人工智慧颠覆：全球视角

本报告对全球主要产业和地区人工智慧驱动的颠覆性变革的现状和未来发展趋势进行了前沿分析。

该报告重点阐述了人工智慧对多个行业的影响，并说明了其背后的技术创新，整合了案例研究、政府数据以及按平台分類的人工智慧发展信息，从而全面而战略性地展现了人工智慧对全球的颠覆性观点。

报告内容

• 对人工智慧主导的关键产业和全球区域颠覆性影响进行全面、即时的分析
• 重点介绍人工智慧在多个产业中引发的重大变革，并概述其背后的技术创新。
• 一种整合案例研究、政府数据和平台特定人工智慧开发资讯的策略性和整体性观点
• 了解人工智慧如何改变技术基础设施、业务结构、客户触点和竞争环境
• 对已利用人工智慧进行平台转型的公司进行即时案例分析，并探讨其向人工智慧原生平台过渡的现状。
• 整合领先的人工智慧管治和研究机构的框架和出版物
• 识别区域领先者和落后者
• 来自业界专家和思想领袖的真知灼见，探讨人工智慧将如何改变商业模式。

目录

第一章执行摘要

• 调查目标和目的
• 进行这项调查的原因
• 调查范围
• 市场摘要
• 颠覆性观点
• 未来趋势与发展
• 产业分析
• 区域洞察
• 结论

第二章 市场概览

• 人工智慧颠覆性影响概述
• 季度回顾：人工智慧转型的主要亮点
• AI市场脉搏仪表板
• 领先的人工智慧颠覆性Start-Ups
• 区域政策的变化
• 云端服务和託管市场趋势
• 人工智慧的演变
• 历史里程碑
• 人工智慧现况（2025）
• 人工智慧平台转型
• 基础模型
• 生成式人工智慧革命
• 2025年及以后的人工智慧

第三章：人工智慧是机会，而非威胁

• 概述
• 新工作涌现/传统工作流失
• 卫生保健
• 传统工作正在消失。
• 创造新的就业机会
• 金融与银行
• 传统工作正在消失。
• 创造新的就业机会
• 製造和供应链
• 传统工作正在消失。
• 创造新的就业机会
• 零售与电子商务
• 传统工作正在消失。
• 创造新的就业机会
• 教育/教育科技
• 传统工作正在消失。
• 创造新的就业机会
• 运输/物流
• 传统工作正在消失。
• 创造新的就业机会
• 媒体与娱乐
• 传统工作正在消失。
• 创造新的就业机会

第四章：人工智慧引发的颠覆类型

• 概述
• 科技颠覆
• 营运中断
• 面向客户的干扰
• 竞争环境的变化

第五章：技术颠覆

• 概述
• 主要趋势
• 成分
• 高阶机器学习和深度学习
• 人工智慧世代
• 自动化和机器人技术
• 预测分析
• 自然语言处理
• 边缘人工智慧和云端人工智慧
• 人工智慧作为一种通用技术
• 人工智慧对产品开发和研发的变革性影响

第六章：营运中断

• 概述
• 主要趋势
• 成分
• 超自动化与智慧工作流程编配
• 预测分析与规范分析
• 人工智慧驱动的人力劳动力
• 数位双胞胎和即时监测
• 动态资源分配与最佳化
• 流程自动化
• 人工智慧在供应链和物流的应用
• 供应链管理的人工智慧挑战
• 人工智慧在环境、社会及治理（ESG）和永续商业报告中的应用

第七章：客户服务中断

• 概述
• 主要趋势
• 成分
• 对话式人工智慧和虚拟助手
• 视觉搜寻和推荐系统
• 预测性客户智能
• 辨识情绪和感受
• 人工智慧驱动的个人化
• 利用行为人工智慧进行体验设计
• 身临其境型人工智慧在扩增实境/虚拟实境商务中的应用

第八章 竞争颠覆

• 概述
• 主要趋势
• 成分
• 人工智慧原生经营模式
• 专有数据和网路效应
• 透过自动化实现成本领先
• 平台策略和生态系统货币化
• 人工智慧工具降低了准入门槛
• Start-Ups与成熟公司
• 人工智慧作为併购和企业估值中的策略资产
• 创新民主化
• 市场结构的变化以及现有公司面临的挑战

第九章：人工智慧对关键产业的影响

• 概述
• 卫生保健
• 金融
• 製造和供应链
• 零售与电子商务
• 教育/教育科技
• 运输/物流
• 媒体与娱乐
• 其他（政府部门、基础建设、法律与合规）

