Artificial Intelligence (AI) Chips Market
Artificial Intelligence Chip (AI ) Market - Size, Segmentation (by Chip Type, by Functionality, by Application, by End-User Industry and by Geography), Competitive Landscape : Global Industry Analysis, Share, Growth, Trends, and Forecast 2023 to 2032
  • ID: RBCT00024
  • March 2024
  • 207 pages

Artificial Intelligence Chip Market Research, 2032

The global artificial intelligence chip market was valued at $15.3 billion in 2022, and is projected to reach $378.5 billion by 2032, growing at a CAGR of 37.8% from 2023 to 2032.

AI chips are tiny slivers of silicon designed to simplify and speed up the development of artificial intelligence systems such as ChatGPT, making them one of the hottest items in technology.

The term AI is used to talk about computing equipment that is specialized to deal with AI workloads. For example, AI chips are used in “training” AI systems to work out difficult problems.

The expansion of the AI Chip market is largely attributed to the increasing demand for autonomous devices, such as robotics and self-driving cars, as well as the proliferation of IoT (Internet of Things) enabled devices. AI chips are designed to enable high-end computing power for these kinds of edge devices. Additionally, important advances in areas such as deep learning have been driving the growth of AI chips.

The rising trend of personalized computing and the increasing demand for healthcare analytics are a few other factors that will contribute to the growth of this market in the future. The growing demand for data centers, which require massive amounts of computing power, is also projected to drive market expansion.


Drivers of the AI Chip Market:

The increasing demand for AI chips is driven by several factors, including the rising investments in machine learning and artificial intelligence (AI) technology from tech companies such as Google, Microsoft, Apple, IBM, and Amazon. Furthermore, the improving computing power of modern-day computers and advancements in cloud technologies are also creating new opportunities for the growth of the AI chip market.

The increasing demand for smart devices such as smartphones, tablets, smart TVs, and wearables is also contributing to the growth of the AI chip market. AI chips are being increasingly integrated into these devices to enhance their performance and capabilities. Additionally, the growing adoption of connected cars is also creating new growth opportunities. AI chips are being used to power autonomous driving features and other advanced technologies in these cars.

Challenges Faced by the AI Chip Market:

The AI chip market faces some significant challenges that are hindering its further growth. Some of these include:

  • Lack of standardization across the industry. With the rapidly evolving technology, it is difficult for developers and manufacturers to keep up with the latest developments in AI chip design and architecture. This leads to performance variations between different suppliers and their respective chips.
  • Limited availability of suitable software for the AI chip market. Due to the complexity of developing applications designed to run on AI chips, there are only a limited number of suitable software solutions available that can handle the more advanced operations.
  • High costs associated with creating custom AI chip solutions. To meet specific customer requirements, organizations often have to spend significant amounts of money creating custom AI chipsets. This can be a prohibitively expensive process for many companies.

Despite these challenges, the AI chip market is still growing at an impressive rate and is poised to expand significantly shortly. With more companies investing in this technology and with improvements being made in terms of performance and cost, the AI chip market is expected to gain considerable traction in the coming years. This will lead to increased adoption and use cases across industries, allowing for greater technological advancements.

Opportunities for Growth in the AI Chip Market:

The AI chip market is expected to grow significantly in the coming years due to a variety of factors, including the rise of data-driven businesses and increased demand for intelligent applications. The rapid growth of digitization and automation has increased the need for improved computing power and efficiency. This has led to an increase in the implementation of AI chips across various industries, including automotive, healthcare, finance, and retail.

The increasing adoption of AI chips across various applications has resulted in the development of more powerful and efficient architectures that are capable of performing complex tasks faster than ever before. This is further fuelling the demand for AI chips from multiple sectors. Additionally, several countries have implemented initiatives such as ‘Startup India’ and ‘Digital India’, which are encouraging the development of AI chips in the country. This is expected to provide further impetus to the expansion of this market shortly.

AI chip providers are also focusing on developing intelligent chips that can be used for machine learning applications. These new-age technologies are expected to help improve the performance of AI chips by providing enhanced computing power and increased efficiency. Furthermore, major players are also actively investing in research and development activities to develop innovative products that can offer better performance when compared to traditional chips. This is likely to create significant opportunities for growth in the AI chip market in the coming years.




Market size value in 2022

USD 15.32 Billion

Market size value in 2032

USD 378.5 Billion

CAGR (2023 to 2032)


Historical data


Base Year





Asia Pacific, Europe, South America, North America, and Middle East & Africa. Regions are further analyzed at the country level.


Chip Type,  Functionality,  Application, End-User Industry and Geography

Table of Contents


  • Market Overview
  • Drivers of the AI Chip Market
  • Challenges Faced by the AI Chip Market
  • Opportunities for Growth in the AI Chip Market
  • Conclusion

The artificial intelligence (AI) chip market can be segmented based on various factors. Here are some common segmentation criteria:

  1. Chip Type: a. Central Processing Unit (CPU) chips: These chips are designed for general-purpose computing tasks and are often used in AI applications that require high-speed processing. b. Graphics Processing Unit (GPU) chips: GPUs are specialized chips known for their parallel processing capabilities, making them suitable for AI tasks such as deep learning and image processing. c. Field-Programmable Gate Array (FPGA) chips: FPGAs offer flexibility and programmability, allowing users to customize the chip's functionality for specific AI applications. d. Application-Specific Integrated Circuit (ASIC) chips: ASICs are designed specifically for AI tasks and offer high performance and energy efficiency for specialized AI workloads.
  2. Functionality: a. Training chips: These chips are optimized for AI model training, which involves processing large datasets and complex calculations. b. Inference chips: Inference chips are designed for running trained AI models in real-time, delivering fast and efficient predictions or decisions.
  3. Application: a. Data centers: AI chips for data centers are optimized for high-performance computing and large-scale AI workloads in cloud environments. b. Edge devices: AI chips for edge devices, such as smartphones, smart cameras, and IoT devices, are typically designed for low power consumption and real-time processing at the edge of the network.
  4. End-User Industry: a. Healthcare: AI chips used in healthcare applications, such as medical imaging, drug discovery, and patient monitoring systems. b. Automotive: AI chips for autonomous vehicles, driver-assistance systems, and connected car applications. c. Retail: AI chips used in retail applications for inventory management, personalized marketing, and customer analytics. d. Manufacturing: AI chips for industrial automation, predictive maintenance, and quality control in manufacturing processes. e. Financial Services: AI chips used in banking, insurance, and financial applications for fraud detection, risk assessment, and algorithmic trading.
  5. Geography: The AI chip market can be segmented based on geographical regions, such as North America, Europe, Asia-Pacific, and the rest of the world, considering regional preferences, market size, and adoption of AI technologies.

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