人工智慧颠覆：全球市场概览

本报告从技术、营运、客户服务、竞争环境等多个角度全面分析了人工智慧对产业、组织和社会的影响。

本报告探讨了人工智慧原生架构的多个方面，包括平台转型、生成式人工智慧、自动化系统、机器人技术和资料基础设施，并分析如何透过智慧自动化和机器学习 (ML) 优化重塑内部工作流程、供应链、物流和决策。报告也探讨了人工智慧在使用者体验、个人化引擎、预测服务、语音介面和人工智慧代理方面的应用。

本报告聚焦于全球受人工智慧影响最大的产业，展示医疗保健、金融与银行、製造与供应链、零售与电子商务、教育与教育科技、运输与物流、媒体与娱乐以及其他新兴领域的实际应用案例和趋势分析。报告还涵盖区域格局，识别人工智慧领域的领导者和落后者。报告中还描绘了北美、亚太、欧洲和其他地区的成熟度、投资趋势、人才生态系统和政策环境。

目录

第一章执行摘要

第二章 市场概述

• 人工智慧颠覆性创新概述
• 人工智慧带来的颠覆性变化的特点
• 人工智慧的演变
• 历史里程碑
• 人工智慧现况（2025年）
• AI平台迁移
• 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：人工智慧造成的颠覆类型

• 概述
• 技术创新
• 即时用例
• 营运中断
• 即时用例
• 客户互动的颠覆性变化
• 即时用例
• 竞争格局的变化
• 即时用例

第四章：技术颠覆

• 概述
• 技术创新的主要趋势
• 人工智慧主导的技术颠覆的基石
• 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（NLP）
• 边缘人工智慧和云端人工智慧
• 人工智慧市场的崛起
• 人工智慧作为通用技术
• 机器学习、自然语言处理和电脑视觉领域的创新
• 人工智慧对产品开发和研发的变革性影响

第五章：营运中断

• 概述
• 人工智慧将如何颠覆营运的关键趋势
• 人工智慧驱动的营运中断的组成部分
• 超自动化与智慧工作流程编配
• 预测分析与规范分析
• 人工智慧驱动的人类劳动力
• 数位双胞胎与即时监控
• 动态资源分配与最佳化
• 智慧决策支援系统
• 流程自动化
• 预测性维护
• 供应链和物流中的人工智慧
• 供应链管理中的资料类型
• 供应链管理的人工智慧挑战
• ESG 和永续商业报告中的 AI

第六章：客户服务中断

• 概述
• 人工智慧主导的客户互动颠覆性创新的主要趋势
• 人工智慧主导的客户互动中的颠覆性创新建构模组
• 对话式人工智慧和虚拟助手
• 视觉搜寻和推荐系统
• 预测客户智能
• 辨识情绪和感受
• 人工智慧驱动的个人化
• 使用行为人工智慧进行体验设计
• AR/VR商务中的身临其境型AI
• 人工智慧如何影响数位无障碍

第七章 竞争扰乱

• 概述
• 人工智慧颠覆竞争的关键挑战
• 人工智慧主导的竞争颠覆的主要趋势
• 人工智慧主导的竞争颠覆的组成部分
• AI原生经营模式
• 独特的数据和网路效应
• 透过自动化实现成本领先
• 平台游戏和生态系统收益
• 开放原始码和人工智慧平台的作用
• 人工智慧工具降低了进入门槛
• Start-Ups与成熟公司
• 人工智慧作为併购和估值中的策略资产
• 民主化创新
• 现有企业面临的市场变化与挑战

第八章：人工智慧对重点产业的影响

• 概述
• 人工智慧对重点产业的影响
• 卫生保健
• 金融
• 製造和供应链
• 零售与电子商务
• 教育与教育技术
• 运输/物流
• 媒体与娱乐
• 其他（政府部门、基础建设、法律与合规）