第十章：人工智慧对关键地区的颠覆性影响

• 概述
• 北美洲
• 欧洲
• 亚太地区
• 世界其他地区

第十一章：人工智慧颠覆性案例研究

• 卫生保健
• 製造和供应链
• 运输/物流
• 零售与电子商务
• 媒体与娱乐

第十二章 专家意见

• 来自主要受访者和主题专家的引述
• 人工智慧如何颠覆化学工业
• 人工智慧将如何颠覆科技产业
• 人工智慧将如何颠覆医疗保健产业
• 人工智慧将如何颠覆製造业
• 关于人工智慧颠覆性创新的新辩论
• Anthropic
• Meta
• Apple
• Salesforce
• 亚马逊（AWS、机器人）
• Microsoft

第十三章：人工智慧颠覆性变革的未来

• 未来展望
• 预测与展望
• 技术创新
• 检索增强生成（RAG）和知识接地
• 参数高效的微调
• 客製化人工智慧加速器和机架级硬体
• 边缘人工智慧/设备端人工智慧
• 智能体人工智慧
• 通用人工智慧
• 神经型态人工智慧

第十四章附录

This report provides an up-to-date analysis of current and future AI disruptions across major industries and global regions. It highlights AI disruptions in multiple industries; explains the innovations behind development; and integrates case studies, governmental data and platform-specific AI developments to deliver a holistic and strategic perspective on global AI disruptions.

Report Scope

This report analyzes how AI disrupts industries, organizations and societies across technological, operational, customer-facing and competitive dimensions. It extends beyond tracking AI adoption trends and focuses on understanding disruption as a systemic force, mapping its worldwide impact on value creation and socio-economy. The study draws on global benchmarks, real-time applications and deep research from academic, corporate and policy institutions to define the evolving AI landscape. The report examines several vectors, including platform shifts involving AI-native architectures, generative AI, automation systems, robotics and data infrastructure. It examines the reengineering of internal workflows, supply chains, logistics and decision-making through intelligent automation and ML-based optimization. It also examines AI in user experience, personalization engines, predictive services, voice interfaces and AI agents.

The report focuses on the most AI-affected sectors globally, with trend analysis in domains such as healthcare, finance and banking, manufacturing and supply chain, retail and e-commerce, education and edtech, transportation and logistics, media and entertainment, and other emerging sectors. The study also presents a regional landscape to identify AI leaders and late adopters. It maps the regional maturity, investment flows, talent ecosystems and policy environments in North America, Asia-Pacific, Europe and the Rest of the World (RoW).

The report evaluates AI disruption through multiple interconnected dimensions that include:

• Shifts in market capitalization linked to AI integration along with Job creation and displacement across cognitive and manual sectors.
• Breakthroughs in foundational models driving sectoral disruption.
• Changes in M&A activity and ecosystem consolidation around data-rich companies.
• Governance frameworks, and implications for data sovereignty and accountability.

Report Includes

• A comprehensive real-time analysis of AI-driven disruptions across major industries and global regions
• Highlights of key AI disruptions in multiple industries and a preview of the innovations behind the developments
• Integration of case studies, governmental data and platform-specific AI developments to deliver a holistic and strategic perspective on global AI disruption
• An understanding of how AI is fundamentally transforming technological infrastructures, operational frameworks, customer interfaces and the competitive dynamics of businesses
• Analyses of real-time Use Cases of companies that has undergone platform shifts due to AI and highlight migration to AI-native platforms
• Incorporate frameworks and publications from leading AI governance and research bodies
• A regional landscape to identify AI leaders and late adopters
• Informed perspectives on how AI can transform businesses from industry experts and thought leaders

Table of Contents

Chapter 1 Executive Summary

• Study Goals and Objectives
• Reasons for Doing This Study
• Scope of Report
• Market Summary
• Disruption Viewpoint
• Future Trends and Development
• Industry Analysis
• Regional Insights
• Conclusion

Chapter 2 Market Overview

• AI Disruption Overview
• Quarter-in-Review: Key AI Disruption Highlights
• AI Market Pulse Dashboard
• Key AI Disruptive Startups
• Regional Policy Shifts
• Cloud and Colocation Market Dynamics
• Evolution of AI
• Historical Milestones
• Current State of AI (2025)
• AI Platform Shift
• Foundation Models
• Generative AI Revolution
• AI Beyond 2025

Chapter 3 AI as an Opportunity, not a Threat

• Overview
• New Job Roles Created/Traditional Jobs Being Displaced
• Healthcare
• Traditional Jobs Being Displaced
• New Job Roles Created
• Finance and Banking
• Traditional Jobs Being Displaced
• New Job Roles Created
• Manufacturing and Supply Chain
• Traditional Jobs Being Displaced
• New Job Roles Created
• Retail and e-Commerce
• Traditional Jobs Being Displaced
• New Job Roles Created
• Education and EdTech
• Traditional Jobs Being Displaced
• New Job Roles Created
• Transportation and Logistics
• Traditional Jobs Being Displaced
• New Job Roles Created
• Media and Entertainment
• Traditional Jobs Being Displaced
• New Job Roles Created

