人工智慧：市場佔有率分析、產業趨勢與統計、成長預測（2026-2031）

根據 Mordor Intelligence 預測，人工智慧 (AI) 市場規模將從 2025 年的 3,060.4 億美元成長到 2026 年的 4,344.2 億美元，然後在 2031 年達到 2,5031.3 億美元，2026 年至 2031 年的複合年成長率為 41.95%。

本報告按組件（硬體、軟體、服務）、部署模式（公共雲端、本地部署、混合部署）、技術（機器學習、深度學習、自然語言處理、電腦視覺、生成式人工智慧、情境感知運算等）、最終用戶產業（銀行、金融服務和保險、IT 和電信、醫療保健和生命科學、製造業等）以及地區對產業進行分類。

全球人工智慧市場趨勢與洞察

主權人工智慧和國家計算計劃

政府資金正在重塑各國的生態系統。印度的「印度人工智慧使命」（IndiaAI Mission）投資103.72億印度盧比（約1.245億美元），用於建構滿足本地語言需求的大規模本土語言模型。日本正投入10兆日圓，以增強其人工智慧和半導體生產能力，展現對長期自給自足的承諾。這些投資正在為能夠滿足本地化法規要求的國內硬體供應商和系統整合商創造強勁的需求。

數據量和數據多樣性的爆炸性成長

工業IoT的部署每天產生Terabyte的感測器數據，迫使企業採用人工智慧驅動的分析技術。西門子報告稱，透過將機器學習整合到其財務營運中，已實現90%的發票處理無接觸化，並獲得了565萬美元的年度投資回報。醫療成像、自動駕駛汽車和零售業的即時交易進一步加劇了數據洪流，推動了對可擴展儲存、邊緣處理和合成數據生成工具的需求。

GPU和電網供電瓶頸

NVIDIA 在 2026 會計年度展望中指出，H100 晶片長期供不應求。這項供應限制導致現貨價格比廠商建議零售價 (MSRP) 高出 30% 至 50%，延緩了企業引進週期。電力公司預測，到 2026 年，資料中心電力需求可能達到 1050 太瓦時 (TWh)，超過幾個關鍵地區的計畫供應成長。因此，新的 AI叢集專案進度面臨壓力。

細分市場分析

預計到2025年，軟體收入將維持61.35%的佔有率，鞏固其在人工智慧市場的基礎地位。然而，隨著企業將重心從實驗階段轉向全面部署，服務領域預計將以40.85%的複合年成長率快速成長，直到2031年。許多受監管行業現在需要的供應商不僅能夠提供許可證，還能解讀合規要求並重新設計工作流程。因此，由於合格整合商短缺，服務供應商能夠收取更高的價格，尤其是在醫療保健和金融服務等特定行業的項目中。

在諮詢、整合和管理服務等領域，擁有垂直行業專業知識的供應商更受青睞。在放射學領域，一項結合資料管治、演算法檢驗和臨床醫生工作流程重組的服務夥伴關係，幫助一家醫院集團在五年內實現了 451% 的投資報酬率。隨著客戶開始根據具體的生產力目標而非抽像模型的精確度來評估項目，那些將硬體、軟體和諮詢支援打包成基於結果的合約的專家，正在價值鏈中向上游移動。

到2025年，公共雲端將佔據人工智慧市場43.72%的佔有率，這反映了其作為預設開發環境的地位。然而，隨著企業對生產環境中延遲最佳化和成本可視性的需求日益成長，預計到2031年，混合模式的複合年成長率將達到45.55%。一些早期採用者正在超大規模叢集上進行模型訓練，然後將推理處理卸載到本地或邊緣設備以實現即時響應。汽車製造商透過在工廠車間執行毫秒視覺任務，同時保持雲端可擴展性以進行模型重新訓練，從而展示了這種架構的有效性。

在資源受限、頻寬成本高昂的環境中，例如海上開採設施和零售商店，邊緣部署同樣重要。而對於面臨嚴格資料居住要求的金融和公共部門而言，本地部署正在重新興起。硬體供應商現在將編配軟體與產品捆綁銷售，該軟體能夠根據策略規則在雲端、本地機架和邊緣設備之間遷移容器，這推動了人工智慧市場混合解決方案的成長趨勢。

