市場調查報告書
商品編碼
1470611
人工智慧基礎設施市場:按產品、部署和最終用戶分類 - 全球預測,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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人工智慧基礎設施市場規模預估2023年為365.2億美元,2024年達451.1億美元,預計2030年將達到1,654億美元,複合年成長率為24.08%。
人工智慧基礎設施市場是指支援各種最終用途產業的人工智慧(AI)應用和機器學習(ML)模型的部署、擴展和管理的硬體、軟體和服務生態系統。 AI 基礎設施包括 GPU、TPU 和 ASIC 等專用處理器、記憶體和儲存解決方案、網路設備、模型訓練軟體平台以及加速 AI 採用的諮詢服務。處理大型資料集的高效能運算平台的需求不斷成長,以及全球邊緣到雲端人工智慧基礎設施的興起,正在推動對人工智慧基礎設施解決方案的需求。此外,政府推動智慧製造和工業 4.0 設施的舉措也促進了市場成長。然而,設計複雜性、部署和維護問題可能會限制人工智慧基礎架構解決方案的採用。網路攻擊和資料外洩事件的脆弱性給市場帶來了挑戰。此外,技術進步以及人工智慧基礎設施與5G技術的整合預計將推動超低延遲和高頻寬應用的新時代,為市場創造新的機會。
主要市場統計 | |
---|---|
基準年[2023] | 365.2億美元 |
預測年份 [2024] | 451.1億美元 |
預測年份 [2030] | 1,654億美元 |
複合年成長率(%) | 24.08% |
滿足人工智慧生態系統特定需求的創新解決方案與服務
專用處理器和快速、可擴展的儲存解決方案等人工智慧硬體對於人工智慧模型的高效訓練和推理效能至關重要。基於 CPU 和 GPU 的系統是具有嚴格運算要求的組織的首選,因為它們的平行處理能力可以減少機器學習模型的訓練時間。 AI基礎設施服務包括實施AI解決方案、確保可維護性和擴充性的諮詢支持,以及用於效能監控的模型管理服務。實施由基於雲端基礎的基礎設施支援的學習模型,以最大限度地提高資源利用率。資料標記和註釋服務對於監督學習演算法維護隱私和安全標準至關重要。提供框架、資料準備工具、模型部署平台等多種軟體工具,用於設計、開發和部署人工智慧解決方案,為複雜操作提供高層介面。
部署:擴大雲端基礎的人工智慧基礎設施的使用,重點關注人工智慧服務的敏捷性和快速部署
雲端基礎的人工智慧基礎架構是一種彈性且擴充性的解決方案,可讓企業利用先進的人工智慧功能,而無需在硬體或維護方面進行大量投資。混合人工智慧基礎設施結合了雲端和本地的優點,使企業能夠保持對敏感資料的控制,同時根據特定要求最佳化部署。當您需要最大限度地控制人工智慧基礎架構或有嚴格的安全要求時,本地部署優於雲端基礎的解決方案。
最終用戶:人工智慧基礎設施擴大部署在企業和政府機構。
雲端服務供應商(CSP) 提供無縫、可擴展的 AI 基礎設施,為具有不同處理和儲存需求的廣泛客戶提供服務。各行各業的公司都在利用人工智慧基礎設施來實現資料分析、自動化以及透過聊天機器人和虛擬助理改善客戶服務等目的,並選擇正確的人工智慧基礎設施解決方案。政府機構正在利用人工智慧基礎設施進行各種應用,包括公共、醫療保健系統管理和交通管理,以提高安全性和合規性、成本效益和互通性。
區域洞察
美洲擁有高度發展的基礎設施,與人工智慧研發相關的投資顯著成長,並且存在重要的全球市場參與者。美國、加拿大和墨西哥是主要國家,不斷成長的消費者需求正在推動人工智慧基礎設施解決方案的採用。在歐盟(EU),法國和德國等國家處於加大研發投資以開發人工智慧技術的最前線。政府措施和政策在推動亞太地區各產業採用人工智慧方面發揮著至關重要的作用。中國、日本和印度等國家的政府已經認知到人工智慧對未來經濟成長的重要性,並正在大力投資研發(R&D)計畫以促進創新。此外,蓬勃發展的新興企業生態系統也對市場成長做出了重大貢獻。
FPNV定位矩陣
FPNV定位矩陣對於評估AI基礎設施市場至關重要。我們檢視與業務策略和產品滿意度相關的關鍵指標,以對供應商進行全面評估。這種深入的分析使用戶能夠根據自己的要求做出明智的決策。根據評估,供應商被分為四個成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市場佔有率分析
市場佔有率分析是一個綜合工具,可以對人工智慧基礎設施市場供應商的現狀進行深入而深入的研究。全面比較和分析供應商在整體收益、基本客群和其他關鍵指標方面的貢獻,以便更好地了解公司的績效及其在爭奪市場佔有率時面臨的挑戰。此外,該分析還提供了對該行業競爭特徵的寶貴見解,包括在研究基準年觀察到的累積、分散主導地位和合併特徵等因素。詳細程度的提高使供應商能夠做出更明智的決策並制定有效的策略,從而在市場上獲得競爭優勢。
1. 市場滲透率:提供有關主要企業所服務的市場的全面資訊。
2. 市場開拓:我們深入研究利潤豐厚的新興市場,並分析其在成熟細分市場的滲透率。
3. 市場多元化:提供有關新產品發布、開拓地區、最新發展和投資的詳細資訊。
4.競爭評估與資訊:對主要企業的市場佔有率、策略、產品、認證、監管狀況、專利狀況、製造能力等進行全面評估。
5. 產品開發與創新:提供對未來技術、研發活動和突破性產品開發的見解。
1.AI基礎設施市場的市場規模和預測是多少?
2.人工智慧基礎設施市場預測期間有哪些產品、細分市場、應用程式和領域需要考慮投資?
3.AI基礎設施市場的技術趨勢和法規結構是什麼?
4.AI基礎設施市場主要廠商的市場佔有率為何?
5.進入AI基礎設施市場的合適形式和策略手段是什麼?
[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?