Artificial Intelligence Chipsets Market Forecasts to 2030 – Global Analysis By Function (Inference and Training), Hardware, Technology, Processing Type, Application, End User and By GeographyAccording to Stratistics MRC, the Global Artificial Intelligence Chipset Market is accounted for $18.6 billion in 2023 and is expected to reach $123.8 billion by 2030 growing at a CAGR of 31.1% during the forecast period. Artificial intelligence (AI) chips are specialised silicon chips used for machine learning that contain AI technology. In several industry sectors, it aids in reducing or eliminating the risk to human life. As the amount of data has expanded, it has become increasingly important to develop systems that are more effective at addressing mathematical and computational issues. As a result, most of the big businesses in the IT sector concentrate on creating AI chips and software.
According to PricewaterhouseCoopers (PwC), European industries such as manufacturing, automotive, electronics, and others are expected to invest USD 182.04 billion in the Industry 4.0 solutions in 2020.
Market Dynamics:
Driver:
Growing adoption of cloud-based solutions
The expansion of data centre construction in industries such as IT & telecom, automotive, etc. is projected to increase demand for cloud-based Al chipsets. Data volume has greatly increased as a result of social media and e-commerce becoming more widely used. The chipset takes care of the need for quicker processing caused by machine learning that is activated. The need for high-speed processors has increased as a result of the data volume's quick growth, which is favorably affecting the market's expansion.
Restraint:
Inadequate AI workforce
AI is made up of complex algorithms. Businesses need a staff with significant experience and specific skill sets in order to create, operate, and deploy AI systems. Additionally, integrating AI-based solutions into the current systems is a difficult operation that necessitates processing enormous amounts of data to mimic human behaviour. Furthermore, the lack of professional certifications and standards in sophisticated technologies such as AI, ML, and others is limiting the growth of the market.
Opportunity:
Emergence of Quantum Computing
Quantum computing technology is widely adopted by enterprises globally, to solve complex problems, and perform analytical calculations. Quantum computers are enabled with technologies such as artificial intelligence, machine learning, computer vision, big data, AR/VR, and others. It is used in various functions such as fraud detection, risk management, portfolio optimization, and applications where instant data response is required. Thus, the emergence of quantum computing is expected to drive the growth of the market.
Threat:
Data privacy concerns in AI platforms
Access to vast databases containing sensitive and private data is frequently needed for AI platforms. Concerns concerning data security and protection are raised by this. The data used to train AI models may be exposed to unauthorised access, breaches, or misuse if it is not effectively protected. Identity theft, privacy issues, and other types of data abuse may result from this. However, different jurisdictions may have a different data privacy law, which makes it difficult to guarantee compliance and safeguard user privacy.
Covid-19 Impact:
The epidemic has had a negative effect on the market and will likely continue to do so in the years to come. This is linked to the affected production processes, supply chains, and emerging industries' limited adoption of AI. The lockdown requirements caused a number of industrial companies to halt their output, which negatively impacted the supply chain system globally. The deployment of hardware and software based on AI has been delayed as a result of this pandemic. The crisis has been particularly hard on a number of businesses, including the automotive and industrial sectors.
The memory segment is expected to be the largest during the forecast period
The memory segment is expected to be the largest during the forecast period, owing to surge in accumulation of data which requires for predictive analytics, machine learning, and computer vision among others to validate, test and train. Thus, a large amount of data storage memory is required. High bandwidth memory is also being used for applications that are not dependent on the computing architecture. Less start-up are also investigating high bandwidth file systems to improve productivity.
The machine learning segment is expected to have the highest CAGR during the forecast period
The machine learning segment is expected to have the highest CAGR during the forecast period, due to increasing investment in innovative products such as voice recognition, image recognition, and multiple language chat bots among others. Thus, in order to utilise numerous levels of data, these solutions need powerful machine learning.
Region with largest share:
North America is projected to hold the largest market share during the forecast period, owing to a large number of U.S. based tech giants in the market. The region is distinguished by a sizable population with increased purchasing power, ongoing infrastructure investments, and governments putting more emphasis on producing AI applications internally. The market for AI chipsets is presented with a chance due to the rapid development of AI applications.
Region with highest CAGR:
Asia Pacific is projected to hold the highest CAGR over the forecast period, due to the rising investments in Al technology. The use of Al chips has been aided by the manufacturing sector's adoption of cutting-edge and contemporary production techniques. Voice commands are only one of the many features that AI chipsets are increasingly being used for in consumer electronics like laptops, tablets, and smartphones. This has led to a high level of acceptance of AI chipsets in the region.
Key players in the market
Some of the key players in Artificial Intelligence Chipset market include Google Inc., NVIDIA Corporation, Intel Corporation, Graphcore Ltd, Advanced Micro Devices Inc., Samsung Electronics Co. Ltd, Huawei Technologies Co., Xilinx Inc., Baidu Inc., Fujitsu Limited, Micron Technology Inc., Qualcomm Technologies, Inc., Microsoft Corporation, Amazon Web Services, Apple Inc., GreenWaves Technologies, XMOS Limited, General Vision, Inc., Kalray Corporation and MediaTek Inc.
Key Developments:
In April 2023, Google announced the supercomputers it uses to train its AI model are 1.7 times faster than its competition. The company has incorporated the Tensor Processing Unit into the computer, enhancing performance.
In August 2022, Qualcomm Technologies, Inc. announced that its Snapdragon 8+ Gen 1 Platform powered Samsung Electronics Co., Ltd.'s cutting-edge foldable smartphones like the Samsung Galaxy Z Fold4 and Galaxy Z Flip4.
In February 2022, Intel launched XeonR., which is a new dual-track roadmap of Performance-core and Efficient-core based products, moving from two optimized platforms into one common, industry-defining platform.
Functions Covered:
• Inference
• Training
Hardwares Covered:
• Memory
• Network
• Processor
• Other Hardwares
Technologies Covered:
• Natural Language Processing
• Computer Vision
• Predictive Analysis
• Context-Aware Computing
• Machine Learning
• Other Technologies
Processing Types Covered:
• Edge Computing
• Cloud Computing
Applications Covered:
• Automobile
• Smartphones
• Medical Imaging
• Robotics
• Security Systems
• Other Applications
End Users Covered:
• Agriculture
• Cybersecurity
• Marketing
• Fintech
• Automotive
• Human Resources
• Healthcare
• Retail
• Government
• Law
• Manufacturing
• Other End Users
Regions Covered:
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Learn how to effectively navigate the market research process to help guide your organization on the journey to success.
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