市场调查报告书
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1470611
人工智慧基础设施市场:按产品、部署和最终用户划分 - 全球预测,2024-2030 年AI Infrastructure Market by Offering (Hardware, Services, Software), Deployment (On-Cloud, On-Premise), End-Users - Global Forecast 2024-2030 |
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人工智慧基础设施市场规模预估2023年为365.2亿美元,2024年达451.1亿美元,预计2030年将达到1,654亿美元,复合年增长率为24.08%。
人工智慧基础设施市场是指支援各种最终用途产业的人工智慧(AI)应用和机器学习(ML)模型的部署、扩展和管理的硬体、软体和服务生态系统。 AI 基础设施包括 GPU、TPU 和 ASIC 等专用处理器、记忆体和储存解决方案、网路设备、模型训练软体平台以及加速 AI 采用的咨询服务。处理大型资料集的高效能运算平台的需求不断增长,以及全球边缘到云端人工智慧基础设施的兴起,正在推动对人工智慧基础设施解决方案的需求。此外,政府推动智慧製造和工业 4.0 设施的倡议也促进了市场成长。然而,设计复杂性、部署和维护问题可能会限制人工智慧基础架构解决方案的采用。网路攻击和资料外洩事件的脆弱性给市场带来了挑战。此外,技术进步以及人工智慧基础设施与5G技术的整合预计将推动超低延迟和高频宽应用的新时代,为市场创造新的机会。
主要市场统计 | |
---|---|
基准年[2023] | 365.2亿美元 |
预测年份 [2024] | 451.1亿美元 |
预测年份 [2030] | 1,654亿美元 |
复合年增长率(%) | 24.08% |
满足人工智慧生态系统特定需求的创新解决方案与服务
专用处理器和快速、可扩展的储存解决方案等人工智慧硬体对于人工智慧模型的高效训练和推理效能至关重要。基于 CPU 和 GPU 的系统是具有严格运算要求的组织的首选,因为它们的平行处理能力可以减少机器学习模型的训练时间。 AI基础设施服务包括实施AI解决方案、确保可维护性和扩充性的咨询支持,以及用于效能监控的模型管理服务。实施由基于云端基础的基础设施支援的学习模型,以最大限度地提高资源利用率。资料标记和註释服务对于监督学习演算法维护隐私和安全标准至关重要。提供框架、资料准备工具、模型部署平台等多种软体工具,用于设计、开发和部署人工智慧解决方案,为复杂操作提供高层介面。
部署:扩大云端基础的人工智慧基础设施的使用,重点关注人工智慧服务的敏捷性和快速部署
云端基础的人工智慧基础架构是一种弹性且扩充性的解决方案,可让企业利用先进的人工智慧功能,而无需在硬体或维护方面进行大量投资。混合人工智慧基础设施结合了云端和本地的优点,使企业能够保持对敏感资料的控制,同时根据特定要求优化部署。当您需要最大限度地控制人工智慧基础架构或有严格的安全要求时,本地部署优于云端基础的解决方案。
最终用户:人工智慧基础设施越来越多地部署在企业和政府机构。
云端服务供应商(CSP) 提供无缝、可扩展的 AI 基础设施,为具有不同处理和储存需求的广泛客户提供服务。各行各业的公司都在利用人工智慧基础设施来实现资料分析、自动化以及透过聊天机器人和虚拟助理改善客户服务等目的,并选择正确的人工智慧基础设施解决方案。政府机构正在利用人工智慧基础设施进行各种应用,包括公共、医疗保健系统管理和交通管理,以提高安全性和合规性、成本效益和互通性。
区域洞察
美洲拥有高度发展的基础设施,与人工智慧研发相关的投资显着成长,并且存在重要的全球市场参与者。美国、加拿大和墨西哥是主要国家,不断增长的消费者需求正在推动人工智慧基础设施解决方案的采用。在欧盟(EU),法国和德国等国家处于加大研发投资以开发人工智慧技术的最前线。政府措施和政策在推动亚太地区各产业采用人工智慧方面发挥着至关重要的作用。中国、日本和印度等国家的政府已经认识到人工智慧对未来经济成长的重要性,并正在大力投资研发(R&D)计画以促进创新。此外,蓬勃发展的新兴企业生态系统也对市场成长做出了重大贡献。
FPNV定位矩阵
FPNV定位矩阵对于评估AI基础设施市场至关重要。我们检视与业务策略和产品满意度相关的关键指标,以对供应商进行全面评估。这种深入的分析使用户能够根据自己的要求做出明智的决策。根据评估,供应商被分为四个成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市场占有率分析
市场占有率分析是一个综合工具,可以对人工智慧基础设施市场供应商的现状进行深入而深入的研究。全面比较和分析供应商在整体收益、基本客群和其他关键指标方面的贡献,以便更好地了解公司的绩效及其在争夺市场占有率时面临的挑战。此外,该分析还提供了对该行业竞争特征的宝贵见解,包括在研究基准年观察到的累积、分散主导地位和合併特征等因素。详细程度的提高使供应商能够做出更明智的决策并制定有效的策略,从而在市场上获得竞争优势。
1. 市场渗透率:提供有关主要企业所服务的市场的全面资讯。
2. 市场开拓:我们深入研究利润丰厚的新兴市场,并分析其在成熟细分市场的渗透率。
3. 市场多元化:提供有关新产品发布、开拓地区、最新发展和投资的详细资讯。
4.竞争评估与资讯:对主要企业的市场占有率、策略、产品、认证、监管状况、专利状况、製造能力等进行全面评估。
5. 产品开发与创新:提供对未来技术、研发活动和突破性产品开发的见解。
1.AI基础设施市场的市场规模和预测是多少?
2.人工智慧基础设施市场预测期间有哪些产品、细分市场、应用程式和领域需要考虑投资?
