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Artificial Intelligence (Chipsets) Market Value Analysis: What Growth Is Expected Over The Forecast Period?
The artificial intelligence (chipsets) market has experienced rapid expansion over recent years. This market is projected to expand from $31.22 billion in 2025 to $40.96 billion by 2026, exhibiting a compound annual growth rate (CAGR) of 31.2%. Historically, this expansion has been driven by factors such as the proliferation of data-intensive applications, the initial integration of GPUs for AI tasks, the development of cloud computing infrastructure, a surge in enterprise-level AI trials, and improved access to semiconductor manufacturing capabilities.
The artificial intelligence (chipsets) market size is anticipated to undergo significant growth over the next few years. It is expected to expand to $119.62 billion in 2030, demonstrating a compound annual growth rate (CAGR) of 30.7%. This expansion during the forecast period can be attributed to a rise in generative AI workloads, the demand for low latency edge computing, the integration of AI across various industries, substantial investments in advanced semiconductor nodes, and the need for power-optimized AI chips. Prominent trends for the forecast period involve an increasing demand for AI accelerators, the expanding deployment of edge AI chips, a growing adoption of GPUs and ASICs, a focus on energy-efficient AI processing, and the enlargement of AI training and inference hardware.
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#Artificial Intelligence (Chipsets) Market Growth Factors: Which Forces Are Supporting Market Expansion?
The artificial intelligence (chipsets) market is expected to grow due to a surge in data generation. Data generation refers to the process of creating, producing, or generating data in various forms, including text, numbers, images, or any other format that can be stored and processed by computers. AI chipsets play a crucial role in data generation by enabling efficient processing, analysis, and interpretation of information. For instance, in September 2023, according to Demand Sage, a US-based data-driven marketing solution provider, the global volume of generated data was 120 zettabytes as of 2023, with projections indicating an anticipated increase to 181 zettabytes by the conclusion of 2025. Internet users globally contribute to the generation of more than 57% of the total data worldwide. Therefore, the surge in data generation drives the artificial intelligence (chipsets) market.
Artificial Intelligence (Chipsets) Market Segment Breakdown: Which Categories Generate The Most Revenue?
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
Artificial Intelligence (Chipsets) Market Trends Reshaping Industry Growth
Major companies operating in the artificial intelligence (chipsets) market are focusing on developing innovative technologies, such as AI chip configuration. AI chip configuration refers to the specific arrangement and organization of components and features on an artificial intelligence (AI) chip. For instance, in August 2023, Nvidia, a US-based software company, launched ‘GH200’. The latest AI configuration is fine-tuned to efficiently execute AI inference tasks, providing robust support for generative AI applications. The latest version of the Grace Hopper Superchip increases the quantity of high-bandwidth memory, providing the design with the capability to drive more substantial AI models.
Artificial Intelligence (Chipsets) Market Key Players And Strategic Industry Positioning
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 Outlook: Where Are The Largest Opportunities Located?
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.
