人工智慧的採用：全球觀點

本報告對各行業的人工智慧採用進行了詳細分析，研究了硬體、軟體和服務中的人工智慧使用情況、關鍵產品創新和投資，並確定了各地區的人工智慧採用趨勢。

目錄

第1章 執行摘要

• 調查目的和目標
• 調查範圍
• 市場摘要
• 採用視角
• 未來趨勢和發展
• 產業分析
• 區域洞察
• 結論

第2章 市場概述

• AI實施概述
• 人工智慧應用的演變
• 重要歷史里程碑
• 人工智慧的現狀
• 主要技術模型
• 人工智慧實施的法規和標準
• EU
• 美國
• 中國
• 日本
• 韓國
• 印度
• 人工智慧應用的主要障礙
• 缺乏知識
• 資料隱私
• 整合挑戰
• 美國關稅法對人工智慧應用的影響

第3章 硬體解決方案中的人工智慧應用趨勢

• 關鍵要點
• 採用分析
• AI處理器與加速器
• 記憶
• 領先 AI 硬體供應商的當前和未來創新

第4章 軟體解決方案中的人工智慧採用趨勢

• 關鍵要點
• 採用分析
• 人工智慧平台
• 主要AI軟體供應商的當前和未來計劃

第5章 服務解決方案中人工智慧應用的趨勢

• 關鍵要點
• 採用分析依服務類型進行的
• 專業服務
• 託管服務
• 主要服務供應商的當前和未來計劃

第6章 各產業人工智慧應用趨勢

• 關鍵要點
• 採用分析
• 衛生保健
• 銀行、金融服務和保險
• 物流與供應鏈
• 零售與電子商務
• 教育/教育技術
• 媒體與娛樂
• 通訊
• 其他（農業、汽車、製造業、能源、公用事業等）

第7章 各地區人工智慧應用趨勢

• 關鍵要點
• 採用分析
• 北美洲
• 歐洲
• 亞太地區
• 拉丁美洲
• 中東和非洲

第8章 人工智慧應用案例研究

• 引進人工智慧來改善業務流程
• 案例研究1：General Electric 實施Predix平台
• 案例研究2：簡化General Motors的車輛檢查流程
• 案例研究3：British Columbia Investment Management Corp.利用人工智慧最佳化業務流程
• 案例研究4：BP利用人工智慧提高石油和天然氣產業的業務效率
• 案例研究5：Delta Airlines 利用人工智慧提高業務效率
• 案例研究6：Bank of America採用 Erica AI 工具
• 案例研究7：Zodiac Maritime 的AI 增強碰撞預測系統
• 案例研究8：Deutsche Telekom利用人工智慧提高業務效率
• 案例研究9：Port of Rotterdam的智慧貨櫃管理
• 案例研究10：Fox Corp. 採用Amazon的人工智慧驅動工具
• 案例研究11：Kroger的智慧陳列架和價格最佳化
• 引進人工智慧進行產品/服務創新
• 案例研究1：人工智慧驅動的電子健康記錄（EHR）最佳化
• 案例研究2：Vodafone的人工智慧驅動客戶服務
• 案例研究3：零售業的預測分析 (Predictive Analytics)
• 案例研究4：Mastercard利用人工智慧最佳化支付處理
• 案例研究5：Siemens Digital Industries Software開發的人工智慧解決方案
• 案例研究6：University of Rochester Medical Center與Butterfly Network 合作
• 案例研究7：OSF HealthCare 的人工智慧虛擬助手
• 案例研究8：Valley Bank的反洗錢策略
• 案例研究9：European School of Management and Business的人工智慧工具
• 案例研究10：AT&T 利用人工智慧重塑客戶服務
• 案例研究11：Bolton College的人工智慧影片製作平台
• 案例研究12：Sephora在美妝零售領域的創新

第9章 人工智慧應用的未來

• 預言
• 人工智慧在主要產業應用的未來
• 衛生保健
• 銀行、金融服務和保險
• 物流與供應鏈
• 媒體與娛樂
• 零售與電子商務

第10章 附錄

This report provides a detailed analysis of AI adoption across various industries. It will examine the use of AI in hardware, software and services, along with key product innovations and investments. The study will also highlight AI adoption trends in different regions.

Report Scope

This report aims to provide a thorough and detailed analysis of the current and future state of AI applications. Its scope includes a multifaceted review, covering both the technological progress driving AI and the various ways these developments are being used across different industries and by emerging businesses.

The following parameters define the scope of the report:

• The report will explore AI hardware, software and service solutions and provide a detailed overview of key developments and innovations. It will define each solution and highlight its significance in the evolving AI ecosystem.
• The report covers a descriptive analysis of AI adoption across various end-use industries. To provide deeper insight, it will include case studies at the application level within these sectors.
• The study highlights AI adoption trends across North America, Europe, Asia-Pacific, South America and the Middle East and Africa.
• The report identifies major challenges affecting AI implementation based on case study analyses for business process improvement and product development.

It will also outline key government guidelines, regulations and standards such as the EU AI Act, which are driving the rapid global AI adoption.

