. This commitment to R&D positions North America as a frontrunner in driving advancements in embedded AI technologies. North America, particularly the United States, has been at the forefront of adopting artificial intelligence across various industries. The high adoption rate signifies the region's willingness to integrate AI technologies into business operations. This widespread acceptance creates a fertile ground for the growth of embedded AI, as organizations seek to leverage the benefits of AI in enhancing efficiency, decision-making, and customer experiences. The pioneering role of North America in AI adoption extends to the development and implementation of embedded AI applications, from intelligent automation in manufacturing to AI-driven analytics in healthcare. 

Research Nester
Embedded AI Market size
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Companies Dominating the Embedded AI Landscape

top-features-companies
    • NVIDIA Corporation
      • Company Overview
      • Business Strategy
      • Key Product Offerings
      • Financial Performance
      • Key Performance Indicators
      • Risk Analysis
      • Recent Development
      • Regional Presence
      • SWOT Analysis
    • Intel Corporation
    • Qualcomm Technologies, Inc.
    • ARM Holdings
    • Google LLC
    • Microsoft Corporation
    • IBM Corporation
    • MediaTek Inc.
    • Texas Instruments Incorporated
    • Advanced Micro Devices, Inc.

In-the-news

In The News

  • Acquisition of Tower Semiconductor (February 2023): This major acquisition, expected to close in 2024, aims to strengthen Intel's foundry business and diversify their manufacturing capabilities.
  • Launch of 4th Gen Xeon Scalable Processors (January 2023): This new processor generation offers improved performance and security features for data centers and high-performance computing.

Author Credits:  Abhishek Verma, Hetal Singh


  • Report ID: 5715
  • Published Date: Feb 21, 2024
  • Report Format: PDF, PPT

Frequently Asked Questions (FAQ)

Increasing demand for IT & ITES sector is the major factor driving the market growth.

The market size of embedded AI is anticipated to attain a CAGR of 8% over the forecast period, i.e., 2024-2036.

The major players in the market NVIDIA Corporation, Intel Corporation, Qualcomm Technologies, Inc., ARM Holdings (Acquired by NVIDIA), Google LLC, Microsoft Corporation, and others.

The software segment is anticipated to garner the largest market size by the end of 2036 and display significant growth opportunities.

The market in the Asia Pacific region is projected to hold the largest market share by the end of 2036 and provide more business opportunities in the future.
Embedded AI Market Report Scope
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