3.AI基础设施市场的技术趋势和法规结构是什么?
4.AI基础设施市场主要厂商的市场占有率为何?
5.进入AI基础设施市场的合适形式和策略手段是什么?
[199 Pages Report] The AI Infrastructure Market size was estimated at USD 36.52 billion in 2023 and expected to reach USD 45.11 billion in 2024, at a CAGR 24.08% to reach USD 165.40 billion by 2030.
The AI infrastructure market refers to the ecosystem of hardware, software, and services that support the deployment, scaling, and management of artificial intelligence (AI) applications and machine learning (ML) models for various end-use industries. The AI infrastructure includes specialized processors such as GPUs, TPUs, ASICs, memory and storage solutions, networking equipment, software platforms for model training, and consulting services to facilitate AI adoption. The increasing need for high-performance computing platforms to process large datasets and the rising edge-to-cloud AI infrastructure worldwide are surging the demand for AI Infrastructure solutions. Additionally, the government initiatives promoting smart manufacturing and Industry 4.0 facilities contribute to market growth. However, the design complexities, deployment, and maintenance issues may limit the adoption of AI infrastructure solutions. The vulnerability to cyberattacks and data breach incidents poses challenges to the market. Moreover, the technological advancements and integration of AI infrastructure with 5G technology is expected to facilitate a new era of ultra-low latency and high-bandwidth applications, opening up additional opportunities for the market.
KEY MARKET STATISTICS | |
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Base Year [2023] | USD 36.52 billion |
Estimated Year [2024] | USD 45.11 billion |
Forecast Year [2030] | USD 165.40 billion |
CAGR (%) | 24.08% |
Offering: Innovative solution and services catering to specific needs of the AI ecosystem
The AI hardware, such as specialized processors and high-speed & scalable storage solutions, are crucial for efficient AI model training and inference performance. Organizations with demanding computational requirements prefer CPU & GPU-based systems due to their parallel processing capabilities that provide shorter training times for machine learning models. Services in AI infrastructure include consulting support on deploying AI solutions, ensuring maintainability & scalability model management services for monitoring performance. The training models using cloud-based infrastructures are implemented to maximize resource utilization. Data labeling & annotation services are essential for supervised learning algorithms to maintain privacy & security standards. A diverse range of software tools, such as frameworks, data preparation tools, and model deployment platforms, are available for designing, developing, and deploying AI solutions to provide a high-level interface for complex operations.
Deployment: Increasing utilization of the cloud-based AI infrastructure focusing on the agility and swift deployment of AI-powered services
Cloud-based AI infrastructure offers a flexible and scalable solution that allows organizations to access advanced AI capabilities without the need for large-scale investments in hardware and maintenance. Hybrid AI infrastructure combines the advantages of cloud and on-premise solutions, enabling organizations to optimize their deployments based on specific requirements while maintaining control over sensitive data. On-premise deployment is preferred over cloud-based solutions when organizations require maximum control over their AI infrastructure or have stringent security requirements.
End-Users: Rising deployment of the AI infrastructure into the enterprises and Government entities
Cloud Service Providers (CSPs) provide seamless and scalable AI infrastructures as they cater to a wide range of clients with varying demands for processing power and storage capabilities. Enterprises across various industries leverage AI infrastructure for purposes such as data analytics, automation, and customer service improvement through chatbots and virtual assistants to select a suitable AI infrastructure solution. Government entities utilize AI infrastructure for various applications such as public safety, healthcare systems management, and traffic management, among others, for enhanced security & compliance, cost-effectiveness, and interoperability.
Regional Insights
The Americas represent a highly developed infrastructure with significant growth in investments associated with AI research and development and the presence of significant global market players. The United States, Canada, and Mexico are major countries with rising consumer demands, boosting the adoption of AI infrastructure solutions. In the European Union, countries such as France and Germany are spearheading efforts to increase investments in research and development to develop AI technology. Government initiatives and policies play an essential role in driving AI adoption across various industries in the Asia-Pacific region. Governments in countries including China, Japan, and India have recognized the importance of AI for future economic growth and are heavily investing in research and development (R&D) programs to boost innovation. Additionally, the thriving startup ecosystem contributes significantly to the market growth.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the AI Infrastructure Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the AI Infrastructure Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the AI Infrastructure Market, highlighting leading vendors and their innovative profiles. These include Accenture PLC, Advanced Micro Devices Inc., Amazon Web Services, Inc., Appinventiv Technology Pvt. Ltd., Cerebras Systems, Cisco Systems, Inc., DataRobot, Inc., Fortinet, Inc., G-Core Labs S.A., Google LLC by Alphabet Inc., Graphcore Limited, Groq, Inc., Hailo Technologies Ltd., Hewlett Packard Enterprise Development LP, Huawei Technologies Co., Ltd., Intel Corporation, International Business Machines Corporation, Lenovo Group Limited, Lightmatter, Inc., Meta Platforms, Inc., Micron Technology Inc., Microsoft Corporation, Mythic, Inc., NEC Corporation, Nutanix, Inc., NVIDIA Corporation, OpenAI OpCo, LLC, Oracle Corporation, Pure Storage, Inc., Salesforce, Inc., SambaNova Systems, Inc, Samsung Electronics Co., Ltd., SAP SE, SenseTime Group Inc., Siemens AG, Sony Group Corporation, Synopsys Inc., and Toshiba Corporation.
Market Segmentation & Coverage
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
1. What is the market size and forecast of the AI Infrastructure Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the AI Infrastructure Market?
3. What are the technology trends and regulatory frameworks in the AI Infrastructure Market?
4. What is the market share of the leading vendors in the AI Infrastructure Market?
5. Which modes and strategic moves are suitable for entering the AI Infrastructure Market?