AI 사용 사례 분석 : 세계 전망

This report provides a comprehensive analysis of artificial intelligence (AI) use cases across technologies, industries, and organizational contexts. The study presents detailed qualitative insights, focusing on how AI applications are evolving, scaling, and creating business value. The scope covers AI use cases across key technology domains, major industry verticals, and startup ecosystems, offering structured visibility into adoption patterns, maturity levels, and real-world implementation scenarios.

The report evaluates AI use cases in relation to technology readiness, value creation potential, operational impact, and adoption barriers. It also examines emerging AI technologies, workforce and skill implications, regulatory and ethical considerations, and investment trends shaping future use cases. The study concludes with a forward-looking perspective on how AI use cases are expected to evolve over the next few years, supported by a clear and defined target audience.

Report Scope

This report provides an in-depth examination of the current and future landscape of AI applications. Its multi-dimensional analysis addresses both the technological advances driving AI and the many ways these advances are being leveraged across various industries and by emerging businesses.

• The report provides an analysis of the latest and emerging AI technologies, such as genAI, edge AI, eXplainable AI (XAI), QML, large language models (LLMs), agentic AI, reinforcement learning, and others (federated AI and neuromorphic computing), and their significance in the evolving AI ecosystem. The report also examines AI adoption and maturity stages across industries, highlighting how organizations progress from experimentation and pilot projects to scaled deployment, operational integration, and value realization.
• The AI use case analysis by technology, where practical applications of AI are explored across a spectrum of underlying technologies, including robotics, cybersecurity, digital twins, XR, AR, VR, blockchain, IoT, and edge computing, is explained in detail. It presents the problems that AI solves within each technological context, the solutions implemented, and the resulting outcomes.
• The detailed analysis of AI use cases by industry covers healthcare, finance and banking, logistics, retail and e-commerce, education and edtech, media and entertainment, telecom, oil and gas, automotive, manufacturing, and others (agriculture, aerospace and defense, construction and mining).
• It also includes a section on AI use case analysis for startups. It examines how companies are deploying AI for operational efficiency, product innovation, compliance, sales and marketing, and talent management.
• The study offers a future perspective on AI use cases, analyzing how AI applications will continue to evolve and reshape industries and technologies, emphasizing areas such as robotics and cybersecurity.

Report Includes

• In-depth analysis of emerging artificial intelligence (AI) technologies and their applications across various industries
• Review of the latest AI advances, such as GenAI, edge AI and quantum machine learning (QML), to analyze specific AI use cases across a range of technologies, describing the problems addressed, the solutions offered, and the tangible outcomes
• A structured analysis of global AI use cases across key technologies, industries, and organizational contexts
• Analysis of AI use cases by technology, including machine learning, computer vision, natural language processing, generative AI, robotics, digital twins, and edge computing
• Analysis of AI use cases by industry, covering healthcare, finance, manufacturing, retail, logistics, telecommunications, government, and other sectors
• Review of AI use cases among startups, including operational, product development, compliance, sales and marketing, and monetization applications
• Insights into emerging AI technologies and their impact on future use case development
• Examination of AI adoption patterns, maturity levels, and real-world implementation scenarios
• Insights into future AI Use Cases in the coming years, considering technological progress and shifting industry demands

Table of Contents

Chapter 1 Executive Summary

• Study Goals and Objectives
• Scope of Report
• Reasons for Doing the Study
• Market Summary
• Technology-Centric View
• Industry-Centric View
• Upcoming Trends and Developments
• Conclusion

Chapter 2 Emerging Technologies in AI

• Overview of AI
• Types of AI
• AI Adoption and Maturity Stages
• Emerging Technologies in AI
• GenAI
• Multimodal AI
• Edge AI
• XAI
• Quantum Machine Learning (QML)
• LLMs
• Agentic AI
• Reinforcement Learning
• Others

Chapter 3 AI Use Case Analysis by Technologies

• Overview
• Key Takeaways
• Robotics
• Applications for AI in Robotics
• Use Cases for AI in Robotics
• Cybersecurity
• Use Cases for AI in Cybersecurity
• Digital Twin
• Key Applications for AI in Digital Twin
• Use Cases for AI in Digital Twin
• XR, Augmented Reality (AR) and Virtual Reality (VR)
• Key Applications for AI in XR, AR and VR
• Use Cases for AI in XR, AR and VR
• Blockchain
• Use Cases for AI in Blockchain
• Internet of Things (IoT)
• Applications for AI in IoT
• Use Cases for AI in IoT
• Edge Computing
• Use Cases for AI in Edge Computing
• Other Technologies
• Use Cases for AI in Other Technologies

Chapter 4 AI Use Case Analysis by Industries

• Overview
• Key Takeaways
• Healthcare
• Use Cases for AI in Healthcare
• Finance and Banking
• Use Cases for AI in Finance and Banking
• Logistics
• Use Cases for AI in Logistics
• Retail and E-Commerce
• Use Cases for AI in Retail and E-Commerce
• Education and EdTech
• Use Cases for AI in Education and EdTech
• Media and Entertainment
• Use Cases for AI in Media and Entertainment
• Telecommunications
• Use Cases for AI in Telecommunication
• Oil and Gas
• Use Cases for AI in Oil and Gas
• Automotive
• Use Cases for AI in Automotive
• Manufacturing
• Use Cases for AI in Manufacturing
• Other Industries
• Use Cases for AI in Other Industries

Chapter 5 AI Use Case Analysis for Startups

• Overview
• Key Takeaways
• Operational Use Cases
• Use Case 1: AI-Powered Employee Research and Knowledge Management
• Use Case 2: AI-Powered Customer Query Resolution at Urban Company
• Use Case 3: AI-Powered Paperwork Reduction for Mobile Dental Clinics atVirtual Dental Care
• Product Development and Innovation Use Cases
• Use Case 1: AI-Driven Personalization and Inventory Optimization in Fashionat Stitch Fix
• Use Case 2: Advancing NLP with OpenAI's GPT Models
• Infrastructure and Compliance Use Cases
• Use Case 1: AI for Global Climate Pledge Accountability
• Use Case 2: AI for Smart Aging Cities in Japan
• Sales and Marketing Use Cases
• Use Case 1: Hyper-Personalized Outreach at Scale with SuperAGI
• Use Case 2: AI-Powered Conversational Intelligence for Sales Coaching
• Human Resources (HR) and Talent Management Use Cases
• Use Case 1: AI-Driven Recruitment Transformation with JobGet
• Use Case 2: AI in Talent Management at CrewBloom
• Scaling and Go-to-Market Challenges

Chapter 6 Future of AI Use Cases

• Evolving AI Use Cases, by Technological Advances
• Key Takeaways
• Future of AI Use Cases in Robotics
• Future of AI Use Cases in Cyber Security
• Future of AI Use Cases in XR, AR and VR
• Future of AI Use Cases in Blockchain
• Future of AI Use Cases in Edge Computing

Chapter 7 Appendix

• Methodology
• Abbreviations