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2024140

2034 年雲端運算人工智慧市場預測：按組件、部署模式、服務模式、應用程式、最終用戶和區域分類的全球分析

AI in Cloud Computing Market Forecasts to 2034 - Global Analysis By Component (Infrastructure, Platforms and Services), Deployment, Service Model, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球雲端運算領域的 AI 市場規模將達到 864 億美元，並在預測期內以 4.9% 的複合年成長率成長，到 2034 年將達到 1268 億美元。

雲端運算中的人工智慧是指將人工智慧和機器學習服務、基礎設施和平台整合到雲端運算環境中，包括GPU加速的AI訓練基礎設施、MLOps平台、AI模型交付端點、生成式AI API服務、AutoML工具、電腦視覺API、自然語言處理服務以及AI驅動的雲端管理功能。這些服務透過公有雲、私有雲和混合雲端架構交付，使企業無需在本地進行硬體投資即可開發、部署和擴展AI應用。

生成式人工智慧雲端基礎設施的激增

企業對生成式人工智慧應用開發前所未有的需求，正推動對大規模雲端基礎架構的投資。企業需要GPU加速的雲端運算能力來微調大規模語言模式、推理服務以及整合人工智慧應用，而這些在本地硬體投資方面並不經濟。超大規模雲端服務超大規模資料中心業者之間為爭奪生成式人工智慧工作負載佔有率而展開的競爭，促使他們增加對雲端容量擴展和人工智慧服務創新方面的投資，從而擴大了雲端人工智慧的整體潛在商機。

雲端人工智慧成本管理的複雜性

人工智慧雲端運算成本管理的複雜性為企業帶來了預算超支的風險。 GPU實例的每小時費用、大型語言模型的API令牌定價以及人工智慧訓練工作流程的資料傳輸費用，都會產生難以預測的支出，而傳統的雲端成本管治框架（專為非人工智慧工作負載設計）難以預測和管理這些支出。如果企業發現實際的人工智慧雲端運算成本遠超最初的商業案例預測，那麼它們將面臨一項艱鉅的任務：如何向財務部門的高階相關人員證明這項投資的合理性。

開發自主人工智慧雲

隨著歐洲、中東和亞太地區各國政府投資建構本土管理的AI雲端容量，以實現資料主權合規、監管獨立以及國家AI能力發展等諸多優勢（這些優勢是依賴美國超大規模資料中心業者雲端服務供應商無法實現的），國家自主AI雲端基礎設施計畫正成為一個重要的新興市場機會。這為區域雲端服務供應商和自主AI基礎設施開發夥伴關係創造了大量的採購機會。

超大規模資料中心業者帶來的市場集中度風險

三大超超大規模資料中心業者平台對人工智慧雲端基礎設施容量和人工智慧服務能力的極度集中，為企業和人工智慧應用開發帶來了依賴性風險。這是因為超大規模資料中心業者的定價權、服務可用性決策以及API變更管理直接影響人工智慧應用的經濟效益和營運連續性，而目前尚無足夠多的替代方案能夠提供同等廣度的人工智慧服務、地理覆蓋和可靠性保障。

新冠疫情的影響：

新冠疫情以前所未有的速度加速了企業雲端遷移，由於遠距辦公和數位化業務連續性的需求，企業對雲端採用的抵觸情緒有所緩解。這促使企業做出多年雲端投資承諾，並將雲端原生基礎架構確立為企業的預設運算架構。疫情期間的雲端採用為資料平台和API基礎架構奠定了基礎，進而為企業後續部署人工智慧能力提供了可能。後疫情時代數位經營模式的擴展將持續推動雲端人工智慧服務的應用成長。

在預測期內，服務業預計將成為規模最大的產業。

在預測期內，服務領域預計將佔據最大的市場佔有率。這是因為企業主要透過使用託管服務 API 來使用雲端 AI，包括機器學習模型訓練、推理服務、電腦視覺、自然語言處理和生成式 AI 應用程式介面 (API)。這些服務在三大超大規模資料中心業者雲端服務平台中佔據了最大的市場佔有率和最高的利潤率，並貢獻了整個 AI 雲端運算市場的大部分收入。