區域分析

北美擁有充裕的創業投資、成熟的雲端生態系以及企業對人工智慧的快速應用，預計將在收入方面保持領先地位，到2025年將佔據37.12%的市場佔有率。諸如《晶片與科學法案》等聯邦項目正在為人工智慧半導體製造廠提供額外資金，支持國內硬體供應並增強人工智慧市場。維吉尼亞、德克薩斯州和奧勒岡州的高效能運算叢集持續吸引軟體新創公司入駐，這些公司選址靠近雲端可用區，以實現低延遲。

歐洲的成長軌跡受兩大因素影響：嚴格的資料隱私法規和龐大的國家計算預算。符合GDPR的架構要求供應商將推理工作負載在地化到區域範圍內，從而催生了對本地GPU設備的需求。法國的公私舉措Mistral AI預計到2025年估值將達到20億歐元，並計畫資金籌措10億美元用於擴展多語言模型訓練。德國和北歐國家也開展了類似的計劃，專注於部署符合雄心勃勃的碳減排目標的環保資料中心，這些計劃正在推動人工智慧市場實現兩位數的區域成長。

預計到2031年，亞太地區的複合年成長率將達到40.75%，成為全球成長最快的地區。中國的「國家半導體計畫」已撥款1兆元人民幣用於晶片及相關基礎設施建設，目標是在2030年前實現；印度已累計10372兆元人民幣用於國家人工智慧運算，推動其國內整合商躋身全球前列。在日本，一項數兆日圓的基金正在加速晶圓廠的升級改造，而人工智慧監管的放寬也縮短了其商業化部署的時間。包括新加坡和馬來西亞在內的東南亞國家已推出資料中心稅收優惠政策，鼓勵超大規模資料中心業者資料中心營運商建立區域中心，進一步擴大了該地區人工智慧市場的規模。

其他好處：

• Excel格式的市場預測（ME）表
• 3個月的分析師支持

目錄

第1章：引言

• 研究假設和市場定義
• 調查範圍

第2章：調查方法

第3章執行摘要

第4章 市場狀況

• 市場概覽
• 市場促進因素
  • 對預測分析的需求日益成長
  • 數據量和數據多樣性的爆炸性成長
  • 基於雲端的人工智慧服務的使用正在迅速成長。
  • 主權人工智慧和國家計算舉措
  • 遷移到本地/私有人工智慧以降低總體擁有成本 (TCO)
  • 節能型人工智慧硬體的需求
• 市場限制因素
  • 巨額資本投資和勞動力短缺
  • 資料隱私和合規障礙
  • GPU/電源網路供電瓶頸
  • 資料中心二氧化碳排放上限
• 重要法規結構的評估
• 價值鏈分析
• 技術展望
• 波特五力模型
• 對關鍵相關人員的影響評估
• 主要用例和案例研究
• 宏觀經濟因素對市場的影響
• 投資分析

第5章 市場區隔

• 按組件
  • 硬體
  • 軟體
  • 服務
• 部署模式
  • 公共雲端
  • 現場
  • 混合
• 透過技術
  • 機器學習
  • 深度學習
  • 自然語言處理
  • 電腦視覺
  • 人工智慧世代
  • 情境感知計算及其他
• 按最終用戶行業分類
  • BFSI
  • 資訊科技/通訊
  • 醫療保健和生命科學
  • 製造業
  • 零售與電子商務
  • 汽車和運輸業
  • 政府/國防
  • 能源公用事業
  • 媒體與娛樂
  • 建造
• 按地區
  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 南美洲
    • 巴西
    • 阿根廷
    • 其他南美國家
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 北歐的
    • 其他歐洲國家
  • 中東和非洲
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 土耳其
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 奈及利亞
      • 其他非洲國家
  • 亞太地區
    • 中國
    • 印度
    • 日本
    • 韓國
    • ASEAN
    • 澳洲
    • 紐西蘭
    • 其他亞太國家

