AI Adoption Global Perspective Analysis Report 2025 | Evolution of AI Adoption, Key Historical Milestones, Current State of AI, Key Technology Models, Regulations and Standards - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "AI Adoption: A Global Perspective" report has been added to ResearchAndMarkets.com's offering.

This report provides a detailed analysis of AI adoption across various industries. It will examine the use of AI in hardware, software and services, along with key product innovations and investments. The study will also highlight AI adoption trends in different regions.

AI is being rapidly adopted across industries. Following generative AI (GenAI), the emergence of agentic AI is expected to accelerate market growth. AI is currently implemented at a functional level and used as virtual assistants, chatbots and to streamline software development. However, there is significant potential for its integration at various organizational levels. This can be achieved through the adoption of agentic AI, which can automate processes and make decisions independently with ease. Advances in large language models (LLMs) combined with 6G technology will enable faster and more accurate realtime data processing.

AI technology has significantly impacted various industries, including banking, financial services and insurance (BFSI); healthcare; media and entertainment; logistics; retail; telecom and education, leading to advances and innovations. The adoption of AI technologies is driven by the continual R&D efforts of tech giants and the increasing demand for advanced solutions in different sectors.

In terms of regional adoption, North America, particularly the U.S., is leading the market due to huge investments and innovations. Canada, Brazil, India, Japan, South Korea, Saudi Arabia and South Africa are some of the emerging countries adopting AI. Along with implementation, these countries are working on various strategies, such as investments in R&D and boosting start-ups, to increase the broader acceptance of AI.

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.

The 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

Key Topics Covered:

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

For more information about this report visit https://www.researchandmarkets.com/r/3wj55n

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