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市場調查報告書
商品編碼
1701092
人工智慧 (AI) 晶片組市場規模、佔有率、成長分析(按晶片類型、按技術、按計算技術、按最終用途、按地區)- 2025 年至 2032 年行業預測Artificial Intelligence (AI) Chipsets Market Size, Share, and Growth Analysis, By Chip Type (CPU, GPU), By Technology (Machine Learning, Natural Language Processing), By Computing Technology, By End Use, By Region - Industry Forecast 2025-2032 |
人工智慧 (AI) 晶片組市場規模預計將在 2023 年達到 306 億美元,從 2024 年的 416.5 億美元成長到 2032 年的 4902.8 億美元,預測期內(2025-2032 年)的複合年成長率為 36.1%。
受數據流量快速成長和運算能力需求增加的推動,AI晶片組市場正在經歷顯著成長。自動駕駛汽車技術的普及和人工智慧資料中心並行運算的日益普及,正在推動人工智慧晶片組在各個領域的融合。特別是,這些晶片組對於自動駕駛汽車發展到 5 級能力至關重要。此外,人工智慧正在融入家用電子電器,進一步推動半導體產業的擴張。儘管面臨技能短缺和缺乏標準化等挑戰,亞馬遜和谷歌等大公司仍在推動矽晶圓計劃並採用創新技術。目前的行業分析表明,超過 50% 的美國大型企業正在利用 AI 產品,這表明 AI 晶片組市場正處於良好的發展軌道上,並有望持續成長。
Artificial Intelligence (AI) Chipsets Market size was valued at USD 30.6 billion in 2023 and is poised to grow from USD 41.65 billion in 2024 to USD 490.28 billion by 2032, growing at a CAGR of 36.1% during the forecast period (2025-2032).
The AI chipset market is witnessing significant growth driven by escalating data traffic and the demand for enhanced computing power. The surge in autonomous vehicle technology and the increasing implementation of parallel computing in AI data centers are boosting the integration of AI chipsets across various sectors. Notably, these chipsets are key to advancing autonomous vehicles to Level 5 capability. Additionally, AI is becoming embedded in consumer electronics, fostering further expansion within the semiconductor industry. Despite challenges like skill shortages and a lack of standardization, major players like Amazon and Google are advancing silicon projects and adopting innovative technologies. Current industry analysis shows that over 50% of large U.S. companies leverage AI products, indicating a promising trajectory for the AI chipset market with a sustainable growth forecast.
Top-down and bottom-up approaches were used to estimate and validate the size of the Artificial Intelligence (AI) Chipsets market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Artificial Intelligence (AI) Chipsets Market Segments Analysis
Global Artificial Intelligence (AI) Chipsets Market is segmented by Chip Type, Technology, Computing Technology, End Use and region. Based on Chip Type, the market is segmented into CPU, GPU, FPGA, ASIC and Others. Based on Technology, the market is segmented into Machine Learning, Natural Language Processing, Context-Aware Computing and Computer Vision. Based on Computing Technology, the market is segmented into Cloud AI Computing and Edge AI Computing. Based on End Use, the market is segmented into Healthcare, Manufacturing, Automotive, Retail & E-Commerce, Marketing, Consumer Electronics, BFSI and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Artificial Intelligence (AI) Chipsets Market
The increasing demand for self-driving vehicles is significantly propelling the growth of the Artificial Intelligence (AI) chipsets market. These chipsets are essential for the functioning of autonomous vehicles, as they provide vital processing power, machine learning capabilities, and real-time decision-making, ensuring a safe and efficient self-driving experience. A noteworthy example is Tesla, which, in August 2023, deployed an extensive supercomputing array consisting of approximately 10,000 Nvidia H100 AI processors to accelerate its progress in fully autonomous driving technology. This investment highlights the crucial role that AI chipsets play in advancing the capabilities and safety of self-driving vehicles, thereby driving market expansion.
Restraints in the Artificial Intelligence (AI) Chipsets Market
The Artificial Intelligence (AI) Chipsets market faces significant challenges due to the complexities involved in developing and implementing AI systems. Companies must possess specialized expertise and a highly skilled workforce to effectively create, manage, and utilize these advanced technologies, which encompass areas such as machine learning, cognitive computing, deep learning, machine intelligence, and image recognition. Furthermore, integrating AI solutions into pre-existing systems presents its own difficulties, often requiring substantial in-house research and costly patent filings. Even seemingly minor errors can lead to systemic failures or incorrect problem resolutions, ultimately undermining the expected results and posing a considerable restraint on market growth.
Market Trends of the Artificial Intelligence (AI) Chipsets Market
The artificial intelligence (AI) chipsets market is witnessing a significant trend towards edge AI computing, characterized by the localization of data processing on devices like smartphones, IoT gadgets, and autonomous vehicles. This paradigm shift aims to enhance operational efficiency by reducing latency, bolstering data privacy, and minimizing bandwidth usage. As businesses and industries increasingly prioritize real-time data analysis and instantaneous decision-making, edge AI chipsets are gaining traction across diverse applications, including smart city initiatives, healthcare innovations, and industrial automation. This trend not only reflects the growing demand for smart, responsive technologies but also highlights the pivotal role of AI chipsets in shaping the future of computing.