Summary
Report Scope
This report analyzes how AI disrupts industries 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, talent ecosystems and policy environment 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.
Report Includes
- An overview of AI-driven disruptions across global industries and regions
- Information on technological and operational disruption, focusing on changes in core operations, workflows, and platforms
- Discussion of how AI is transforming job functions and skill demand across industries
- Analysis of competitive disruption, including platform shifts and lowering of market entry barriers
- Coverage of disruption in customer experience, personalization, and customer support
- Case studies and real-time use cases of companies that have undergone disruption due to AI adoption
- Insights and perspectives from industry experts, thought leaders, and primary respondents
ページTOPに戻る
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 (Q4 2025): Key AI Disruption Highlights
AI Market Pulse Dashboard
Supply Chain Risks
Compute and GPU scarcity
Semiconductor Geopolitics and Export Controls
Component Shortages and Price Inflation
Energy and Data Center Capacity Constraints
Cloud and Platform Outages
Data Integrity and Cross-Border Data Risk
Logistics, Shipping and Port Volatility
Talent and Services Supply
Key AI Disruptive Startups
Regulatory Enforcement
U.S.
Europe
China
India
Cloud and Data Center Constraints
AI Beyond 2025
2030 Scenario Planning Matrix
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
Human-in-the-Loop Persistence
AI Productivity Dividend versus Headcount Reduction
Unionization and Legal Risk
Legal risk 2025
Chapter 4 Types of Disruptions Influenced by AI
Overview
Technological Disruption
Operational Disruption
Customer-Facing Disruption
Competitive Landscape Shift
Severity Mapping (Incremental versus existential disruption)
Technological Disruption
Operational Disruption
Customer-Facing Disruption
Competitive Landscape Shifts
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’s Transformative Impact on Product Development and R&D
Agentic AI: Where It Works versus Breaks
Where Agentic AI Works
Where Agentic AI Breaks
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
Cost of Intelligence: Model Training and Scaling
AI in Sustainable Operations
Chapter 7 Customer-Facing Disruptions
Overview
Key Trends in AI-Driven Customer-Facing Disruptions
Shifts in Industry Concentration Due to AI Scale Effects
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
Regulatory Scrutiny on Consumer AI
Europe
The U.S.
Asia-Pacific
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
Market Shifts and Incumbent Challenges
Role of Open-Source and AI Platforms
Chapter 9 AI Impact on Major Industries
Overview
Chemicals and Materials
Healthcare and Life Sciences
Technology and Software
Manufacturing and Industrial
Energy, Utilities and Climate Tech
Education and Edtech
Transportation and Logistics
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 Snapshots – AI Deployments
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
Regulator and Auditor Views
Chapter 13 Future of AI Disruption
Future of AI Disruption
Forecasts and Predictions (2025–2030)
Expected Industry Disruption Hotspots 2026
AI Disruption Hotspots in 2026
AI-Induced Market Crashes
Innovations
Retrieval-Augmented Generation (RAG) and Knowledge-Grounding
Parameter-Efficient Fine-Tuning
Custom AI Accelerators and Rack-Scale Hardware
Edge and On-device AI
Artificial General Intelligence (AGI)
Neuromorphic AI
AI in Climate Intelligence and Green Transition
Bio-AI and Neuro-Symbolic Systems
Macroeconomic Sensitivity Scenarios
Scenario 1: Productivity Surge and Disinflationary Shock
Scenario 2: Labor Displacement and Demand Drag
Scenario 3: Capital Concentration and AI-Led Inequality
Scenario 4: Financial Volatility and Policy Lag
Chapter 14 Appendix
Methodology
References
Abbreviations
ページTOPに戻る
List of Tables/Graphs
List of Tables
Table 1 : KPIs Quarter 4, 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 : Policy-Relevant Severity Matrix, Q4 2025
Table 10 : SWOT Analysis: Startups vs. Incumbents
Table 11 : Challenges that Incumbents Must Confront
Table 12 : AI Deployments, Q4 2025
Table 13 : Global Market for AI Component Infrastructure, by End Use Industry, Through 2030
Table 14 : Abbreviations Used in This Report