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Artificial Intelligence (Chipsets) Market Forecast: What Value Will The Market Reach By 2030?
The artificial intelligence (chipsets) market size has experienced significant expansion in recent years. It is projected to increase from $31.22 billion in 2025 to $40.96 billion in 2026, achieving a compound annual growth rate (CAGR) of 31.2%. The historical market growth can be ascribed to factors such as the rise of data-intensive applications, the early adoption of GPUs for AI workloads, the broadening of cloud computing infrastructure, increased AI experimentation by enterprises, and improved access to semiconductor fabrication.
The artificial intelligence (chipsets) market size is projected to experience substantial expansion over the next few years. It is anticipated to reach $119.62 billion by 2030, demonstrating a compound annual growth rate (CAGR) of 30.7%. This expansion during the forecast period can be primarily attributed to a rise in generative AI workloads, the increasing need for low latency edge computing, widespread AI integration across various industries, significant investments in advanced semiconductor nodes, and the growing requirement for power-optimized AI chips. Furthermore, major developments anticipated in this period include a heightened demand for AI accelerators, the increased deployment of edge AI chips, a surge in the adoption of GPUs and ASICs, a strong emphasis on energy-efficient AI processing, and the broader expansion of hardware for AI training and inference.
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Artificial Intelligence (Chipsets) Market Growth Factors: What’s Supporting Expansion?
The increasing volume of data generation is projected to fuel the expansion of the artificial intelligence (chipsets) market. This process involves the creation and production of data in diverse formats, including text, numbers, or images, all of which are storable and processable by computers. 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 data-driven marketing solution provider, revealed in September 2023 that the global data volume generated reached 120 zettabytes in 2023, with expectations for it to grow to 181 zettabytes by the end of 2025. Worldwide, internet users are responsible for generating over 57% of the total global data. Consequently, the substantial rise in data generation is a key driver for the artificial intelligence (chipsets) market.
Artificial Intelligence (Chipsets) Market Segment Outlook: Which Categories Are Growing Fastest?
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 Transformation Trends: What Innovations Are Driving Change?
Major companies in the artificial intelligence (chipsets) market are concentrating on developing innovative technologies, such as AI chip configuration. AI chip configuration describes the precise arrangement and organization of components and features on an artificial intelligence (AI) chip. For instance, in August 2023, Nvidia, a US-based software company, introduced ‘GH200’. This newest AI configuration is optimized to efficiently perform AI inference tasks, offering strong support for generative AI applications. The updated version of the Grace Hopper Superchip enhances the amount of high-bandwidth memory, allowing the design to power more substantial AI models.
Artificial Intelligence (Chipsets) Market Leading Companies And Competitive Benchmarking
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 Analysis: Which Geography Leads On Revenue?
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.