第6章 競爭情勢

• 市場集中度
• 策略趨勢
• 市佔率分析
• 公司簡介
  • International Business Machines Corporation
  • Intel Corporation
  • Microsoft Corporation
  • Google LLC（Alphabet Inc.）
  • Amazon Web Services, Inc.（Amazon.com, Inc.）
  • Oracle Corporation
  • Salesforce, Inc.
  • SAP SE
  • SAS Institute Inc.
  • Cisco Systems, Inc.
  • Siemens AG
  • NVIDIA Corporation
  • Hewlett Packard Enterprise Company
  • Accenture plc
  • Baidu, Inc.
  • Alibaba Cloud（Intelligent Cloud Business of Alibaba Group Holding Limited）
  • Palantir Technologies Inc.
  • OpenAI, Inc.
  • Meta Platforms, Inc.
  • Huawei Technologies Co., Ltd.
  • Tencent Holdings Limited
  • ServiceNow, Inc.
  • Snowflake Inc.

第7章 市場機會與未來展望

According to Mordor Intelligence, the artificial intelligence market size is expected to grow from USD 306.04 billion in 2025 to USD 434.42 billion in 2026 and is forecast to reach USD 2,503.13 billion by 2031 at 41.95% CAGR over 2026-2031.

This report Segments the Industry Into by Component (Hardware, Software, and Services), Deployment Mode (Public Cloud, On-Premise, and Hybrid), Technology (Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Generative AI, and Context-Aware Computing and Others), End-User Industry (BFSI, IT and Telecommunications, Healthcare and Life Sciences, Manufacturing, and More), and Geography.

Global Artificial Intelligence Market Trends and Insights

Sovereign AI and national compute programs

Government funding is shaping local ecosystems. India's IndiaAI Mission is channeling INR 10,372 crore (USD 124.5 million) into indigenous large language models that meet local language needs. Japan is mobilising JPY 10 trillion for AI and semiconductor capacity, signalling a long-term commitment to self-reliance. Such investments create protected demand for domestic hardware vendors and systems integrators that can comply with localisation rules.

Explosive growth in data volume and variety

Industrial IoT rollouts generate terabytes of sensor data daily, pushing enterprises to adopt AI-driven analytics. Siemens reports 90% touchless invoice processing and USD 5.65 million annual ROI after embedding machine learning into its finance operations. Healthcare imaging, autonomous vehicles, and real-time retail transactions all add to the data deluge, driving up demand for scalable storage, edge processing, and synthetic data generation tools.

GPU and power-grid supply bottlenecks

NVIDIA cited persistent H100 shortages in its FY 2026 outlook, a constraint that has inflated spot prices 30-50% above MSRP and slowed enterprise deployment cycles. Power utilities forecast that data-center electricity demand could hit 1,050 TWh by 2026, exceeding planned capacity additions in several major regions, which in turn pressures project timelines for new AI clusters.

Other drivers and restraints analyzed in the detailed report include:

1. Surging adoption of cloud-based AI services
2. Shift toward on-prem or private AI for TCO control
3. High capex and talent shortages

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Software retained 61.35% revenue share in 2025, reinforcing its foundational role in the artificial intelligence market. Yet the Services segment is forecast to race ahead at 40.85% CAGR through 2031 as enterprises shift focus from experimentation to full-scale implementation. Many regulated industries now require vendors that can interpret compliance mandates and redesign workflows, rather than merely deliver licenses. The scarcity of qualified integrators, therefore, enables service providers to command premium pricing, especially for domain-specific projects in healthcare and financial services.

Across consulting, integration, and managed-services lines, vendors with vertical expertise are preferred. In radiology, service partnerships that combine data-governance, algorithm validation, and clinician workflow redesign are returning 451% ROI for hospital groups over five years. Specialists that package hardware, software, and advisory support into outcome-based contracts are moving up the value chain as customers measure projects against concrete productivity targets rather than abstract model accuracy.

Public Cloud held 43.72% of artificial intelligence market share in 2025, reflecting its role as the default development environment. Hybrid models, however, are projected to compound at 45.55% CAGR to 2031 as organizations seek latency optimization and cost visibility in production. Early adopters run training on hyperscale clusters then push inferencing to on-prem or edge devices for real-time response. Automotive OEMs validate this architecture by executing millisecond-level vision tasks on factory floors while retaining cloud elasticity for model retraining.

