AI 디스럽션 : 세계의 개요

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 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

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