The AI chips market is projected to grow 51% from North America, indicating strong regional concentration of AI chip demand.

The global artificial intelligence (AI) chips market size is estimated to grow by USD 389.25 billion from 2024 to 2028, according to Technavio, with the market expanding at a CAGR of over 68.13% during the forecast period. The market encompasses multiple product categories including ASICs, GPUs, CPUs, and FPGAs, serving end-users across media and advertising, BFSI, IT and telecommunication, and other sectors. Major participants in the market include 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., Micron Technology Inc., SK HYNIX INC., Apple Inc., Imagination Technologies, Mythic, Kalray, Blaize, Groq Inc., HAILO TECHNOLOGIES LTD., GreenWaves Technologies, and SiMa Technologies Inc.

North America is estimated to contribute 51% to the growth of the global market and is experiencing significant expansion driven by increasing investments in autonomous vehicle technology. Advanced systems such as ADAS, HUD, LiDAR, and RADAR are being integrated into these vehicles, generating and processing vast amounts of real-time data. In response, chip manufacturers are heavily investing in research and development of AI chips tailored for autonomous vehicles, with major automotive original equipment manufacturers (OEMs) working on commercializing autonomous vehicles, creating lucrative opportunities for AI chip manufacturers.

Artificial Intelligence chips, specifically Application-Specific Integrated Circuits (ASICs), are becoming increasingly popular in data center applications due to their superior performance and speed. ASICs are customized, non-configurable chips that offer an instruction set and libraries for local data processing, acting as an accelerator for parallel algorithms. Google's Tensor Processing Unit (TPU), designed for deep neural networks and already in use for Google Search and Google Street View, exemplifies this application. ASICs provide faster performance than GPUs, FPGAs, and CPUs, and TPUs feature an instruction set that allows TensorFlow programs to be modified and new algorithms to be developed, making them valuable assets for managing data effectively.

The AI chips market is experiencing significant growth due to the increasing adoption of AI technologies across various industries, with deep learning and machine learning algorithms driving demand for these specialized hardware components. AI chips are essential for robotics, quantum computing, and advanced applications, with the market including CPU, FPGA, GPU, System on Chip (SoC), and Multichip Module (MCM) solutions. Applications extend across healthcare, retail, finance, automotive, IoT devices, and more, with healthcare utilizing AI chips for health monitoring, personalized health, and treatment devices, particularly for the elderly population. In retail, AI enables customer behavior analysis, inventory management, and personalized marketing, while in finance it supports fraud detection, risk assessment, and algorithmic trading. Key technologies driving the market include high-bandwidth memory and Trainium2 chips, with companies investing heavily in AI chip development including Nvidia's A100 chip, Ascend 910B chipset, and H200 chipset to meet growing demand for energy-efficient and high-performance AI solutions. The market is evolving with a shift from cloud to edge computing, as ethical concerns surrounding AI continue to fuel the development of specific integrated circuits.