Authored By: Sarah
27 Jun 2024

 Artificial Intelligence (Ai) Chips Market Size to grow by USD 389251.3 million between 2024-2028

According to a research report “ Artificial Intelligence (Ai) Chips Market” by Product (ASICs, GPUs, CPUs, FPGAs) End-user (Media and advertising, BFSI, IT and telecommunication, Others) Geography (North America, Europe, APAC, South America, Middle East and Africa)- Global Forecast to 2028 published by Technavio, the market size is estimated to grow by USD 389251.3 million, at a CAGR of over 68.13% during the forecast period. In today's digital economy, businesses heavily rely on data centers to operate their online services, which consist of numerous servers, each powered by a Central Processing Unit (CPU). However, with the increasing adoption of Artificial Intelligence (AI), particularly deep neural networks, there is a growing need for more powerful processors. Neural networks require significant computational resources to analyze vast datasets, surpassing the capabilities of CPUs. To enhance data center efficiency and reduce power consumption, companies are integrating Application-Specific Integrated Circuits (ASICs) and Graphics Processing Units (GPUs) designed specifically for AI applications. By improving power efficiency and reducing operational costs, businesses can ensure optimal uptime and maintain a competitive edge in their respective industries.

Browse market data tables, figures, and in-depth TOC on “Artificial Intelligence (Ai) Chips Market” by Product (ASICs, GPUs, CPUs, FPGAs) End-user (Media and advertising, BFSI, IT and telecommunication, Others) Geography (North America, Europe, APAC, South America, Middle East and Africa) Global Forecast to 2028. Download Free Sample


By Product, the ASICs segment is projected to dominate the market size in 2024

The media and advertising sector represents the largest end-user segment in the Artificial Intelligence (AI) Chips Market. This trend is driven by the escalating investments and technological advancements in media and advertising industries worldwide. The media and advertising industry's growing fascination with AI technologies is noteworthy, as these applications are still in their nascent stages. Despite this, the potential for AI to revolutionize media and advertising is significant. In recent times, media and advertising industries have shown a burgeoning interest in AI technologies, with the potential to shape the future of this sector.

By End-user, Media and advertising  segment is expected to hold the largest market size for the year 2024

In the burgeoning market for Artificial Intelligence (AI) chips, Application-Specific Integrated Circuits (ASICs) are emerging as a preferred choice for cloud-based data centers. ASICs are highly specialized, non-configurable chips that offer faster performance than GPUs and FPGAs through their customized instruction sets and locally stored data processing capabilities. While they are not reconfigurable, their fixed function provides unparalleled efficiency for parallel algorithms, making them an indispensable accelerator in AI applications. The adoption of ASIC-based AI chips is on the rise, as they outperform GPUs, FPGAs, and CPUs in data center applications, thereby driving market growth.

North America is forecasted to hold the largest market size by region in 2024

The Artificial Intelligence (AI) chip market is experiencing significant growth due to the increasing demand for advanced computing solutions to power AI applications. These specialized chips are designed to accelerate machine learning and deep learning algorithms, enabling businesses to enhance their operational efficiency and gain a competitive edge. Major tech companies and startups are investing heavily in R&D to bring innovative AI chip solutions to market, driving market expansion.

The Artificial Intelligence (Ai) Chips Market growth and forecasting report also includes detailed analyses of the competitive landscape of the market growth and forecasting and information about 20 market companies, including:

  • Advanced Micro Devices Inc.
  • Alphabet Inc.
  • Baidu Inc.
  • Broadcom Inc.
  • Cerebras
  • Fujitsu Ltd.
  • Graphcore Ltd.
  • Huawei Technologies Co. Ltd.
  • Intel Corp.
  • International Business Machines Corp.
  • MediaTek Inc.
  • Microchip Technology Inc.
  • NVIDIA Corp.
  • NXP Semiconductors NV
  • Qualcomm Inc.
  • SambaNova Systems Inc.
  • Samsung Electronics Co. Ltd.
  • SenseTime Group Inc.
  • Taiwan Semiconductor Manufacturing Co. Ltd.
  • Tesla Inc.

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Research Analysis Overview

Artificial Intelligence (AI) is revolutionizing various industries, from autonomous vehicles to finance and healthcare. The demand for AI technologies is driving the growth of the AI chips market, which includes System on Chips (SoCs), Multichip Modules (MCMs), GPUs, FPGAs, CPUs, and specific integrated circuits. These hardware components power AI algorithms, machine learning, and deep learning applications. Edge AI and cloud AI are two primary deployment models. Edge AI, which runs AI algorithms locally on devices like IoT devices and autonomous vehicles, requires high-performance, low-power chips. Cloud AI, which processes data in data centers using supercomputers, demands high-performance chips with high bandwidth memory, such as the Trainium2 chip. Ethical concerns surrounding AI are also driving the development of new AI chips. Advanced Micro Devices (AMD) and other companies are exploring AI chips for quantum computing and generative AI. AI chips are also essential for robotics and other hardware applications. The AI chips market is expected to grow significantly in the coming years, with applications in automotive, retail, finance, healthcare, and more. Key players in the AI chips market include NVIDIA, Intel, AMD, Qualcomm, and Xilinx. They are investing heavily in research and development to create more powerful and efficient AI chips to meet the growing demand for AI technologies.

Market Research Overview

Artificial Intelligence (AI) is revolutionizing various industries by enabling machines to perform tasks that typically require human intelligence. The backbone of AI systems are chips specifically designed to handle the complex computations involved in areas like visual understanding and machine intelligence. These chips are often compared to the "brains" of the system, processing the "sequence of images" or "single image" data with an "algorithmic basis" or "theoretical basis" for "visual understanding." Different types of chips are used for specific AI applications. For instance, gaming consoles and personal computers use GPUs (Graphics Processing Units) for rendering high-quality images and handling graphic applications. Embedded systems, mobile phones, and IoT devices utilize CPUs (Central Processing Units), DSPs (Digital Signal Processors), ASICs (Application-Specific Integrated Circuits), FPGAs (Field-Programmable Gate Arrays), and other processors for automatic analysis of structured data and behavioral patterns. AI chips are also essential for computer vision applications, including pose detection, object recognition, and image recognition, which are crucial for industries like finance, retail, healthcare, automotive, and robotics. Ethical concerns regarding AI technologies, such as privacy and security, have led to the development of edge computing and AI data centers for real-time data processing and reducing latency. Major tech companies like Oracle Cloud Infrastructure, Google Cloud, Amazon Web Services, and Microsoft Azure have entered the AI chip market with their offerings, such as the H200 chipset, Ascend 910B chipset, and Nvidia's A100 chip. These chips are designed to be energy-efficient and offer high computing power for AI applications. Moreover, AI chips are also being used in advanced fields like quantum computing, generative AI, and cognitive computing, expanding the scope of AI applications in various industries. The future of AI chips holds great potential, with advancements in hardware components, AI algorithms, and ethical considerations driving innovation in this rapidly evolving market.


Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200

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