There have been several market characteristics that have emerged that drive demand for smart and autonomous products resulting into significant growth in embedded AI market in recent years.
The rise of Internet of Things (IoT) is one of the key market trends driving the growth in embedded AI market. With increasing numbers of connected devices and growing demands for real-time data analysis, there has been an increase in demand for embedded artificial intelligence solutions capable processing and analyzing data locally. Unlike a server based or cloud-based computing system where these decisions would be made at, edge computing contains intelligent IoT endpoints that can make decisions independently without relying on backhaul connection to a central site.
Additionally, there is a shift towards edge computing being observed in the market currently. It refers to carrying out data processing as well as analysis right from where they were obtained rather than sending it back to any centralized cloud or even a data center The importance played by Embedded AI in edge computing includes reduction latency performing complex tasks locally improving privacy/security among others. Consequently this factors has pushed industries such as automotive manufacturing health care as well as smart homes into adopting embedded AI solutions that require real-time and local data analysis.
Consequently, there is growing need for energy efficient embedded AI system. This can cause an increase in power consumption when the devices become more intelligent and autonomous since they require much processing power. Embedded AI technologies have been developed to deal with this problem by consuming less power while still ensuring high performance. As a result, Energy efficiency and environmental friendliness are now becoming important consideration in the design and development of embedded AI since the energy required to run these machines is very high.
Another market trend in the embedded AI market is hardware acceleration and specialized chips. Often CPUs do not have good performance when it comes to AI tasks, thus having limited computing ability and consuming much power. These limitations made designing specialized chips such as GPUs, FPGAs or even ASICs specifically for artificial intelligence workloads possible.
On top of this, there has been increasing integration of embedded AI into consumer electronics and smart devices. In order to offer personalized intelligent experiences, smartphones, smart speakers wearables among other consumers’ electronic gadgets increasingly include embedded artificial intelligence capabilities that allows them to understand consumer preferences adapt accordingly and operate autonomously.
Moreover, the market is facing increased adoption of autonomous vehicles and robotics. Embedded AI helps in aiding self-driving cars and robots to sense their environment, reason, make intelligent decisions, and negotiate with complex situations. These applications need localized AI processing for real-time functions such as object detection, path planning or decision-making. This trend has led to development of embedded AI solutions that target autonomous systems specifically hence propelling growth in automotive and robotics sectors.
Report Attribute/Metric | Details |
---|---|
Market Opportunities | IoT integration, and automotive advancements |
Market Dynamics | Rapid technological advancements |
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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