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.
Growth Drivers
Challenges
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Base Year |
2023 |
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Forecast Year |
2024-2036 |
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CAGR |
~8% |
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Base Year Market Size (2023) |
~ USD 41 Billion |
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Forecast Year Market Size (2036) |
~ USD 57 Billion |
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Regional Scope |
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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:
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Offering |
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End User |
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Data Type |
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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.
Author Credits: Abhishek Verma, Hetal Singh
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