Edge rollouts are equally important in resource-constrained settings such as offshore rigs or retail outlets where bandwidth is expensive. On-prem deployments are resurging within finance and public-sector agencies that face strict data-residency mandates. Hardware suppliers now bundle orchestration software that migrates containers across clouds, on-prem racks, and edge devices based on policy rules, ensuring the artificial intelligence market size for hybrid solutions remains on an upward trajectory.

Complete Report Scope:

• By Component
  • Hardware
  • Software
  • Services
• By Deployment Mode
  • Public Cloud
  • On-Premise
  • Hybrid
• By Technology
  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Computer Vision
  • Generative AI
  • Context-Aware Computing and Others
• By End-user Industry
  • BFSI
  • IT and Telecommunications
  • Healthcare and Life Sciences
  • Manufacturing
  • Retail and E-commerce
  • Automotive and Transportation
  • Government and Defense
  • Energy and Utilities
  • Media and Entertainment
  • Construction
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Nordics
    • Rest of Europe
  • Middle East and Africa
    • Middle East
      • Saudi Arabia
      • United Arab Emirates
      • Turkey
      • Rest of Middle East
    • Africa
      • South Africa
      • Egypt
      • Nigeria
      • Rest of Africa
  • Asia-Pacific
    • China
    • India
    • Japan
    • South Korea
    • ASEAN
    • Australia
    • New Zealand
    • Rest of Asia-Pacific

Geography Analysis

North America remained the revenue leader with 37.12% share in 2025 thanks to deep venture capital pools, mature cloud ecosystems, and rapid enterprise adoption. Federal programs such as the CHIPS and Science Act funnel additional funding into AI-ready fabs, supporting domestic hardware supply and reinforcing the artificial intelligence market. High-performance computing clusters in Virginia, Texas, and Oregon continue to attract software start-ups that co-locate near cloud availability zones for lower latency.

Europe's growth profile is shaped by the twin forces of strict data-privacy regulation and sizable sovereign compute budgets. GDPR compliant architectures push vendors to localize inference workloads inside regional borders, creating demand for on-prem GPU appliances. France's public-private initiative around Mistral AI gained a €2 billion valuation in 2025 and aims to raise USD 1 billion to scale multilingual model training. Similar programs in Germany and the Nordics focus on green-data-center footprints that align with ambitious carbon-reduction targets, sustaining double-digit regional growth for the artificial intelligence market.

Asia-Pacific is projected to register a 40.75% CAGR through 2031, the fastest worldwide. China's National Semiconductor Mission allocates RMB 1 trillion by 2030 for chips and supporting infrastructure, while India earmarks INR10,372 crore for national AI compute, propelling domestic integrators into global rankings. Japan's multi-trillion-yen fund fast-tracks fab upgrades and light-touch AI regulation that accelerates time to commercial deployment. Southeast Asian economies, including Singapore and Malaysia, are introducing data-center tax incentives that entice hyperscalers to anchor regional hubs, further enlarging the artificial intelligence market size in the region.

1. International Business Machines Corporation
2. Intel Corporation
3. Microsoft Corporation
4. Google LLC (Alphabet Inc.)
5. Amazon Web Services, Inc. (Amazon.com, Inc.)
6. Oracle Corporation
7. Salesforce, Inc.
8. SAP SE
9. SAS Institute Inc.
10. Cisco Systems, Inc.
11. Siemens AG
12. NVIDIA Corporation
13. Hewlett Packard Enterprise Company
14. Accenture plc
15. Baidu, Inc.
16. Alibaba Cloud (Intelligent Cloud Business of Alibaba Group Holding Limited)
17. Palantir Technologies Inc.
18. OpenAI, Inc.
19. Meta Platforms, Inc.
20. Huawei Technologies Co., Ltd.
21. Tencent Holdings Limited
22. ServiceNow, Inc.
23. Snowflake Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising demand for predictive analytics
  • 4.2.2 Explosive growth in data volume/variety
  • 4.2.3 Surging adoption of cloud-based AI services
  • 4.2.4 Sovereign AI and national compute initiatives
  • 4.2.5 Shift toward on-prem/private AI for TCO control
  • 4.2.6 Demand for energy-efficient AI hardware
• 4.3 Market Restraints
  • 4.3.1 High capex and talent shortages
  • 4.3.2 Data-privacy and compliance barriers
  • 4.3.3 GPU / power-grid supply bottlenecks
  • 4.3.4 Data-center carbon-emission caps
• 4.4 Evaluation of Critical Regulatory Framework
• 4.5 Value Chain Analysis
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Competitive Rivalry
• 4.8 Impact Assessment of Key Stakeholders
• 4.9 Key Use Cases and Case Studies
• 4.10 Impact on Macroeconomic Factors of the Market
• 4.11 Investment Analysis