預計混合雲端細分市場在預測期內將呈現最高的複合年成長率。

在預測期內，混合雲端領域預計將呈現最高的成長率。這主要是由於企業傾向於採用混合雲端人工智慧架構，該架構允許在私有基礎設施上處理敏感數據，同時利用公共雲端的GPU容量來處理計算密集型人工智慧訓練和服務工作負載；此外，監管機構的數據居住要求也規定人工智慧工作負載必須在特定的地理或組織管理範圍內執行，而純公共雲端架構無法滿足這些要求。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率。這是因為美國擁有亞馬遜雲端服務（AWS）、微軟Azure和谷歌雲，這些服務佔據了全球人工智慧雲端基礎設施容量和收入的大部分，並且在美國科技、金融服務和醫療保健行業擁有全球最高的企業雲端人工智慧採用率。此外，超大規模資料中心超大規模資料中心業者的大規模基礎設施投資也集中在北美的資料中心叢集，以滿足全球對人工智慧工作負載的需求。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率。這主要歸功於中國、印度、日本、韓國和東南亞等國家企業雲人工智慧應用的快速成長；阿里雲、騰訊雲和華為雲等領先的區域雲端服務提供商不斷拓展面向國內和區域市場的人工智慧服務組合；以及亞太地區各國政府的雲人工智慧投資計劃，這些都催生了對雲人工智慧基礎設施採購的新機構需求。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要企業進行SWOT分析（最多3家公司）
  • 區域分類
    • 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：雲端運算領域的全球人工智慧市場：按組件分類

  • 基礎設施
  • 平台
  • 服務
    • 諮詢和顧問服務
    • 整合與部署
    • 支援與維護

第6章：雲端運算領域的全球人工智慧市場：以部署方式分類

  • 公共雲端
  • 私有雲端
  • 混合雲端

第7章：雲端運算領域的全球人工智慧市場：按服務模式分類

  • IaaS
  • PaaS
  • SaaS

第8章：雲端運算領域的全球人工智慧市場：按應用分類

  • 數據分析
  • 訓練人工智慧模型
  • 自動化
  • 客戶分析
  • 詐欺偵測與安全
  • 供應鏈最佳化
  • 個性化行銷和建議

第9章：雲端運算領域的全球人工智慧市場：按最終用戶分類

  • BFSI
  • 衛生保健
  • 零售
  • 資訊科技/通訊
  • 政府/公共部門

第10章：全球雲端運算人工智慧市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • Amazon Web Services Inc.
  • Microsoft Azure
  • Google Cloud
  • IBM Cloud
  • Oracle Cloud
  • Alibaba Cloud
  • Salesforce Inc.
  • SAP SE
  • VMware Inc.
  • Red Hat Inc.
  • Tencent Cloud
  • Huawei Cloud
  • DigitalOcean Holdings Inc.
  • Rackspace Technology
  • Snowflake Inc.
  • Databricks Inc.
  • ServiceNow Inc.
Product Code: SMRC35351

According to Stratistics MRC, the Global AI in Cloud Computing Market is accounted for $86.4 billion in 2026 and is expected to reach $126.8 billion by 2034 growing at a CAGR of 4.9% during the forecast period. AI in cloud computing refers to the integration of artificial intelligence and machine learning services, infrastructure, and platforms within cloud computing environments, encompassing GPU-accelerated AI training infrastructure, MLOps platforms, AI model serving endpoints, generative AI API services, AutoML tools, computer vision APIs, natural language processing services, and AI-powered cloud management capabilities delivered through public, private, and hybrid cloud architectures that enable enterprises to develop, deploy, and scale AI applications without on-premise hardware investment.

Market Dynamics:

Driver:

Generative AI Cloud Infrastructure Surge

Unprecedented enterprise demand for generative AI application development is driving massive cloud infrastructure investment as organizations require GPU-accelerated cloud computing capacity for large language model fine-tuning, inference serving, and AI application integration that cannot be economically delivered through on-premise hardware investment. Hyperscaler competition for generative AI workload share is generating substantial cloud capacity expansion investment and AI service innovation that expands total addressable cloud AI revenue opportunity.

Restraint:

Cloud AI Cost Management Complexity

AI cloud computing cost management complexity creates enterprise budget overrun risks as GPU instance hourly costs, large language model API token pricing, and data transfer fees for AI training workflows generate unpredictable expenditure that is difficult to forecast and control through conventional cloud cost governance frameworks designed for non-AI workload profiles. Organizations discovering actual AI cloud computing costs substantially exceeding initial business case projections face difficult investment justification challenges with senior finance stakeholders.

Opportunity:

Sovereign AI Cloud Development

National sovereign AI cloud infrastructure programs represent a major emerging market opportunity as governments across Europe, Middle East, and Asia Pacific invest in domestically controlled AI cloud capacity providing data sovereignty compliance, regulatory independence, and national AI capability development benefits that cannot be satisfied through reliance on US-headquartered hyperscaler cloud providers, creating substantial procurement opportunities for regional cloud providers and sovereign AI infrastructure development partnerships.

