Artificial Intelligence for Edge Device Trends and Forecast
The future of the global artificial intelligence for edge device market looks promising with opportunities in the automotive, consumer and enterprise robotic, drone, head-mounted display, smart speaker, and mobile phone markets. The global artificial intelligence for edge device market is expected to grow with a CAGR of 19.0% from 2024 to 2030. The major drivers for this market are increasing adoption of IoT devices and growing concerns about data privacy and security.
• Lucintel forecasts that, within the type category, hardware is expected to witness the highest growth over the forecast period due to growing demand for AI-powered devices.
• Within the application category, mobile phone is expected to witness the highest growth due to rise in adaptation of mobile phones.
• In terms of regions, North America will remain the largest region over the forecast period due to rising adoption of edge computing and IoT devices and growing demand of smart home products.
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Emerging Trends in the Artificial Intelligence for Edge Device Market
In this market where AI is applied in edge devices, there are several emerging trends that are changing how this technology is created and used. These trends are becoming increasingly relevant due to the growing use of edge devices. They are instrumental in determining which trends will dominate the market for AI in edge devices in the near future.
• Increased Edge Processing Power: Improvements in edge neural computation result from revolutionary changes in AI chip design, which have increased the processing power of edge devices. New processors are suited for more complex AI tasks that can be performed locally, reducing the need to rely on cloud computing services and avoiding long delays. This movement enables on-the-go data gathering and analysis by users in applications such as self-driving trains and industrial automation.
• Improved Privacy and Security: With the increased use of edge devices, it becomes vital to protect data at the edge. Approaches such as federated learning and edge encryption have been adopted to ensure the safety of sensitive information and mitigate privacy issues without degrading performance.
• AI and IoT Convergence: The combination of artificial intelligence and the Internet of Things is advancing the commercial viability of marginal edge devices. Therefore, real-time processing and feedback on the environment are possible, enabling applications such as intelligent homes, manufacturing, and healthcare.
• Reduction of Energy Consumption and Environmental Impact: Due to growing concerns regarding energy use, there is a trend focusing on the design of energy-efficient AI systems and their supporting hardware. New energy-saving AI chips and various strategies are providing edge devices with necessary performance while minimizing their adverse effects on the environment.
• Edge AI Operationalization in Rural and Underdeveloped Regions: More attention is being paid to utilizing AI in rural areas and other outlying regions that may have connectivity limitations. Edge AI applications do not rely on centralized infrastructures, offering essential services, including healthcare and agricultural sustainability, in underserved areas.
Taken together, these emerging trends are accelerating the development of AI for edge devices, improving their capabilities, safety, and usability. The increased computing power, security, and energy efficiency prepare the industry for various aspects of the volatile technological environment.
Recent Developments in the Artificial Intelligence for Edge Device Market
The recent state of the art in AI for edge devices has made it possible to change the way data is collected, processed, and reused. These developments are significant in progress related to hardware, software, and applications, which will lead edge computing to its bright future. Achievements and their significance to different areas of the economy are illustrated in the form of innovations.
• Advancement in Edge AI Chips: The ability of edge devices to be utilized in more ways than in the past has been positively impacted by the packaging of devices dedicated to edge computing. These machines provide support for implementing machine learning applications that require vast computational resources while saving energy and allowing the computation of complex algorithms on the equipment in real time.
• AI-Powered Edge Security Solutions: Edge security has undergone transformative changes following the advent of advanced solutions supported by AI technology. This means that, in addition to basic software and data protection, proactive measures are employed to prevent attacks from occurring.
• Integration with 5G Technology: AI applications, such as smart-edge and IoT, will develop new capabilities with the integration of edge computing and 5G networks. Thanks to the high speed and ultra-reliable nature of 5G, edge devices can now handle real-time applications and perform data-heavy tasks, including autonomous driving and smart cities.
• Development of Low-Power AI Models: Institutions and companies are working towards the goal of power-efficient AI models suitable for edge devices with batteries. They are enhancing model tolerance to inadequate computational power through strategies such as model pruning and model quantization.
• Expansion of Edge AI Applications: The use cases for edge AI are increasing, with growing demand across sectors such as medical, agricultural, and manufacturing. Edge AI systems are being developed to meet specific efficiency needs, including long-distance surveillance and quick data processing.
These key developments in AI for edge devices are likely to bring considerable changes to the industry in terms of cost efficiency, safety, and a wider range of applications. However, existing technology will continue to evolve as these concepts drive further advancements in edge computing and its integration into various industries.
Strategic Growth Opportunities for Artificial Intelligence for Edge Device Market
The AI strategic growth perspective for edge devices is enormous, as it involves the transformational capabilities of these technologies across various application sectors. Focusing on key areas of growth helps stakeholders take advantage of these opportunities and enhance the innovation process.
