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.
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 Size was valued at USD 8,304.1 million in 2022. The Embedded AI Industry is projected to grow from USD 9,544.8 million in 2023 to USD 43,436.0 million by 2032, exhibiting a compound annual growth rate (CAGR) of 20.9% during the forecast period (2023 - 2032).
Embedded AI Market, commonly known as Embedded Artificial Intelligence (EAI), is a general-purpose AI framework system. It is embedded into network devices and provides common model management, data gathering, and data preprocessing features for these devices' AI algorithm-based functions. It also has the ability to submit inference findings to AI algorithm-based functions. This completely exploits the sample data and computational capabilities of devices, while also providing benefits such as reduced data transfer costs, data security, and real-time inference and decision-making.
The market for Embedded AI Market is influenced by factors such as growing demand for intelligent and autonomous systems, increasing developments in Al and ML technologies enable better and smarter decisions, and Embedded Al is increasingly being used for industry-specific applications. The market offers several opportunities for industry players and new entrants to research and develop technological solutions that may provide the ability to solve problems in day-to-day business activities.
FIGURE 1: EMBEDDED AI MARKET SIZE (2019-2032) (USD MILLION)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
By 2025, half of cloud data centers will deploy advanced robots with artificial intelligence (AI) and machine learning (ML) capabilities. Cloud computing provides several advantages for AI. First is the scalability and flexibility of resources based on needs. This allows Embedded AI Market systems to handle fluctuations in data processing needs without impacting performance. Cloud offers a variety of pre trained models library for various tasks. This allows developers to quickly integrate AI functionalities into embedded devices without building models from scratch. Problems like restricted processing power, and storage capacity, among others are not likely on cloud platforms. Cloud platforms provide tools for Embedded AI Market systems for tracking and monitoring. Cloud AI services provide ready-made intelligence for the applications and workflows. AI Services easily integrate with the applications to address common use cases such as personalized recommendations, modernizing the contact centre, improving safety and security, and increasing customer engagement.
Few examples of Cloud based AI include Image and Video Recognition, Natural Language Processing (NLP), and Predictive Analytics among others. Cloud based AI services offer cost effectiveness by offering features based on needs, updating and training models as the infrastructure and tools are already provided. Integration of AI by cloud platforms is also facilitated easily. Cloud services have access to APIs (Application Programming Interfaces) that simplify the process of integrating AI into applications.
A growing opprtunity is the combination of cloud and edge computing for AI applications. Cloud platforms will handle complex tasks and model training, while edge devices will perform real-time, low-latency processing at the network's edge. Cloud services remove the need for on-site infrastructure management, reducing upfront costs associated with purchasing and maintaining hardware.
Based on offering, the global Embedded AI Market is segmented into hardware, software and services. In 2023, the hardware segment is expected to have the largest market share. The hardware segment includes Embedded AI Market systems' physical components like processors, memory modules, sensors, and other electronic parts. To empower simulated intelligence capacities in implanted gadgets, equipment gives the essential network and computational power.
FIGURE 2: EMBEDDED AI MARKET SHARE BY OFFERING 2022 VS 2032 (USD MILLION)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Based on data type, the global Embedded AI Market is segmented into sensor data, image and video data, numeric data, caterogical data and others. Due to high level of reliability and accuracy, sensor data had the largest market share of XX percent in 2022. Information gathered from various embedded sensors, such as temperature, motion, proximity, and environmental sensors, is referred to as sensor data. This kind of information gives ongoing bits of knowledge into the actual world, empowering applications like natural checking, modern computerization, and brilliant home frameworks.
The Embedded AI Market based on industry vertical has been bifurcated into BFSI, IT & telecom, retail & ecommerce, manufacturing, energy & utilities, transportation & logistics, healthcare & life sciences, media & entertainment, automotive and others. In 2022, the IT & telecom segment is expected to have the largest market share. In the IT and Telecom industry, implanted computer based intelligence is used for network improvement, prescient upkeep, client experience the executives, wise remote helpers, and online protection. Embedded AI Market is used by technology companies and telecom operators to increase network efficiency, automate customer support, and create novel services and applications.
By region, the study segments the market into North America, Europe, Asia-Pacific, the Middle East, & Africa, and South America. North America had the greatest market share in 2022. North America stands as a pioneer in technological innovation, particularly in the field of AI. The region boasts a robust ecosystem of tech giants, startups, and research institutions driving the development of Embedded AI Market solutions. Silicon Valley, particular, serves as a hub for cutting edge-AI research and development. The presence of leading companies like Google, Microsoft, and Qualcomm among others further fuels innovation in embedded technologies.
In the North American region, Embedded AI Market is used extensively in healthcare, automotive, and consumer electronics industries. In medical services, implanted computer based intelligence fueled gadgets are altering patient consideration through remote checking, prescient examination, and customized therapy proposals. Also, the auto business is utilizing implanted man-made intelligence for independent driving elements, which improves the security and productivity on the streets.