5 MARKET SEGMENTATION

• 5.1 By Component
  • 5.1.1 Hardware
  • 5.1.2 Software
  • 5.1.3 Services
• 5.2 By Deployment Mode
  • 5.2.1 Public Cloud
  • 5.2.2 On-Premise
  • 5.2.3 Hybrid
• 5.3 By Technology
  • 5.3.1 Machine Learning
  • 5.3.2 Deep Learning
  • 5.3.3 Natural Language Processing
  • 5.3.4 Computer Vision
  • 5.3.5 Generative AI
  • 5.3.6 Context-Aware Computing and Others
• 5.4 By End-user Industry
  • 5.4.1 BFSI
  • 5.4.2 IT and Telecommunications
  • 5.4.3 Healthcare and Life Sciences
  • 5.4.4 Manufacturing
  • 5.4.5 Retail and E-commerce
  • 5.4.6 Automotive and Transportation
  • 5.4.7 Government and Defense
  • 5.4.8 Energy and Utilities
  • 5.4.9 Media and Entertainment
  • 5.4.10 Construction
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 United Kingdom
    • 5.5.3.2 Germany
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Nordics
    • 5.5.3.7 Rest of Europe
  • 5.5.4 Middle East and Africa
    • 5.5.4.1 Middle East
      • 5.5.4.1.1 Saudi Arabia
      • 5.5.4.1.2 United Arab Emirates
      • 5.5.4.1.3 Turkey
      • 5.5.4.1.4 Rest of Middle East
    • 5.5.4.2 Africa
      • 5.5.4.2.1 South Africa
      • 5.5.4.2.2 Egypt
      • 5.5.4.2.3 Nigeria
      • 5.5.4.2.4 Rest of Africa
  • 5.5.5 Asia-Pacific
    • 5.5.5.1 China
    • 5.5.5.2 India
    • 5.5.5.3 Japan
    • 5.5.5.4 South Korea
    • 5.5.5.5 ASEAN
    • 5.5.5.6 Australia
    • 5.5.5.7 New Zealand
    • 5.5.5.8 Rest of Asia-Pacific

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
  • 6.4.1 International Business Machines Corporation
  • 6.4.2 Intel Corporation
  • 6.4.3 Microsoft Corporation
  • 6.4.4 Google LLC (Alphabet Inc.)
  • 6.4.5 Amazon Web Services, Inc. (Amazon.com, Inc.)
  • 6.4.6 Oracle Corporation
  • 6.4.7 Salesforce, Inc.
  • 6.4.8 SAP SE
  • 6.4.9 SAS Institute Inc.
  • 6.4.10 Cisco Systems, Inc.
  • 6.4.11 Siemens AG
  • 6.4.12 NVIDIA Corporation
  • 6.4.13 Hewlett Packard Enterprise Company
  • 6.4.14 Accenture plc
  • 6.4.15 Baidu, Inc.
  • 6.4.16 Alibaba Cloud (Intelligent Cloud Business of Alibaba Group Holding Limited)
  • 6.4.17 Palantir Technologies Inc.
  • 6.4.18 OpenAI, Inc.
  • 6.4.19 Meta Platforms, Inc.
  • 6.4.20 Huawei Technologies Co., Ltd.
  • 6.4.21 Tencent Holdings Limited
  • 6.4.22 ServiceNow, Inc.
  • 6.4.23 Snowflake Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-need Assessment