人工智慧的采用：全球观点

本报告对各行业的人工智慧采用进行了详细分析，研究了硬体、软体和服务中的人工智慧使用情况、关键产品创新和投资，并确定了各地区的人工智慧采用趋势。

目录

第一章执行摘要

• 调查目的和目标
• 调查范围
• 市场摘要
• 招募视角
• 未来趋势和发展
• 产业分析
• 区域洞察
• 结论

第二章 市场概述

• AI实施概述
• 人工智慧应用的演变
• 重要历史里程碑
• 人工智慧的现状
• 主要技术模型
• 人工智慧实施的法规和标准
• EU
• 美国
• 中国
• 日本
• 韩国
• 印度
• 人工智慧应用的主要障碍
• 缺乏知识
• 资料隐私
• 整合挑战
• 美国关税法对人工智慧应用的影响

第三章 硬体解决方案中的人工智慧应用趋势

• 关键要点
• 招募分析
• AI处理器与加速器
• 记忆
• 领先 AI 硬体供应商的当前和未来创新

第四章：软体解决方案中的人工智慧采用趋势

• 关键要点
• 招募分析
• 人工智慧平台
• 主要AI软体供应商的当前和未来计划

第五章 服务解决方案中人工智慧应用的趋势

• 关键要点
• 按服务类型进行的招募分析
• 专业服务
• 託管服务
• 主要服务供应商的当前和未来计划

第六章 各产业人工智慧应用趋势

• 关键要点
• 招募分析
• 卫生保健
• 银行、金融服务和保险
• 物流与供应链
• 零售与电子商务
• 教育/教育技术
• 媒体与娱乐
• 通讯
• 其他（农业、汽车、製造业、能源、公用事业等）

第七章 各地区人工智慧应用趋势

• 关键要点
• 招募分析
• 北美洲
• 欧洲
• 亚太地区
• 拉丁美洲
• 中东和非洲

第 8 章：人工智慧应用案例研究

• 引入人工智慧来改善业务流程
• 案例研究1：通用电气实施Predix平台
• 案例研究2：简化通用汽车的车辆检查流程
• 案例研究3：不列颠哥伦比亚投资管理公司利用人工智慧优化业务流程
• 案例研究4：BP利用人工智慧提高石油和天然气产业的业务效率
• 案例研究5：达美航空利用人工智慧提高业务效率
• 案例研究6：美国银行采用 Erica AI 工具
• 案例研究7：Zodiac Maritime 的 AI 增强碰撞预测系统
• 案例研究8：德国电信利用人工智慧提高业务效率
• 案例研究9：鹿特丹港的智慧货柜管理
• 案例研究10：福斯公司采用亚马逊的人工智慧驱动工具
• 案例研究11：Kroger的智慧陈列架和价格优化
• 引进人工智慧进行产品/服务创新
• 案例研究1：人工智慧驱动的电子健康记录 (EHR) 优化
• 案例研究2：沃达丰的人工智慧驱动客户服务
• 案例研究3：零售业的预测分析
• 案例研究4：万事达卡利用人工智慧优化支付处理
• 案例研究5：西门子数位工业软体开发的人工智慧解决方案
• 案例研究6：罗彻斯特大学医学中心与蝴蝶网路合作
• 案例研究7：OSF HealthCare 的人工智慧虚拟助手
• 案例研究8：Valley Bank的反洗钱策略
• 案例研究9：欧洲管理与商业学院的人工智慧工具
• 案例研究10：AT&T 利用人工智慧重塑客户服务
• 案例研究11：博尔顿学院的人工智慧影片製作平台
• 案例研究12：丝芙兰在美妆零售领域的创新

第九章：人工智慧应用的未来

• 预言
• 人工智慧在主要产业应用的未来
• 卫生保健
• 银行、金融服务和保险
• 物流与供应链
• 媒体与娱乐
• 零售与电子商务

第十章 附录

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