AI顛覆：全球市場概覽

本報告從技術、營運、客戶服務、競爭環境等多個角度全面分析了AI對產業、組織和社會的影響。

本報告探討了AI原生架構的多個方面，包括平台轉型、生成式AI、自動化系統、機器人技術和資料基礎設施，並分析如何透過智慧自動化和機器學習（ML）最佳化重塑內部工作流程、供應鏈、物流和決策。報告也探討了AI在使用者體驗、個人化引擎、預測服務、語音介面和AI代理方面的應用。

本報告聚焦於全球受AI影響最大的產業，展示醫療保健、金融與銀行、製造與供應鏈、零售與電子商務、教育與教育科技、運輸與物流、媒體與娛樂以及其他新興領域的實際應用案例和趨勢分析。報告還涵蓋區域格局，識別AI領域的領導者和落後者。報告中還描繪了北美、亞太、歐洲和其他地區的成熟度、投資趨勢、人才生態系統和政策環境。

目錄

第1章 執行摘要

第2章 市場概述

• AI顛覆性創新概述
• AI帶來的顛覆性變化的特點
• AI的演變
• 歷史里程碑
• AI現況（2025年）
• AI平台遷移
• 基礎模型
• 生成式AI革命
• 2025年及以後的AI

第3章 AI造成的顛覆類型

• 概述
• 技術創新
• 即時用例
• 營運中斷
• 即時用例
• 客戶互動的顛覆性變化
• 即時用例
• 競爭格局的變化
• 即時用例

第4章 技術顛覆

• 概述
• 技術創新的主要趨勢
• AI主導的技術顛覆的基石
• 高階機器學習和深度學習
• AI世代
• 自動化和機器人技術
• 預測分析
• 自然語言處理（NLP）
• 邊緣AI和雲端AI
• AI市場的崛起
• AI作為通用技術
• 機器學習、自然語言處理和電腦視覺領域的創新
• AI對產品開發和研發的變革性影響

第5章 營運中斷

• 概述
• AI將如何顛覆營運的關鍵趨勢
• AI驅動的營運中斷的組成部分
• 超自動化與智慧工作流程編配
• 預測分析與規範分析
• AI驅動的人類勞動力
• 數位雙胞胎與即時監控
• 動態資源分配與最佳化
• 智慧決策支援系統
• 流程自動化
• 預測性維護
• 供應鏈和物流中的AI
• 供應鏈管理中的資料類型
• 供應鏈管理的AI挑戰
• ESG 和永續商業報告中的AI

第6章 客戶服務中斷

• 概述
• AI主導的客戶互動顛覆性創新的主要趨勢
• AI主導的客戶互動中的顛覆性創新建構模組
• 對話式AI和虛擬助手
• 視覺搜尋和推薦系統
• 預測客戶智慧
• 辨識情緒和感受
• AI驅動的個人化
• 使用行為AI進行體驗設計
• AR/VR商務中的身臨其境型AI
• AI如何影響數位無障礙

第7章 競爭擾亂

• 概述
• AI顛覆競爭的關鍵挑戰
• AI主導的競爭顛覆的主要趨勢
• AI主導的競爭顛覆的組成部分
• AI原生經營模式
• 獨特的資料和網路效應
• 透過自動化實現成本領先
• 平台遊戲和生態系統收益
• 開放原始碼和AI平台的作用
• AI工具降低了進入門檻
• Start-Ups與成熟公司
• AI作為併購和估值中的策略資產
• 民主化創新
• 現有企業面臨的市場變化與挑戰

第8章 AI對重點產業的影響

• 概述
• AI對重點產業的影響
• 衛生保健
• 金融
• 製造和供應鏈
• 零售與電子商務
• 教育與教育技術
• 運輸/物流
• 媒體與娛樂
• 其他（政府部門、基礎建設、法律與合規）

第9章 AI驅動重點區域顛覆性變革

• 概述
• 北美洲
• 歐洲
• 亞太地區
• 世界其他地區

第10章 顛覆案例研究

• 顛覆案例研究
• 衛生保健
• Google DeepMind 的AlphaFold
• 利用 Deep 6 AI 加速臨床試驗
• AstraZeneca利用AI徹底改變癌症治療
• Roche利用AI徹底改變藥物研發
• Novartis的AI藥物開發
• 製造和供應鏈
• 亞馬遜供應鏈中的AI轉型
• Unilever的供應鏈最佳化
• Siemens推進工業自動化
• 通用電氣生產最佳化
• 運輸/物流
• Tesla自動駕駛汽車
• Airbus在飛機維修中使用AI
• Ford提升駕駛安全性
• 零售與電子商務
• Zara 的AI驅動零售策略
• Stitch Fix 改變時尚零售業的未來
• 利用 Salesforce 協助客戶關係管理（CRM）
• Procter & Gamble將AI引進消費品製造
• 媒體與娛樂
• Netflix 的個人化娛樂
• Baidu推廣語音辨識
• NVIDIA 利用 AI 改善遊戲圖形
• 金融與銀行
• American Express利用AI增強交易安全性
• 其他領域
• Blue River Technology在農業領域應用AI
• The Weather Company 的天氣模式預報
• Cisco利用AI實現網路安全
• Shell的能源資源最佳化
• 烏克蘭的AI無人機襲擊宣傳活動

第11章 專家意見

• 主要受訪者和主題專家的引言
• AI將如何顛覆製造業和物流業
• AI將如何顛覆教育產業
• AI如何顛覆生產力軟體產業
• AI將如何顛覆出版業
• 訪談重點
• 製造和物流
• 教育與教育技術
• 生產力
• 出版
• AI驅動的顛覆性變革辯論中的新敘事
• 從替代到增強
• AI作為通用技術
• 道德AI
• 全球AI競賽
• 民主化與集權化

第12章 AI顛覆的未來

• AI顛覆的未來
• 預測
• 創新
• 代理AI
• 通用AI（AGI）
• 神經型態AI

第13章 附錄

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