FIGURE 3: EMBEDDED AI MARKET SHARE BY REGION 2022 VS 2032 (USD Million)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Asia Pacific is expected to be the fastest growing region in Embedded AI Market. Asia Pacific area is likewise seeing quick reception pace of Embedded AI Market reasoning in which implanted man-made intelligence is no special case. It is primarily powered by expansion of brilliant gadgets, quick urbanization, and expanding web infiltration. In a variety of industries, China, Japan, and South Korea are leading the way in AI innovation and development.
Europe is expected to be the second-largest market over the projection period. Europe is likewise at developing speed in Embedded AI Market, driven by serious areas of strength for an on moral simulated intelligence standards and information security guidelines like General Data Protection Regulation (GDPR). European nations focus on mindful artificial intelligence Advancement, zeroing in on straightforwardness, responsibility, and decency in artificial intelligence calculations.
Manufacturers in the region are at the forefront of the adoption of Embedded AI Market, incorporating AI-powered features into automobiles to improve safety, navigation, and driver assistance systems. Moreover, European medical care suppliers are progressively sending inserted man-made intelligence answers for illness analysis, customized therapy arranging, and medication disclosure.
The countries considered in the scope of the Embedded AI Market are the U.S, Canada, Mexico, Germany, France, UK, Italy, Spain, Poland, Netherlands, Rest of Europe, China, Japan, India, Australia, South Korea, Malaysia, Indonesia, Rest of Asia Pacific, Brazil, Argentina, Colombia, Rest of South America, Saudi Arabia, UAE, South Africa, and Rest of Middle East & Africa.
The Embedded AI Market is expected to witness high competition as this technology helps industries to present and design product/services easily. Some of the key players in Embedded AI Market are Microsoft, Google, IBM, Siemens, AWS, NVIDIA, Intel, Qualcomm, STMicroelectronics, Oracle, Salesforce, NXP, Lattice, Octonion and HPE among others.
The competition in the Embedded AI Market is driven by various factors, including pricing, quality, delivery time, and the ability to offer customized solutions to customers. Moreover, partnerships and collaborations with other players in the industry, such as service providers and suppliers, are crucial for companies to remain competitive in the market. Mergers and acquisitions are also common in the Embedded AI Market, as companies seek to expand their reach and capabilities. Additionally, the growth of the vendors is dependent on market conditions, government support, and industrial development.
These companies are concentrating on developing Embedded AI Market products with powerful technologies, and these technology allows workers to execute activities in a 360-degree context. Although the international players dominate the market, regional and local players with small market shares also have a significant presence. Moreover, they are focusing on product development and expansion to expand their product portfolio and enhance their customer relationships. Additionally, the companies are investing in the development of new and innovative AI solution.
MicroStrategy has just introduced new generative AI capabilities that allow companies to integrate AI-powered insights into their employees' workflows. In 2019, the company initially launched HyperIntelligence, which is an embedded analytics platform that provides business intelligence insights to users without requiring any clicks. In March 2024, MicroStrategy introduced Auto, a generative AI-powered bot that can be embedded into any application and allows for natural language interactions with data. The latest iteration of MicroStrategy One incorporates AI-powered insights that seamlessly integrate HyperIntelligence and Auto functionalities. Collectively, they empower users to further explore the insights derived from HyperIntelligence by leveraging the generative artificial intelligence capabilities of Auto.
According to Doug Henschen, an analyst at Constellation Research, it was reasonable for MicroStrategy to combine HyperIntelligence with Auto, as both features already existed separately within its platform. In October 2023, the vendor introduced its initial suite of generative AI functionalities, which encompassed natural language inquiry and explanation, as well as the production of code in natural language to facilitate the creation of data tables and database operations. Subsequently, in March, MicroStrategy released Auto, which expanded the company's generative AI capabilities outside the business intelligence (BI) domain and made them embeddable
In June 2024, Inventive, a firm located in Silicon Valley, commenced operations after securing $6.5 million in venture funding. Inventive specializes in integrating artificial intelligence into enterprise software-as-a-service (SaaS) solutions. Wing VC, a venture capital firm recognized for supporting firms that prioritize artificial intelligence (AI), is leading this funding round. Tokyo Black and a notable collection of angel investors, including former executives from Google and Meta, are also contributing. The injection of funds will accelerate Inventive's objective to simplify the incorporation of artificial intelligence into software products used by customers, allowing enterprises to provide more intelligent and efficient solutions.
Inventive is committed to assisting large businesses and rapidly expanding organizations in enhancing the customer experience and increasing revenue through the integration of a conversational AI copilot. The AI Analyst seamlessly connects into SaaS solutions, enabling customers to effortlessly explore, save, and operationalize insights derived from their reliable data using natural language. This emphasis on fundamental company operations expands data capacity to fulfill a wide range of client requirements.
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