AIディスラプションの世界概観　2025年10月

本レポートは、主要業界および世界各地におけるAIによる現在および将来のディスラプション（創造的破壊）に関する最新の分析を提供します。複数の業界におけるAIによるディスラプションに焦点を当て、その背景にあるイノベーションを解説するとともに、ケーススタディ、政府データ、プラットフォーム固有のAI開発を統合することで、世界的なAIによるディスラプションに関する包括的かつ戦略的な視点を提供します。

本レポートは、AIの影響を最も受けている世界的セクターに焦点を当て、ヘルスケア、金融・銀行、製造・サプライチェーン、小売・eコマース、教育・エドテック、運輸・物流、メディア・エンターテインメント、その他の新興セクターといった分野におけるトレンド分析を行っています。また、AIの先進企業と後発企業を特定するための地域別の状況も示しています。北米、アジア太平洋、欧州、そしてその他の地域（RoW）におけるAIの成熟度、投資フロー、人材エコシステム、政策環境をマッピングしています。

本レポートでは、AIによるディスラプションを、以下の複数の相互に関連する側面から評価しています。

• AIの統合に伴う時価総額の変動、ならびに認知・手作業セクターにおける雇用創出と雇用喪失。
• セクターにおけるディスラプションを促進する基盤モデルのブレークスルー。
• データリッチ企業を取り巻くM&A活動とエコシステム統合の変化。
• ガバナンス・フレームワーク、そしてデータ主権とアカウンタビリティへの影響。

Report Highlights

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 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

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.

Table of Contents

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

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

List of Figures
Figure 1 : AI Use Cases in Operations Management

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