AI Adoption: A Global Perspective
| 出版社 | BCC Research |
| 出版年月 | 2025年8月 |
| ページ数 | 92 |
| 価格タイプ | シングルユーザライセンス |
| 価格 | USD 4,650 |
| 種別 | 英文調査報告書 |
Report Scope
This report aims to provide a thorough and detailed analysis of the current and future state of AI applications. Its scope includes a multifaceted review, covering both the technological progress driving AI and the various ways these developments are being used across different industries and by emerging businesses.
The following parameters define the scope of the report:
– The report will explore AI hardware, software and service solutions and provide a detailed overview of key developments and innovations. It will define each solution and highlight its significance in the evolving AI ecosystem.
– The report covers a descriptive analysis of AI adoption across various end-use industries. To provide deeper insight, it will include case studies at the application level within these sectors.
– The study highlights AI adoption trends across North America, Europe, Asia-Pacific, South America and the Middle East and Africa.
– The report identifies major challenges affecting AI implementation based on case study analyses for business process improvement and product development.
It will also outline key government guidelines, regulations and standards such as the EU AI Act, which are driving the rapid global AI adoption.
Report Includes
– A general outlook of the artificial intelligence (AI) adoption scenarios across industries by applications, with key companies’ developments
– Trends in the AI adoption in hardware, software and services solutions, along with major technological innovations, current state of AI and historical milestones
– A look at the regulatory landscape featuring key international and regional regulations and standards for AI adoption
– Review of the impact of ongoing U.S. tariffs on global trade and investment, and challenges associated with AI infrastructure development and global supply chains
– Case studies on AI implementation to improve business processes and for product or service innovation
– Insights into future AI adoption plans of key companies across different sectors, and projections and growth forecasts through 2030
– Role of AI adoption in the global cybersecurity market landscape
– Expert quotes on AI adoption from primary respondents
Table of Contents
Table of Contents
Chapter 1 Executive Summary
Study Goals and Objectives
Scope of Report
Market Summary
Adoption Viewpoint
Future Trends and Developments
Industry Analysis
Regional Insights
Conclusion
Chapter 2 Market Overview
AI Adoption Overview
Evolution of AI Adoption
Key Historical Milestones
Current State of AI
Key Technology Models
Regulations and Standards for AI Adoption
European Union
U.S.
China
Japan
South Korea
India
Key Barriers for AI Adoption
Lack of Knowledge
Data Privacy
Integration Challenges
Impact of U.S. Tariff Laws on AI Adoption
Chapter 3 AI Adoption in Hardware Solutions
Key Takeaways
Adoption Analysis
AI Processors and Accelerators
Memory
Current and Future Innovations of Key AI Hardware Providers
Chapter 4 AI Adoption in Software Solutions
Key Takeaways
Adoption Analysis
AI Platforms
Current and Future Plans of Key AI Software Providers
Chapter 5 AI Adoption in Service Solutions
Key Takeaways
Adoption Analysis by Service Type
Professional Services
Managed Services
Current and Future Plans for Key Service Providers
Chapter 6 AI Adoption by Industries
Key Takeaways
Adoption Analysis
Healthcare
Banking, Financial Services and Insurance
Logistics and Supply Chain
Retail and eCommerce
Education and EdTech
Media and Entertainment
Telecommunication
Others (Agriculture, Automotive, Manufacturing, Energy and Utilities and More)
Chapter 7 AI Adoption Trends by Regions
Key Takeaways
Adoption Analysis
North America
Europe
Asia-Pacific
Latin America
Middle East and Africa
Chapter 8 Case Studies on AI Adoption
AI Implementation to Improve Business Processes
Case Study 1: General Electric’s Deployment of Predix Platform
Case Study 2: General Motors’ Vehicle Inspection Process Efficiency
Case Study 3: British Columbia Investment Management Corp. Implemented AI to Optimize Business Procedures
Case Study 4: AI for Operational Efficiency in Oil and Gas at BP
Case Study 5: Delta Airlines Improved Operational Efficiency Using AI
Case Study 6: Bank of America’s Adoption of AI Tool Erica
Case Study 7: Zodiac Maritime’s AI-Enhanced Collision Prediction System
Case Study 8: Deutsche Telekom Improving Operational Efficacy with AI
Case Study 9: Port of Rotterdam’s Smart Container Management
Case Study 10: Fox Corp. Implemented Amazon’s AI-Driven Tools
Case Study 11: Kroger’s Intelligent Shelving and Pricing Optimization
AI Implementation for Product/Service Innovation
Case Study 1: AI-Powered Electronic Health Records Optimization
Case Study 2: Vodafone’s AI-Driven Customer Service
Case Study 3: Predictive Analytics in Retail
Case Study 4: Mastercard Optimized Payment Processing with AI
Case Study 5: Siemens Digital Industries Software Developed an AI Solution
Case Study 6: Collaboration Between the University of Rochester Medical Center and Butterfly Network
Case Study 7: OSF HealthCare’s AI-Powered Virtual Assistant
Case Study 8: Valley Bank’s Anti-Money Laundering
Case Study 9: AI-Powered Tool for European School of Management and Business
Case Study 10: AT&T Transformed Customer Service with AI
Case Study 11: Bolton College’s AI-Powered Video Creation Platform
Case Study 12: Sephora’s Innovation in Beauty Retail
Chapter 9 Future of AI Adoption
Forecasts and Predictions
Future of AI Adoption in Key Industries
Healthcare
Banking, Financial Services and Insurance
Logistics and Supply Chain
Media and Entertainment
Retail and E-Commerce
Chapter 10 Appendix
Methodology
References
Abbreviations
List of Tables
List of Tables
Table 1 : Key Historical AI Milestones, 2000-2016
Table 2 : Types of AI Technology, Primary Function and Applications
Table 3 : AI Services Provided by IBM
Table 4 : Value of AI Implementation across BFSI
Table 5 : AI Applications in Media and Entertainment
Table 6 : AI Applications in Agriculture
Table 7 : Phases and Milestones: The AI Adoption Roadmap
Table 8 : Agentic AI in BFSI
Table 9 : Agentic AI in Retail and eCommerce
Table 10 : Abbreviations Used in This Report
List of Figures
List of Figures
Figure 1 : Global Corporate Investments in AI, 2019–2024
Figure 2 : Notable AI Models in the U.S., China and Europe, 2024
Figure 3 : Key Barriers to AI Adoption, 2024
Figure 4 : U.S. AI-Directed Technology Imports, November 2024 to March 2025
Figure 5 : U.S. Survey of GenAI Adoption at Work and at Home, August 2024
Figure 6 : Organizations Using AI and GenAI in at Least One Business Function, 2020–2024
Figure 7 : Number of AI Medical Devices Approved by the FDA, 2018–2023
Figure 8 : Share of Firms That Have Adopted AI, by Employee Size, in the U.S., 2024
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