Artificial Intelligence (AI) Chip Market (By Technology: Machine learning, Natural language processing, Context-Aware Computing, Computer Vision, Predictive Analysis; By Chip Type: GPU, ASIA, FPGA, CPU, Others; By Processing Type: Edge, Cloud ; By Function: Training, Inference; By End-Users: Manufacturing, Healthcare, Automotive, Agriculture, Retail, Human Resources, Marketing, BFSI, Government, Others) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032

The global artificial intelligence (AI) chip market size was exhibited at USD 16.88 billion in 2022 and is projected to hit around USD 227.55 billion by 2032, growing at a CAGR of 29.73% during the forecast period 2023 to 2032.

Key Pointers:

• By Geographically, North America region dominates the global market.
• By technology, the machine learning segment dominates the global market. 
• By chip type, the CPU segment is the leading the global market. 
• By processing type, the edge segment accounted more than 75% of revenue share in 2022. 
• By function, the inference segment is growing at a significant rate. 
• By end-users, the BFSI segment holds the maximum revenue share and is predicted to maintain growth from 2023 to 2032.

Artificial Intelligence (AI) Chip Market Report Scope

According to Himanshu Jangra Lead Analyst, Semiconductor and Electronics, at Allied Market Research, the Artificial intelligence chip Market is expected to showcase remarkable growth during the forecast period of 2023-2032. The report contains a thorough examination of the market size, Artificial intelligence chip market trends, key market players, sales analysis, major driving factors, and key investment pockets. The report on the global artificial intelligence chip market provides an overview of the market as well as market definition and scope. The ongoing technological advancements and surge in demand for artificial intelligence processors and artificial intelligence brain chip solutions have an impact on market growth. Furthermore, the report provides a quantitative and qualitative analysis of the artificial intelligence chip market opportunity, as well as a breakdown of the pain points, value chain analysis, and key regulations.  

Artificial intelligence (AI) chips are specialized silicon chips, which incorporate AI technology and are used for machine learning. AI helps in eliminating or minimizing the risk to human life in many industry verticals. The need for more efficient systems for solving mathematical and computational problems has become crucial, as the volume of data has increased. Thus, the majority of the key players in the IT industry focus on developing AI chips and applications.

Artificial Intelligence (chipsets) market dynamics

Driver: The emerging trend of autonomous vehicles

Autonomous vehicles rely on a combination of sensors, cameras, radar, lidar, and other technologies to perceive their surroundings accurately. AI (chipsets) plays a crucial role in processing the vast amount of real-time data generated by these sensors. The chipsets accelerate perception tasks such as object detection, tracking, and classification, allowing the vehicle to make informed decisions based on the analyzed data. The need for powerful AI (chipsets) capable of handling complex perception tasks is essential to enable safe and efficient autonomous driving.

Autonomous vehicles employ sophisticated AI algorithms for mapping, path planning, and decision-making tasks. These algorithms require substantial computational power and efficient processing to handle driving lessons' complexity and real-time nature. AI (chipsets) is designed to deliver the high-performance computing needed to execute these complex algorithms efficiently, ensuring the smooth operation of autonomous vehicles.

Restraint: Lack of AI hardware experts and skilled workforce

Developing AI (chipsets) requires specialized knowledge and expertise in hardware design, architecture, and optimization for AI workloads. However, there is a need for more AI hardware experts who possess the necessary skills and experience to design and develop these chipsets. This expertise scarcity can slow the pace of innovation and product development in the AI (chipsets) market.

AI (chipsets) often incorporates specialized accelerators and custom architectures tailored for AI workloads. Designing and optimizing these components requires technical skills and knowledge that may be limited in the existing talent pool. The need for more skilled workers who can handle these specialized tasks can restrict the growth and development of AI (chipsets).

Opportunity: Surging demand for AI-based FPGA

FPGAs offer inherent flexibility and programmability compared to fixed-function ASICs (Application-Specific Integrated Circuits). This makes them suitable for handling diverse AI workloads and adapting to evolving AI algorithms. As AI models and algorithms continue to grow rapidly, the ability to reprogram and reconfigure FPGAs provides a competitive advantage in meeting the changing demands of AI applications.

Energy efficiency is critical in AI (chipsets), particularly in edge computing and IoT devices where power constraints exist. FPGAs can be power-optimized to deliver high performance per watt by leveraging parallel processing capabilities and fine-grained control over resources. The ability to optimize power consumption while maintaining performance is crucial for AI (chipsets), making AI-based FPGAs an attractive choice.

Challenge: Data privacy concerns in AI platforms

AI platforms often require access to large datasets, including personal and sensitive information. This raises concerns about data security and protection. If the data used for training AI models is not adequately safeguarded, it can be vulnerable to unauthorized access, breaches, or misuse. This can lead to privacy violations, identity theft, or other forms of data abuse.

AI platforms often involve the sharing of data across organizations or even international borders. However, data privacy regulations can vary across jurisdictions, making it challenging to ensure compliance and protect user privacy. Adhering to diverse legal frameworks while enabling data sharing and collaboration poses a significant challenge for AI (chipsets) companies.

Some of the prominent players in the Artificial Intelligence (AI) Chip Market include:

• NVIDIA Corporation
• General Vision Inc.
• Amazon Web Services
• Google Inc.
• Microsoft Corporation
• Advanced Micro Devices Inc. 

Segments Covered in the Report

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2032. For this study, Nova one advisor, Inc. has segmented the global Artificial Intelligence (AI) Chip market.

By Technology

• Machine learning
• Natural language processing
• Context-aware computing
• Computer vision
• Predictive analysis

By Chip Type

• GPU
• ASIA
• FPGA
• CPU
• Others

By Processing Type

• Edge
• Cloud

By Function

• Training
• Inference

By End-Users

• Manufacturing
• Healthcare
• Automotive
• Agriculture
• Retail
• Human Resources
• Marketing
• BFSI
• Government
• Others

By Region

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa (MEA)