Report Includes

• A general outlook of the artificial intelligence (AI) adoption scenarios across industries by applications, with key companies' developments
• Trends in the AI adoption in hardware, software and services solutions, along with major technological innovations, current state of AI and historical milestones
• A look at the regulatory landscape featuring key international and regional regulations and standards for AI adoption
• Review of the impact of ongoing U.S. tariffs on global trade and investment, and challenges associated with AI infrastructure development and global supply chains
• Case studies on AI implementation to improve business processes and for product or service innovation
• Insights into future AI adoption plans of key companies across different sectors, and projections and growth forecasts through 2030
• Role of AI adoption in the global cybersecurity market landscape
• Expert quotes on AI adoption from primary respondents

Table of Contents

Chapter 1 Executive Summary

• Study Goals and Objectives
• Scope of Report
• Market Summary
• Adoption Viewpoint
• Future Trends and Developments
• Industry Analysis
• Regional Insights
• Conclusion

Chapter 2 Market Overview

• AI Adoption Overview
• Evolution of AI Adoption
• Key Historical Milestones
• Current State of AI
• Key Technology Models
• Regulations and Standards for AI Adoption
• European Union
• U.S.
• China
• Japan
• South Korea
• India
• Key Barriers for AI Adoption
• Lack of Knowledge
• Data Privacy
• Integration Challenges
• Impact of U.S. Tariff Laws on AI Adoption

Chapter 3 AI Adoption in Hardware Solutions

• Key Takeaways
• Adoption Analysis
• AI Processors and Accelerators
• Memory
• Current and Future Innovations of Key AI Hardware Providers

Chapter 4 AI Adoption in Software Solutions

• Key Takeaways
• Adoption Analysis
• AI Platforms
• Current and Future Plans of Key AI Software Providers

Chapter 5 AI Adoption in Service Solutions

• Key Takeaways
• Adoption Analysis by Service Type
• Professional Services
• Managed Services
• Current and Future Plans for Key Service Providers

Chapter 6 AI Adoption by Industries

• Key Takeaways
• Adoption Analysis
• Healthcare
• Banking, Financial Services and Insurance
• Logistics and Supply Chain
• Retail and eCommerce
• Education and EdTech
• Media and Entertainment
• Telecommunication
• Others (Agriculture, Automotive, Manufacturing, Energy and Utilities and More)

Chapter 7 AI Adoption Trends by Regions

• Key Takeaways
• Adoption Analysis
• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East and Africa

Chapter 8 Case Studies on AI Adoption

• AI Implementation to Improve Business Processes
• Case Study 1: General Electric's Deployment of Predix Platform
• Case Study 2: General Motors' Vehicle Inspection Process Efficiency
• Case Study 3: British Columbia Investment Management Corp. Implemented AI to Optimize Business Procedures
• Case Study 4: AI for Operational Efficiency in Oil and Gas at BP
• Case Study 5: Delta Airlines Improved Operational Efficiency Using AI
• Case Study 6: Bank of America's Adoption of AI Tool Erica
• Case Study 7: Zodiac Maritime's AI-Enhanced Collision Prediction System
• Case Study 8: Deutsche Telekom Improving Operational Efficacy with AI
• Case Study 9: Port of Rotterdam's Smart Container Management
• Case Study 10: Fox Corp. Implemented Amazon's AI-Driven Tools
• Case Study 11: Kroger's Intelligent Shelving and Pricing Optimization
• AI Implementation for Product/Service Innovation
• Case Study 1: AI-Powered Electronic Health Records Optimization
• Case Study 2: Vodafone's AI-Driven Customer Service
• Case Study 3: Predictive Analytics in Retail
• Case Study 4: Mastercard Optimized Payment Processing with AI
• Case Study 5: Siemens Digital Industries Software Developed an AI Solution
• Case Study 6: Collaboration Between the University of Rochester Medical Center and Butterfly Network
• Case Study 7: OSF HealthCare's AI-Powered Virtual Assistant
• Case Study 8: Valley Bank's Anti-Money Laundering
• Case Study 9: AI-Powered Tool for European School of Management and Business
• Case Study 10: AT&T Transformed Customer Service with AI
• Case Study 11: Bolton College's AI-Powered Video Creation Platform
• Case Study 12: Sephora's Innovation in Beauty Retail

Chapter 9 Future of AI Adoption

• Forecasts and Predictions
• Future of AI Adoption in Key Industries
• Healthcare
• Banking, Financial Services and Insurance
• Logistics and Supply Chain
• Media and Entertainment
• Retail and E-Commerce

Chapter 10 Appendix

• Methodology
• References
• Abbreviations

List of Tables

• Table 1 : Key Historical AI Milestones, 2000-2016
• Table 2 : Types of AI Technology, Primary Function and Applications
• Table 3 : AI Services Provided by IBM
• Table 4 : Value of AI Implementation across BFSI
• Table 5 : AI Applications in Media and Entertainment
• Table 6 : AI Applications in Agriculture
• Table 7 : Phases and Milestones: The AI Adoption Roadmap
• Table 8 : Agentic AI in BFSI
• Table 9 : Agentic AI in Retail and eCommerce
• Table 10 : Abbreviations Used in This Report

List of Figures

• Figure 1 : Global Corporate Investments in AI, 2019-2024
• Figure 2 : Notable AI Models in the U.S., China and Europe, 2024
• Figure 3 : Key Barriers to AI Adoption, 2024
• Figure 4 : U.S. AI-Directed Technology Imports, November 2024 to March 2025
• Figure 5 : U.S. Survey of GenAI Adoption at Work and at Home, August 2024
• Figure 6 : Organizations Using AI and GenAI in at Least One Business Function, 2020-2024
• Figure 7 : Number of AI Medical Devices Approved by the FDA, 2018-2023
• Figure 8 : Share of Firms That Have Adopted AI, by Employee Size, in the U.S., 2024