Threat:

Hyperscaler Market Concentration Risk

Extreme concentration of AI cloud infrastructure capacity and AI service capabilities within three dominant hyperscaler platforms creates dependency risk for enterprises and AI application developers as hyperscaler pricing power, service availability decisions, and API change management directly determine AI application economics and operational continuity without adequate competitive alternatives providing equivalent AI service breadth, geographic coverage, and reliability guarantees.

Covid-19 Impact:

COVID-19 accelerated enterprise cloud migration at unprecedented speed as remote work requirements and digital business continuity demands eliminated organizational resistance to cloud adoption, generating multi-year cloud investment commitments that established cloud-native infrastructure as the default enterprise computing architecture. Pandemic-era cloud adoption created the data platform and API infrastructure foundations enabling subsequent enterprise AI capability deployment. Post-pandemic digital business model expansion continues driving cloud AI service consumption growth.

The services segment is expected to be the largest during the forecast period

The services segment is expected to account for the largest market share during the forecast period, due to dominant enterprise consumption of cloud AI through managed service API consumption including machine learning model training, inference serving, computer vision, natural language processing, and generative AI application programming interfaces that represent the highest-volume and highest-margin cloud AI revenue category across all three major hyperscaler platforms generating the majority of total AI cloud computing market revenue.

The hybrid cloud segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the hybrid cloud segment is predicted to witness the highest growth rate, driven by enterprise preference for hybrid cloud AI architectures enabling sensitive data processing on private infrastructure while leveraging public cloud GPU capacity for computationally intensive AI training and serving workloads, combined with regulatory data residency requirements mandating certain AI workload execution within specific geographic or organizational control boundaries that pure public cloud architectures cannot satisfy.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to the United States hosting Amazon Web Services, Microsoft Azure, and Google Cloud representing the majority of global AI cloud infrastructure capacity and revenue, combined with the world's highest enterprise cloud AI adoption rates across technology, financial services, and healthcare sectors, and substantial hyperscaler infrastructure investment concentrated in North American data center clusters serving global AI workload demand.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, due to rapidly growing enterprise cloud AI adoption across China, India, Japan, South Korea, and Southeast Asia, major regional cloud providers including Alibaba Cloud, Tencent Cloud, and Huawei Cloud expanding AI service portfolios for domestic and regional markets, and substantial government cloud AI investment programs across Asia Pacific creating new institutional cloud AI infrastructure procurement demand.

Key players in the market

Some of the key players in AI in Cloud Computing Market include Amazon Web Services Inc., Microsoft Azure, Google Cloud, IBM Cloud, Oracle Cloud, Alibaba Cloud, Salesforce Inc., SAP SE, VMware Inc., Red Hat Inc., Tencent Cloud, Huawei Cloud, DigitalOcean Holdings Inc., Rackspace Technology, Snowflake Inc., Databricks Inc., and ServiceNow Inc..

Key Developments:

In March 2026, Amazon Web Services Inc. launched Amazon Bedrock enterprise expansion with new foundation model options and agent orchestration capabilities enabling enterprise generative AI application development at scale across multiple cloud regions.

In February 2026, Snowflake Inc. introduced Snowflake Arctic enterprise AI platform enabling organizations to train and deploy industry-specific large language models directly within their Snowflake data cloud environment without data movement.

In January 2026, Databricks Inc. expanded its Mosaic AI platform with new compound AI system tools enabling enterprise data teams to build sophisticated multi-model AI applications combining retrieval augmentation, fine-tuning, and agent orchestration.

Components Covered:

  • Infrastructure
  • Platforms
  • Services

Deployments Covered:

  • Public Cloud
  • Private Cloud
  • Hybrid Cloud

Service Models Covered:

  • IaaS
  • PaaS
  • SaaS

Applications Covered:

  • Data Analytics
  • AI Model Training
  • Automation
  • Customer Analytics
  • Fraud Detection & Security
  • Supply Chain Optimization
  • Personalized Marketing & Recommendations

End Users Covered:

  • BFSI
  • Healthcare
  • Retail
  • IT & Telecom
  • Government & Public Sector

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI in Cloud Computing Market, By Component

  • 5.1 Infrastructure
  • 5.2 Platforms
  • 5.3 Services
    • 5.3.1 Consulting & Advisory
    • 5.3.2 Integration & Deployment
    • 5.3.3 Support & Maintenance

