人工智慧顛覆：全球視角

本報告對全球主要產業和地區人工智慧驅動的顛覆性變革的現狀和未來發展趨勢進行了前沿分析。

該報告重點闡述了人工智慧對多個行業的影響，並說明了其背後的技術創新，整合了案例研究、政府數據以及按平台分類的人工智慧發展資訊，從而全面而戰略性地展現了人工智慧對全球的顛覆性觀點。

報告內容

• 對人工智慧主導的關鍵產業和全球區域顛覆性影響進行全面、即時的分析
• 重點介紹人工智慧在多個產業中引發的重大變革，並概述其背後的技術創新。
• 一種整合案例研究、政府數據和平台特定人工智慧開發資訊的策略性和整體性觀點
• 了解人工智慧如何改變技術基礎設施、業務結構、客戶觸點和競爭環境
• 對已利用人工智慧進行平台轉型的公司進行即時案例分析，並探討其向人工智慧原生平台過渡的現狀。
• 整合領先的人工智慧管治和研究機構的框架和出版物
• 識別區域領先者和落後者
• 來自業界專家和思想領袖的真知灼見，探討人工智慧將如何改變商業模式。

目錄

第1章執行摘要

• 調查目標和目的
• 進行這項調查的原因
• 調查範圍
• 市場摘要
• 顛覆性觀點
• 未來趨勢與發展
• 產業分析
• 區域洞察
• 結論

第2章 市場概覽

• 人工智慧顛覆性影響概述
• 季度回顧：人工智慧轉型的主要亮點
• AI市場脈搏儀表板
• 領先的人工智慧顛覆性Start-Ups
• 區域政策的變化
• 雲端服務和託管市場趨勢
• 人工智慧的演變
• 歷史里程碑
• 人工智慧現況（2025）
• 人工智慧平台轉型
• 基礎模型
• 生成式人工智慧革命
• 2025年及以後的人工智慧

第3章：人工智慧是機遇，而非威脅

• 概述
• 新工作湧現/傳統工作流失
• 衛生保健
• 傳統工作正在消失。
• 創造新的就業機會
• 金融與銀行
• 傳統工作正在消失。
• 創造新的就業機會
• 製造和供應鏈
• 傳統工作正在消失。
• 創造新的就業機會
• 零售與電子商務
• 傳統工作正在消失。
• 創造新的就業機會
• 教育/教育科技
• 傳統工作正在消失。
• 創造新的就業機會
• 運輸/物流
• 傳統工作正在消失。
• 創造新的就業機會
• 媒體與娛樂
• 傳統工作正在消失。
• 創造新的就業機會

第4章：人工智慧引發的顛覆類型

• 概述
• 科技顛覆
• 營運中斷
• 面向客戶的干擾
• 競爭環境的變化

第5章：技術顛覆

• 概述
• 主要趨勢
• 成分
• 高階機器學習和深度學習
• 人工智慧世代
• 自動化和機器人技術
• 預測分析
• 自然語言處理
• 邊緣人工智慧和雲端人工智慧
• 人工智慧作為一種通用技術
• 人工智慧對產品開發和研發的變革性影響

第6章：營運中斷

• 概述
• 主要趨勢
• 成分
• 超自動化與智慧工作流程編配
• 預測分析與規範分析
• 人工智慧驅動的人力勞動力
• 數位雙胞胎和即時監測
• 動態資源分配與最佳化
• 流程自動化
• 人工智慧在供應鏈和物流的應用
• 供應鏈管理的人工智慧挑戰
• 人工智慧在環境、社會及治理（ESG）和永續商業報告中的應用

第7章：客戶服務中斷

• 概述
• 主要趨勢
• 成分
• 對話式人工智慧和虛擬助手
• 視覺搜尋和推薦系統
• 預測性客戶智慧
• 辨識情緒和感受
• 人工智慧驅動的個人化
• 利用行為人工智慧進行體驗設計
• 身臨其境型人工智慧在擴增實境/虛擬實境商務中的應用

第8章 競爭顛覆

• 概述
• 主要趨勢
• 成分
• 人工智慧原生經營模式
• 專有數據和網路效應
• 透過自動化實現成本領先
• 平台策略和生態系統貨幣化
• 人工智慧工具降低了准入門檻
• Start-Ups與成熟公司
• 人工智慧作為併購和企業估值中的策略資產
• 創新民主化
• 市場結構的變化以及現有公司面臨的挑戰

第9章：人工智慧對關鍵產業的影響

• 概述
• 衛生保健
• 金融
• 製造和供應鏈
• 零售與電子商務
• 教育/教育科技
• 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10章：人工智慧對關鍵地區的顛覆性影響

• 概述
• 北美洲
• 歐洲
• 亞太地區
• 世界其他地區

第11章：人工智慧顛覆性案例研究

• 衛生保健
• 製造和供應鏈
• 運輸/物流
• 零售與電子商務
• 媒體與娛樂

第12章 專家意見

• 來自主要受訪者和主題專家的引述
• 人工智慧如何顛覆化學工業
• 人工智慧將如何顛覆科技產業
• 人工智慧將如何顛覆醫療保健產業
• 人工智慧將如何顛覆製造業
• 關於人工智慧顛覆性創新的新辯論
• Anthropic
• Meta
• Apple
• Salesforce
• 亞馬遜（AWS、機器人）
• Microsoft

第13章：人工智慧顛覆性變革的未來

• 未來展望
• 預測與展望
• 技術創新
• 檢索增強生成（RAG）和知識接地
• 參數高效的微調
• 客製化人工智慧加速器和機架級硬體
• 邊緣人工智慧/設備端人工智慧
• 智慧體人工智慧
• 通用人工智慧
• 神經型態人工智慧

第14章附錄

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