第九章 人工智慧驱动重点区域颠覆性变革

• 概述
• 北美洲
• 欧洲
• 亚太地区
• 世界其他地区

第 10 章：颠覆案例研究

• 颠覆案例研究
• 卫生保健
• 谷歌 DeepMind 的 AlphaFold
• 利用 Deep 6 AI 加速临床试验
• 阿斯特捷利康利用人工智慧彻底改变癌症治疗
• 罗氏利用人工智慧彻底改变药物研发
• 诺华的人工智慧药物开发
• 製造和供应链
• 亚马逊供应链中的人工智慧转型
• 联合利华的供应链优化
• 西门子推进工业自动化
• 通用电气生产最佳化
• 运输/物流
• 特斯拉自动驾驶汽车
• 空中巴士在飞机维修中使用人工智慧
• 福特提升驾驶安全性
• 零售与电子商务
• Zara 的人工智慧驱动零售策略
• Stitch Fix 改变时尚零售业的未来
• 利用 Salesforce 协助客户关係管理 (CRM)
• 宝洁将人工智慧引入消费品製造
• 媒体与娱乐
• Netflix 的个人化娱乐
• 百度推广语音辨识
• NVIDIA 利用 AI 改善游戏图形
• 金融与银行
• 美国运通利用人工智慧增强交易安全性
• 其他领域
• 蓝河科技在农业领域应用人工智慧
• The Weather Company 的天气模式预报
• 思科利用人工智慧实现网路安全
• 壳牌的能源资源优化
• 乌克兰的人工智慧无人机袭击宣传活动

第十一章 专家意见

• 主要受访者和主题专家的引言
• 人工智慧将如何颠覆製造业和物流业
• 人工智慧将如何颠覆教育产业
• 人工智慧如何颠覆生产力软体产业
• 人工智慧将如何颠覆出版业
• 访谈重点
• 製造和物流
• 教育与教育技术
• 生产力
• 发布
• 人工智慧驱动的颠覆性变革辩论中的新叙事
• 从替代到增强
• 人工智慧作为通用技术
• 道德人工智慧
• 全球人工智慧竞赛
• 民主化与集权化

第 12 章：人工智慧颠覆的未来

• 人工智慧颠覆的未来
• 预言
• 创新
• 代理人工智慧
• 通用人工智慧（AGI）
• 神经型态人工智慧

第十三章 附录

This report provides an up-to-date analysis of current and future AI disruptions across key sectors and global regions. The report 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 disruption.

Report Scope

This report comprehensively analyzes how AI disrupts industries, organizations and societies across technological, operational, customer-facing and competitive dimensions. 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 real-world use cases and 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 base year for the market study is 2024, with estimates and forecasts for 2025 through 2030. Market estimates are valued in U.S. dollars (millions). The study covers current market and technological conditions involving real-time case studies, implementation data and short-term trends. This is followed by forecast (2025 through 2030), including AI maturity roadmaps, workforce evolution, disruption inflection points, feedback from key industry players, investment trends and regulatory timelines.

Report Includes

• An overview of the types of disruptions influenced by AI, e.g., technological, operational, customer-facing, or shifts in the competitive landscape
• Information on operational disruptions, which focuses on how AI is changing core operations, workflows and supply chains
• Discussion of the transformation or replacement of job functions, as well as shifts in the skill demand across various industries
• Competitive disruption and market entry, i.e., lowering of market entry barriers due to AI
• Analysis of disruption in customer experience and discussion of how AI is transforming user experience, personalization and customer support
• Coverage of case studies of companies that have undergone major disruption due to AI adoption
• Expert quotes on AI disruption from primary respondents

Table of Contents

Chapter 1 Executive Summary

• Study Goals and Objectives
• Reasons for Doing This Study
• Scope of Report

Chapter 2 Market Overview

• AI Disruption Overview
• Characteristics of AI Disruption
• Evolution of AI
• Historical Milestones
• Current State of AI (2025)
• AI Platform Shift
• Foundation Models
• Generative AI Revolution
• AI Beyond 2025

Chapter 3 Type of Disruptions Influenced by AI

• Overview
• Technological Disruption
• Real-time Use Cases
• Operational Disruption
• Real-time Use Cases
• Customer-Facing Disruption
• Real-time Use Cases
• Competitive Landscape Shift
• Real-time Use Cases

Chapter 4 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 (NLP)
• Edge and Cloud AI
• Rise of AI Marketplaces
• AI as a General-Purpose Technology
• Innovations in ML, NLP and Computer Vision
• AI's Transformative Impact on Product Development and R&D