6 Global AI in Cloud Computing Market, By Deployment

  • 6.1 Public Cloud
  • 6.2 Private Cloud
  • 6.3 Hybrid Cloud

7 Global AI in Cloud Computing Market, By Service Model

  • 7.1 IaaS
  • 7.2 PaaS
  • 7.3 SaaS

8 Global AI in Cloud Computing Market, By Application

  • 8.1 Data Analytics
  • 8.2 AI Model Training
  • 8.3 Automation
  • 8.4 Customer Analytics
  • 8.5 Fraud Detection & Security
  • 8.6 Supply Chain Optimization
  • 8.7 Personalized Marketing & Recommendations

9 Global AI in Cloud Computing Market, By End User

  • 9.1 BFSI
  • 9.2 Healthcare
  • 9.3 Retail
  • 9.4 IT & Telecom
  • 9.5 Government & Public Sector

10 Global AI in Cloud Computing Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 Amazon Web Services Inc.
  • 13.2 Microsoft Azure
  • 13.3 Google Cloud
  • 13.4 IBM Cloud
  • 13.5 Oracle Cloud
  • 13.6 Alibaba Cloud
  • 13.7 Salesforce Inc.
  • 13.8 SAP SE
  • 13.9 VMware Inc.
  • 13.10 Red Hat Inc.
  • 13.11 Tencent Cloud
  • 13.12 Huawei Cloud
  • 13.13 DigitalOcean Holdings Inc.
  • 13.14 Rackspace Technology
  • 13.15 Snowflake Inc.
  • 13.16 Databricks Inc.
  • 13.17 ServiceNow Inc.

List of Tables

  • Table 1 Global AI in Cloud Computing Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI in Cloud Computing Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI in Cloud Computing Market Outlook, By Infrastructure (2023-2034) ($MN)
  • Table 4 Global AI in Cloud Computing Market Outlook, By Platforms (2023-2034) ($MN)
  • Table 5 Global AI in Cloud Computing Market Outlook, By Services (2023-2034) ($MN)
  • Table 6 Global AI in Cloud Computing Market Outlook, By Consulting & Advisory (2023-2034) ($MN)
  • Table 7 Global AI in Cloud Computing Market Outlook, By Integration & Deployment (2023-2034) ($MN)
  • Table 8 Global AI in Cloud Computing Market Outlook, By Support & Maintenance (2023-2034) ($MN)
  • Table 9 Global AI in Cloud Computing Market Outlook, By Deployment (2023-2034) ($MN)
  • Table 10 Global AI in Cloud Computing Market Outlook, By Public Cloud (2023-2034) ($MN)
  • Table 11 Global AI in Cloud Computing Market Outlook, By Private Cloud (2023-2034) ($MN)
  • Table 12 Global AI in Cloud Computing Market Outlook, By Hybrid Cloud (2023-2034) ($MN)
  • Table 13 Global AI in Cloud Computing Market Outlook, By Service Model (2023-2034) ($MN)
  • Table 14 Global AI in Cloud Computing Market Outlook, By IaaS (2023-2034) ($MN)
  • Table 15 Global AI in Cloud Computing Market Outlook, By PaaS (2023-2034) ($MN)
  • Table 16 Global AI in Cloud Computing Market Outlook, By SaaS (2023-2034) ($MN)
  • Table 17 Global AI in Cloud Computing Market Outlook, By Application (2023-2034) ($MN)
  • Table 18 Global AI in Cloud Computing Market Outlook, By Data Analytics (2023-2034) ($MN)
  • Table 19 Global AI in Cloud Computing Market Outlook, By AI Model Training (2023-2034) ($MN)
  • Table 20 Global AI in Cloud Computing Market Outlook, By Automation (2023-2034) ($MN)
  • Table 21 Global AI in Cloud Computing Market Outlook, By Customer Analytics (2023-2034) ($MN)
  • Table 22 Global AI in Cloud Computing Market Outlook, By Fraud Detection & Security (2023-2034) ($MN)
  • Table 23 Global AI in Cloud Computing Market Outlook, By Supply Chain Optimization (2023-2034) ($MN)
  • Table 24 Global AI in Cloud Computing Market Outlook, By Personalized Marketing & Recommendations (2023-2034) ($MN)
  • Table 25 Global AI in Cloud Computing Market Outlook, By End User (2023-2034) ($MN)
  • Table 26 Global AI in Cloud Computing Market Outlook, By BFSI (2023-2034) ($MN)
  • Table 27 Global AI in Cloud Computing Market Outlook, By Healthcare (2023-2034) ($MN)
  • Table 28 Global AI in Cloud Computing Market Outlook, By Retail (2023-2034) ($MN)
  • Table 29 Global AI in Cloud Computing Market Outlook, By IT & Telecom (2023-2034) ($MN)
  • Table 30 Global AI in Cloud Computing Market Outlook, By Government & Public Sector (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.