Chapter 4 Type of Disruptions Influenced by AI

• Overview
• Technological Disruption
• Operational Disruption
• Customer-Facing Disruption
• Competitive Landscape Shift

Chapter 5 Technological Disruptions

• Overview
• Key Trends in Technological Disruption
• Components of AI-Driven Technological Disruption
• Advanced ML and Deep Learning
• Generative AI
• Automation and Robotics
• Predictive Analytics
• Natural Language Processing
• Edge and Cloud AI
• AI as a General-Purpose Technology
• AI's Transformative Impact on Product Development and R&D

Chapter 6 Operational Disruptions

• Overview
• Key Trends in AI-Driven Operational Disruption
• Components of AI-Driven Operational Disruption
• Hyperautomation and Intelligent Workflow Orchestration
• Predictive and Prescriptive Analytics
• AI-Augmented Human Workforce
• Digital Twins and Real-Time Monitoring
• Dynamic Resource Allocation and Optimization
• Process Automation
• AI in Supply Chain and Logistics
• Challenges of AI in Supply Chain Management
• AI in ESG and Sustainable Operations Reporting

Chapter 7 Customer-Facing Disruptions

• Overview
• Key Trends in AI-Driven Customer-Facing Disruptions
• Components of AI-Driven Customer-Facing Disruption
• Conversational AI and Virtual Assistants
• Visual Search and Recommendation Systems
• Predictive Customer Intelligence
• Emotion and Sentiment Recognition
• AI-Driven Personalization
• Experience Design Powered by Behavioral AI
• Immersive AI in AR/VR Commerce

Chapter 8 Competitive Disruptions

• Overview
• Key Trends in AI-Driven Competitive Disruptions
• Components of AI-Driven Competitive Disruption
• AI-Native Business Models
• Proprietary Data and Network Effects
• Automation-enabled Cost Leadership
• Platform Play and Ecosystem Monetization
• AI Tools Lowering Barriers to Entry
• Startups vs. Incumbents
• AI as a Strategic Asset in M&A and Valuation
• Democratization of Innovation
• Market Shifts and Incumbent Challenges

Chapter 9 AI Impact on Major Industries

• Overview
• Healthcare
• Finance
• Manufacturing and Supply Chain
• Retail and E-commerce
• Education and Edtech
• Transportation and Logistics
• Media and Entertainment
• Others (Government Sectors, Infrastructure, Legal and Compliance)

Chapter 10 AI Disruption in Major Regions

• Overview
• North America
• Europe
• Asia-Pacific
• Rest of the World

Chapter 11 Case Studies of AI Disruptions

• Case Studies of Disruptions
• Healthcare
• Manufacturing and Supply Chain
• Transportation and Logistics
• Retail and e-Commerce
• Media and Entertainment

Chapter 12 Expert Opinions

• Quotes from Primary Respondents and Domain Experts
• How AI is Disrupting the Chemicals Industry
• How AI is Disrupting the Technology Industry
• How AI is Disrupting the Healthcare Industry
• How AI is Disrupting the Manufacturing Industry
• Emerging Narratives in the AI Disruption Debate
• Anthropic
• Meta
• Apple
• Salesforce
• Amazon (AWS/Robotics)
• Microsoft

Chapter 13 Future of AI Disruption

• Future of AI Disruption
• Forecasts and Predictions (2025-2030)
• Innovations
• Retrieval-Augmented Generation (RAG) and Knowledge-Grounding
• Parameter-Efficient Fine-Tuning
• Custom AI Accelerators and Rack-Scale Hardware
• Edge and On-device AI
• Agentic AI
• Artificial General Intelligence (AGI)
• Neuromorphic AI

Chapter 14 Appendix

• Methodology
• References
• Abbreviations

List of Tables

• Table 1 : KPIs Quarter 3, 2025
• Table 2 : Scenario Planning Matrix, 2030
• Table 3 : Exposure to AI Automation by Aggregated Occupation Group, 2025
• Table 4 : AI Disruption vs. AI Transformation vs. AI Optimization
• Table 5 : Real-Time Technological Use Cases, 2025
• Table 6 : Real-Time Operational Use Cases, 2025
• Table 7 : Real-Time Customer Facing Use Cases, 2025
• Table 8 : Real-Time Competitive Landscape Shift Use Cases, 2025
• Table 9 : SWOT Analysis: Startups vs. Incumbents
• Table 10 : Global AI Market, by Region, Through 2030
• Table 11 : Abbreviations Used in This Report

List of Figures

• Figure 1 : AI Use Cases in Operations Management