Chapter 5 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
• Intelligent Decision Support System
• Process Automation
• Predictive Maintenance
• AI in Supply Chain and Logistics
• Types of Data in Supply Chain Management
• Challenges of AI in Supply Chain Management
• AI in ESG and Sustainable Operations Reporting

Chapter 6 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
• AI Impact on Digital Accessibility

Chapter 7 Competitive Disruptions

• Overview
• Major Challenges with AI-driven Competitive Disruption
• 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
• Role of Open-Source and AI Platforms
• 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 8 AI Impact on Major Industries

• Overview
• AI Impact on Major Industries
• 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 9 AI Disruption in Major Regions

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

Chapter 10 Case Studies of Disruptions

• Case Studies of Disruptions
• Healthcare
• Google DeepMind's AlphaFold
• Deep 6 AI Accelerating Clinical Trials
• AstraZeneca Revolutionizing Oncology with AI
• Roche Innovating Drug Discovery with AI
• Novartis Using AI in Drug Formulation
• Manufacturing and Supply Chain
• AI Transforms Amazon's Supply Chain
• Unilever Optimizing Supply Chain with AI
• Siemens Advancing Industrial Automation with AI
• General Electric Using AI to Optimize Energy Production
• Transportation and Logistics
• Tesla's Autonomous Vehicles
• Airbus Using AI for Aircraft Maintenance
• Ford Enhancing Driving Safety with AI
• Retail and E-commerce
• Zara Driving Retail with AI
• Stitch Fix Transforming the Future of Fashion Retail
• Salesforce Utilizing AI to Enhance Customer Relationship Management
• Procter & Gamble Incorporating AI in Consumer Goods Production
• Media and Entertainment
• Netflix Personalizing Entertainment with AI
• Baidu Facilitating Voice Recognition
• NVIDIA Utilizing AI to Enhance Gaming Graphics
• Finance and Banking
• American Express Using AI to Secure Transactions
• Other Sectors
• Blue River Technology Utilizing AI in Agriculture
• The Weather Company Utilizing AI to Predict Weather Patterns
• Cisco Using AI to Secure Networks
• Shell Using AI to Optimize Energy Resources
• Ukraine's AI-Powered Drone Strike Campaign

Chapter 11 Expert Opinions

• Quotes from Primary Respondents and Domain Experts
• How AI is Disrupting the Manufacturing and Logistics Industry
• How AI is Disrupting the Education Industry
• How AI is Disrupting the Productivity Software Industry
• How AI is Disrupting the Publishing Industry
• Interview Highlights
• Manufacturing and logistics
• Education and Edtech
• Productivity
• Publishing
• Emerging Narratives in the AI Disruption Debate
• From Displacement to Augmentation
• AI as a General-Purpose Technology
• Ethical AI
• Global AI Race
• Democratization vs. Centralization

Chapter 12 Future of AI Disruption

• Future of AI Disruption
• Forecasts and Predictions (2025-2030)
• Innovations
• Agentic AI
• Artificial General Intelligence (AGI)
• Neuromorphic AI

Chapter 13 Appendix

• Methodology
• References
• Abbreviations

List of Tables

• Table 1 : Comparison of AI Disruption with Non-AI Technology Disruption
• Table 2 : Snapshot of AI Use and their Company/Agency Name, 2025
• Table 3 : Scenario Planning Matrix, 2030
• Table 4 : AI Disruption vs. AI Transformation vs. AI Optimization
• Table 5 : Industry Impact
• Table 6 : SWOT Analysis: Startups vs. Incumbents
• Table 7 : Newly Funded AI Companies, by Country/Region, 2023
• Table 8 : Global Market for AI, by Region, Through 2030
• Table 9 : Abbreviations Used in This Report

List of Figures

• Figure 1 : AI Use Cases in Operations Management
• Figure 2 : Notable ML Models, by Country/Region, 2023
• Figure 3 : Relevance of Selected Responsible AI Risks for Organizations, by Region, 2025
• Figure 4 : Global Market Shares of AI, by Region, 2024