• Smart Cities: Traffic management, public safety, and urban services are increasingly reliant on AI-based edge devices in the creation of smart cities. With edge computing, more data can be analyzed in real time, enhancing the infrastructure of cities and improving the standard of living for citizens.
• Healthcare Monitoring: In the healthcare field, there is increased use of edge devices enhanced with AI to monitor patients and diagnose diseases. More commonly, these activities are performed on the edge, where critical information can be extracted and used for remote health monitoring, early diagnosis of diseases, and customized therapy.
• Industrial Automation: The use of AI at the edge has provided tools to transform industrial automation with real-time feedback and control of manufacturing processes. Edge devices reduce operational downtime, improve predictive maintenance, and enhance production efficiency by removing bottlenecks.
• Agricultural Technology: Through the use of edge AI technology, agricultural practices have advanced, especially in precision farming and livestock management. By utilizing data from edge sensors and drones, farmers can determine how crops should be managed, when resources should be deployed, and estimate potential yields.
• Retail Analytics: In the retail domain, edge AI enables better user experiences through real-time analytics deployment. Edge devices enhance sales performance by tracking customer patterns, managing stock control, and improving the purchasing process for customers.
These strategic growth opportunities are shaping the future of AI for edge devices, particularly for applications in smart cities, healthcare, industrial automation, agriculture, and retail. Capitalizing on these opportunities will enhance technology development and extend the reach of edge computing.
Artificial Intelligence for Edge Device Market Driver and Challenges
The AI for edge devices market is influenced by a myriad of factors that are variable and contribute to the challenges faced by edge devices, including technology, economy, and regulation. Understanding these factors is paramount in addressing the challenges in this fluid environment.
The factors responsible for driving the artificial intelligence for edge device market include:
• Technological Advancements: Factors primarily in the technological domain, such as improvements in AI and edge computing technologies, are driving the market. Edge devices are therefore more efficient and sophisticated due to advancements in applications through new AI algorithms, hardware, and connectivity across all sectors.
• Economic Incentives: The cost of edge computing infrastructure is declining, and there is growing investment in AI, which is driving the uptake of AI for edge devices. Attractive pricing and better return on investment are encouraging businesses to adopt edge solutions.
• Regulatory Support: The growth of AI for edge devices is being facilitated by the existence of supportive policies. Governments and organizations are establishing guidelines and standards to regulate the use and development of technology effectively.
• Demand for Real-Time Processing: The need for real-time data processing continues to grow in many areas, including but not limited to autonomous vehicles and smart cities. Edge devices are essential for processing data on-site to avoid time wastage and achieve quicker decisions.
• Increased Connectivity: New connectivity technologies like 5G are enhancing the performance of edge devices. A robust, fast, and non-volatile network ensures ease of use for AI at the edge, which accelerates the rate of innovation.
Challenges in the artificial intelligence for edge device market are:
• Data Security and Privacy: A major challenge remains the data security and privacy of sensitive information processed at the edge. It is important to protect data by addressing threats and implementing effective security systems.
• Scalability Issues: One of the biggest problems faced, particularly in edge AI solutions, is the difficulty in scaling these solutions to meet the varying needs of different environments. There is a need for solutions that can adapt to users and specific use cases.
• Integration Complexity: Another challenge is that edge AI and existing systems and platforms do not integrate seamlessly. There is a significant need to ensure compatibility between platforms and systems.
The market for AI-based applications for edge devices faces both forces and pressures that challenge the rapid advancement of technology and the economic factors driving the development of this market. Data protection, scalability, and integration issues pose potential bottlenecks. Certain advancements, such as more sophisticated algorithms for AI and improved connectivity, enable real-time processing and expand the range of applications. However, addressing security vulnerabilities and achieving structural scalability and compatibility is crucial to enhancing market growth. The interplay of these factors will determine the direction of edge computing and its impact on various sectors and utilities.
List of Artificial Intelligence Companies for Edge Device Market
Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies artificial intelligence companies for edge device market cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the artificial intelligence companies for edge device market are profiled in this report include-
• Alibaba
• Apple
• Arm
• Baidu
• CEVA Logistics
• Cambricon
• Google
Artificial Intelligence for Edge Device by Segment
The study includes a forecast for the global artificial intelligence for edge device by type, application, and region.
Artificial Intelligence for Edge Device Market by Type [Analysis by Value from 2018 to 2030]:
• Hardware
• Software
Artificial Intelligence for Edge Device Market by Application [Analysis by Value from 2018 to 2030]:
• Automotive
• Consumer and Enterprise Robotics
• Drones
• Head-Mounted Displays
• Smart Speakers
• Mobile Phones
• Others
Artificial Intelligence for Edge Device Market by Region [Analysis by Value from 2018 to 2030]:
• North America
• Europe
• Asia Pacific
• The Rest of the World
Country Wise Outlook for the Artificial Intelligence for Edge Device Market
Application of Artificial Intelligence (AI) for edge devices globally has progressed rapidly due to the need for computing power, minimal latency, and maximum data security. The development of industries embracing edge computing technologies has accelerated the pace at which new technologies emerge, with more countries active on different fronts. This summary presents recent developments in the United States, China, Germany, India, and Japan regarding edge AI devices and interventions.
