AIのユースケース分析：世界展望

本レポートは、テクノロジー、業界、組織的コンテキストを横断した人工知能（AI）のユースケースを包括的に分析しています。本調査では、AIアプリケーションがどのように進化、拡張し、ビジネス価値を創出しているかに焦点を当て、詳細な定性的な洞察を提供しています。主要なテクノロジー領域、主要産業分野、スタートアップエコシステムにおけるAIユースケースを網羅し、導入パターン、成熟度、そして実際の導入シナリオを体系的に可視化しています。

本レポートでは、AIユースケースを、テクノロジーの成熟度、価値創造の可能性、運用への影響、導入障壁の観点から評価しています。また、新興AIテクノロジー、人材とスキルへの影響、規制および倫理上の考慮事項、そして将来のユースケースを形作る投資動向についても考察しています。最後に、明確かつ明確な対象読者層に基づき、今後数年間のAIユースケースの進化に関する将来予測を提示しています。

レポートの内容

• 新興の人工知能（AI）技術と様々な業界におけるその応用に関する詳細な分析
• GenAI、エッジAI、量子機械学習（QML）などの最新のAI技術をレビューし、様々な技術における具体的なAIユースケースを分析し、対処すべき問題、提供されるソリューション、そして具体的な成果を説明します。
• 主要な技術、業界、組織のコンテキストにおけるグローバルAIユースケースの構造化分析
• 機械学習、コンピュータービジョン、自然言語処理、生成AI、ロボティクス、デジタルツイン、エッジコンピューティングなど、技術別のAIユースケース分析
• 医療、金融、製造、小売、物流、通信、政府機関など、業界別のAIユースケース分析
• 運用、製品開発、コンプライアンス、営業・マーケティング、収益化アプリケーションなど、スタートアップ企業のAIユースケースレビュー
• 新興AI技術とそれらが将来のユースケース開発に与える影響に関する洞察
• AIの採用パターン、成熟度、そして実際の導入シナリオの検討
• 技術動向を考慮した、今後数年間のAIユースケースに関する洞察進歩と変化する業界の需要

Report Highlights

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 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

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

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