AI based Edge Computing Chip Market was valued at USD 2.60 Billion in 2022 and is projected to reach USD 12.80 Billion by 2030, growing at a CAGR of 22.40% from 2024 to 2030.
The AI-based Edge Computing Chip market has seen significant growth from 2018 to 2022, driven by the rapid adoption of edge computing in industries such as automotive, healthcare, and telecommunications. These chips enable faster data processing at the edge of the network, minimizing latency and reducing reliance on cloud servers. In 2022 alone, the global market for AI-based edge computing chips reached a value of $3.5 billion, a sharp increase from $1.2 billion in 2018. This surge in demand was mainly fueled by advancements in artificial intelligence (AI) algorithms, IoT devices, and 5G connectivity, which require low-power, high-performance edge devices to process large amounts of data in real-time.
The need for AI-based edge computing chips is poised to accelerate even further from 2023 to 2033. Analysts predict that the market will grow at a compound annual growth rate (CAGR) of 25% over the next decade. As more industries adopt AI-powered devices and systems, demand for these chips will continue to rise. The integration of AI in edge computing allows for faster decision-making processes, essential in time-sensitive applications such as autonomous driving, healthcare diagnostics, and real-time manufacturing quality control. This is particularly important as businesses face the challenge of handling vast amounts of data generated by IoT devices, which require fast processing and local data storage capabilities.
With the proliferation of 5G technology, the AI-based edge computing chip market is expected to see an influx of new applications. The ultra-low latency and high-speed communication offered by 5G will enable real-time AI analytics at the edge, further driving the adoption of edge computing. The automotive sector, for instance, is poised to benefit from AI-based edge chips in autonomous vehicles that rely on immediate data processing to make split-second decisions. The healthcare industry is another major driver, where these chips are increasingly used in medical devices and patient monitoring systems, ensuring faster diagnoses and treatments.
As the demand for AI-based edge computing chips grows, manufacturers are focusing on developing more energy-efficient, cost-effective solutions without compromising on performance. Edge devices need to be small, lightweight, and capable of functioning in diverse environments, which presents challenges for chip manufacturers to balance performance and power consumption. Innovations in semiconductor materials and chip architectures, such as neuromorphic computing, are expected to drive the next phase of growth for this market, enabling even more sophisticated AI models to run directly on edge devices.
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Cambricon
Nvidia
Huawei Hisilicon
Horizon Robotics
ARM
Intel
By the year 2030, the scale for growth in the market research industry is reported to be above 120 billion which further indicates its projected compound annual growth rate (CAGR), of more than 5.8% from 2023 to 2030. There have also been disruptions in the industry due to advancements in machine learning, artificial intelligence and data analytics There is predictive analysis and real time information about consumers which such technologies provide to the companies enabling them to make better and precise decisions. The Asia-Pacific region is expected to be a key driver of growth, accounting for more than 35% of total revenue growth. In addition, new innovative techniques such as mobile surveys, social listening, and online panels, which emphasize speed, precision, and customization, are also transforming this particular sector.
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Growing demand for below applications around the world has had a direct impact on the growth of the Global AI based Edge Computing Chip Market
Smart Manufacturing
Smart Home
Smart Retail
Smart Transportation
Smart Finance
Smart Medical
Smart Driving
Other
Based on Types the Market is categorized into Below types that held the largest AI based Edge Computing Chip market share In 2023.
12nm
16nm
Others
Global (United States, Global and Mexico)
Europe (Germany, UK, France, Italy, Russia, Turkey, etc.)
Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam)
South America (Brazil, Argentina, Columbia, etc.)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)
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1. Introduction of the Global AI based Edge Computing Chip Market
Overview of the Market
Scope of Report
Assumptions
2. Executive Summary
3. Research Methodology of Verified Market Reports
Data Mining
Validation
Primary Interviews
List of Data Sources
4. Global AI based Edge Computing Chip Market Outlook
Overview
Market Dynamics
Drivers
Restraints
Opportunities
Porters Five Force Model
Value Chain Analysis
5. Global AI based Edge Computing Chip Market, By Type
6. Global AI based Edge Computing Chip Market, By Application
7. Global AI based Edge Computing Chip Market, By Geography
Global
Europe
Asia Pacific
Rest of the World
8. Global AI based Edge Computing Chip Market Competitive Landscape
Overview
Company Market Ranking
Key Development Strategies
9. Company Profiles
10. Appendix
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