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What Is The Artificial Intelligence (Chipsets) Market Size In 2026, And Where Is It Heading By 2030?
The market size for artificial intelligence (chipsets) has observed exponential growth in recent years. It is projected to increase from $31.22 billion in 2025 to $40.96 billion in 2026, at a compound annual growth rate (CAGR) of 31.2%. This historical expansion can be attributed to several factors, including the proliferation of data-intensive applications, the early adoption of GPUs for AI workloads, the development of cloud computing infrastructure, a rise in enterprise AI experimentation, and enhanced availability of semiconductor fabrication.
The artificial intelligence (chipsets) market size is anticipated to experience substantial growth over the next few years. It is forecast to reach $119.62 billion in 2030, demonstrating a compound annual growth rate (CAGR) of 30.7%. This expansion during the projection period can be attributed to a surge in generative AI workloads, the necessity for low latency edge computing, the integration of AI across various industries, investments in advanced semiconductor nodes, and the requirement for power optimized AI chips. Significant trends expected in the forecast period include an escalating demand for AI accelerators, the increased deployment of edge AI chips, a growing adoption of GPUs and ASICs, a focus on energy efficient AI processing, and the broader expansion of AI training and inference hardware.
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Artificial Intelligence (Chipsets) Market Growth Drivers And Their Impact On Future Demand
The future expansion of the artificial intelligence (chipsets) market is anticipated to be driven by the increasing volume of data generation. Data generation encompasses the creation or production of information in diverse formats, including text, numerical values, and images, all of which are suitable for computer storage and processing. Artificial intelligence chipsets are vital for data generation, facilitating the effective processing, analysis, and understanding of information. For example, data from Demand Sage, a US-based provider of data-driven marketing solutions, revealed in September 2023 that the worldwide data volume reached 120 zettabytes in 2023, with forecasts predicting a rise to 181 zettabytes by the end of 2025. Globally, internet users are responsible for creating over 57% of the total data generated across the world. Consequently, this increase in data generation fuels the artificial intelligence (chipsets) market.
What Categories Define The Artificial Intelligence (Chipsets) Market?
The artificial intelligence (chipsets) market covered in this report is segmented –
1) By Hardware: Processor, Memory, Network
2) By Technology: Machine Learning, Natural Language Processing, Context-Aware Computing, Computer Vision, Predictive Analysis
3) By Function: Training, Inference
4) By Computing Technology: Cloud AI Computing, Edge AI Computing
5) By Industry Vertical: Consumer Electronics, Media And Advertising, Banking, Financial Services And Insurance (BFSI), Information Technology (IT) And Telecom, Retail, Healthcare, Automotive, Other Industry Verticals
Subsegments:
1) By Processor: Central Processing Units (CPUs), Graphics Processing Units (GPUs), Application-Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), Digital Signal Processors (DSPs)
2) By Memory: Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Non-Volatile Memory (NVM), Flash Memory
3) By Network: Network Interface Cards (NICs), Network Processors, Switches And Routers
What New Developments Are Emerging In The Artificial Intelligence (Chipsets) Market?
Leading companies in the artificial intelligence (chipsets) market are concentrating on creating innovative technologies, including AI chip configuration. AI chip configuration describes the specific arrangement and structure of components and features on an artificial intelligence (AI) chip. For example, in August 2023, Nvidia, a US-based software company, unveiled ‘GH200’. This most recent AI configuration is optimized to effectively perform AI inference tasks, offering strong support for generative AI applications. The newest version of the Grace Hopper Superchip boosts the amount of high-bandwidth memory, giving the design the ability to run more substantial AI models.
Major Players Driving Competition In The Artificial Intelligence (Chipsets) Market
Major companies operating in the artificial intelligence (chipsets) market are Apple Inc.; Alphabet Inc.; Samsung Electronics Co. Ltd.; Huawei Technologies Co. Ltd.; Intel Corporation; International Business Machines Corporation; Qualcomm Technologies Inc.; Micron Technology Inc.; NVIDIA Corporation; AMD; MediaTek Inc.; Baidu Inc.; Xilinx Inc.; Ampere Computing LLC; Cambricon Technologies Corporation; Horizon Robotics Inc.; VeriSilicon Holdings Co.; Cerebras Systems Inc.; Hailo; Graphcore Limited; SambaNova Systems Inc.; Mythic Inc.; Wave Computing Inc.; Esperanto Technologies Inc.; CogniTensor Inc.; Syntiant Corporation; Tenstorrent Inc.; BrainChip Holdings Ltd.
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Artificial Intelligence (Chipsets) Market Regional Leaders: Insights From The 2026 Report
North America was the largest region in the artificial intelligence (chipsets) market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (chipsets) 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.
