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Hardware Artificial Intelligence Market Expected To Reach $27.1 Billion By 2030 At 21.6% CAGR
The hardware artificial intelligence market size has witnessed significant expansion in recent years. It is projected to increase from $10.2 billion in 2025 to $12.39 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 21.5%. This historical growth can be ascribed to elements such as the early adoption of GPUs for AI tasks, a surge in data center compute demand, the rising utilization of machine learning models, the development of cloud computing infrastructure, and the enhancement of semiconductor manufacturing capabilities.
The hardware artificial intelligence market is projected to experience substantial growth over the next few years. It is anticipated to reach $27.1 billion by 2030, demonstrating a compound annual growth rate (CAGR) of 21.6%. This expansion during the forecast period is driven by the increasing deployment of edge devices, a growing need for low-latency AI processing, the advancement of autonomous systems, an escalating demand for scalable AI infrastructure, and ongoing improvements in neural network processor design. Noteworthy trends for this duration include the rising requirement for high-performance AI accelerators, the increasing adoption of edge AI hardware solutions, a heightened demand for energy-efficient AI chips, the expansion of AI data centers and high-speed compute infrastructure, and the broader use of specialized hardware for deep learning training and inference.
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Hardware Artificial Intelligence Market Opportunity Drivers: What Is Creating New Revenue Potential?
The expanding global base of internet users is projected to fuel the growth of the hardware artificial intelligence market. Internet consumers utilize online platforms for information, communication, and various activities, with increasing global interconnectedness driving greater reliance on the internet for cross-border interactions and commerce, particularly evident in emerging markets. Hardware AI plays a crucial role by enhancing user experiences through faster data processing and facilitating wider internet access via advanced devices such as smartphones, smart speakers, and IoT devices. This trend is supported by data from the International Telecommunication Union (ITU), a Switzerland-based specialized agency, which indicated that global internet usage increased from 66% (approximately 5.3 billion people) in 2022 to about 67% (around 5.4 billion people) in 2023. Consequently, the rising number of internet consumers worldwide is a key driver for the hardware artificial intelligence market’s expansion.
Hardware Artificial Intelligence Market Segment Performance And Strategic Opportunities
The hardware artificial intelligence market covered in this report is segmented –
1) By Hardware Function: Processor, Network, Storage
2) By Product: Central Processing Unit (CPU), Graphics Processing Unit (GPU), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), Memory, Modules
3) By Technology: Machine Learning, Computer Vision, Other Technologies
4) By End Use Industry: Banking, Financial Services And Insurance (BFSI), Information Technology (IT) And Telecommunication, Healthcare, Media And Entertainment, Aerospace And Defense, Manufacturing, Automotive, Agriculture, Retail, Other End Users
Subsegments:
1) By Processor: Graphics Processing Unit (GPU), Central Processing Unit (CPU), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), Neural Network Processor (NPU)
2) By Network: AI-Optimized Network Infrastructure, Switches Or Routers, Data Center Networks, Network Interface Cards (NICs)
3) By Storage: Solid-State Drives (SSD), Hard Disk Drives (HDD), Cloud Storage Solutions, Data Storage Systems For AI Workloads, High-Performance Storage Systems
Hardware Artificial Intelligence Market Trends Driving Strategic Industry Expansion
Leading companies within the hardware artificial intelligence market are actively developing sophisticated products, such as new AI chips, to meet the increasing demand for specialized hardware optimized for AI workloads. This specialized computing hardware is essential for creating and deploying artificial intelligence systems, specifically engineered to manage the unique and complex computational requirements of AI algorithms with speed and efficiency. For example, in December 2023, Advanced Micro Devices, Inc., a US-based IT corporation, unveiled two new AI chips: the Instinct MI300X accelerator and the Instinct M1300A accelerated processing unit (APU). These are designed to train and run large language models (LLMs) and offer enhanced energy efficiency compared to their predecessors. The MI300X offers 1.5 times more memory capacity than the previous M1250X version and competes with Nvidia’s H100 chips for training LLMs, yet it demonstrates superior performance in inference tasks. Both chips are intended to fuel innovations in generative AI and are crafted to efficiently handle the complex computational needs of AI algorithms.
Hardware Artificial Intelligence Market Key Players: Which Companies Shape Industry Competition?
Major companies operating in the hardware artificial intelligence market are Google Plc, Samsung Electronics Co. Ltd., Microsoft Corporation, Dell Technologies Inc., Bosch GmbH, Huawei Technologies Co. Ltd., Intel Corporation, International Business Machines Corporation, Xilinx Inc., Oracle Corporation, Honeywell International Inc., Micron Technology, NVIDIA Corporation, Hewlett Packard Enterprise, Toyota Industries Corporation, Safran S.A., Thales Group, Leidos Holdings Inc., Rockwell Automation Inc., The Smiths Group plc, Arm Limited, Axis Communication AB, Inspur Information Technology Co. Ltd., OSI Systems Inc., Graphcore Limited
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Hardware Artificial Intelligence Market Geographic Distribution And Regional Opportunities
North America was the largest region in the hardware artificial intelligence market in 2025. The regions covered in the hardware artificial intelligence market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.