• United States: American efforts to improve edge devices by incorporating AI emphasize the enhancement of machine learning algorithms and hardware acceleration. NVIDIA and Intel are introducing breakthroughs through powerful edge GPUs and AI processors that are custom-made. Additionally, it is easier to integrate AI into Internet of Things (IoT) gadgets, enabling faster data processing and instant data-driven decisions. The United States also adopts a global perspective toward AI ethics and legislation, benefiting technology users.
• China: China has achieved significant progress in AI for edge devices, leveraging its capabilities in manufacturing high-performance chips. Huawei and Alibaba are advancing edge AI with neural network processors and AI accelerators. ChinaÄX%$%Xs focus areas include smart cities and industrial automation, applying AI to boost efficiency and improve oversight in security and manufacturing.
• Germany: With its strong automotive and industrial sectors, German companies are advancing edge AI technology. Organizations in Germany are using edge AI to address challenges in autonomous vehicle operation and smart factory technology. Due to the nation’s culture of order and discipline, incremental adoption of AI in edge computing is evident, enhancing data handling speed and operational efficiency across industries.
• India: India, with its affordable and scalable AI solutions for edge devices, has positioned itself as a significant player in this field. Indian startups are developing advanced edge AI solutions for agriculture, healthcare, and smart city sectors. The primary goal is to design compact, high-quality edge devices capable of addressing complex AI challenges, enabling users to solve local issues and expand market reach.
• Japan: Edge AI applications in Japan are strongly supported by its industrial base in robotics and electronics. Companies such as Sony and Toshiba are driving the development of small, powerful devices optimized for high-performance AI in edge applications. Japan focuses on combining AI with robotics to advance industrial automation and enhance consumer electronic products, pushing forward intelligent edge computing applications.
Features of the Global Artificial Intelligence for Edge Device Market
Market Size Estimates: Artificial intelligence for edge device market size estimation in terms of value ($B).
Trend and Forecast Analysis: Market trends (2018 to 2023) and forecast (2024 to 2030) by various segments and regions.
Segmentation Analysis: Artificial intelligence for edge device market size by type, application, and region in terms of value ($B).
Regional Analysis: Artificial intelligence for edge device market breakdown by North America, Europe, Asia Pacific, and Rest of the World.
Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the artificial intelligence for edge device market.
Strategic Analysis: This includes M&A, new product development, and competitive landscape of the artificial intelligence for edge device market.
Analysis of competitive intensity of the industry based on Porter’s Five Forces model.
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FAQ
Q1. What is the growth forecast for artificial intelligence for edge device market?
Answer: The global artificial intelligence for edge device market is expected to grow with a CAGR of 19.0% from 2024 to 2030.
Q2. What are the major drivers influencing the growth of the artificial intelligence for edge device market?
Answer: The major drivers for this market are increasing adoption of IoT devices and growing concerns about data privacy and security.
Q3. What are the major segments for artificial intelligence for edge device market?
Answer: The future of the artificial intelligence for edge device market looks promising with opportunities in the automotive, consumer and enterprise robotic, drone, head-mounted display, smart speaker, and mobile phone markets.
Q4. Who are the key artificial intelligence for edge device market companies?
Answer: Some of the key artificial intelligence for edge device companies are as follows:
• Alibaba
• Apple
• Arm
• Baidu
• CEVA Logistics
• Cambricon
• Google
Q5. Which artificial intelligence for edge device market segment will be the largest in future?
Answer: Lucintel forecasts that hardware is expected to witness highest growth over the forecast period due to growing demand for AI-powered devices.
Q6. In artificial intelligence for edge device market, which region is expected to be the largest in next 5 years?
Answer: North America will remain the largest region over the forecast period due to rising adoption of edge computing and IoT devices and growing demand of smart home products.
Q.7 Do we receive customization in this report?
Answer: Yes, Lucintel provides 10% customization without any additional cost.
This report answers following 11 key questions:
Q.1. What are some of the most promising, high-growth opportunities for the artificial intelligence for edge device market by type (hardware and software), application (automotive, consumer and enterprise robotics, drones, head-mounted displays, smart speakers, mobile phones, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
Q.2. Which segments will grow at a faster pace and why?
Q.3. Which region will grow at a faster pace and why?
Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
Q.5. What are the business risks and competitive threats in this market?
Q.6. What are the emerging trends in this market and the reasons behind them?
Q.7. What are some of the changing demands of customers in the market?
Q.8. What are the new developments in the market? Which companies are leading these developments?
Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?
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