Infrastructure for AI Network Design and Architecture: Building self-learning networks for the age of intelligence (English Edition)
暫譯: 人工智慧網路設計與架構基礎建設：為智慧時代建構自學網路 (英文版)

Artificial intelligence is redefining the digital backbone of our world. As data demands explode and connectivity becomes intelligent, networks are no longer passive pipelines; rather, they are evolving into dynamic, self-learning ecosystems that sense, decide, and adapt in real time. This transformation marks the beginning of a new era where AI is not just an enabler but the foundation of modern organizational infrastructure, AI security, and automated collaboration.

The book guides the readers through how networks can think, heal, and evolve. It also includes real-world examples that reveal how AIOps, digital twins, and predictive analytics transform connectivity into a living, learning system, one that continuously optimizes performance, resilience, and trust.

By the end, readers will gain a clear framework for assessing AI readiness, implementing intelligent network strategies, and managing emerging risks with confidence. They will understand how to build and sustain adaptive, secure, and future-ready infrastructures, equipping themselves to lead their organizations through the AI-powered revolution already reshaping our connected world.

What you will learn

● Understand how AI transforms networks into intelligent ecosystems.

● Evolution of infrastructure from static systems to self-learning networks.

● Learn how AI reshapes organizational workflows and governance models.

● Discover how AIOps, digital twins, and automation redefine operational resilience.

● Examine AI's expanding role in cybersecurity and Zero Trust enforcement.

● Identify and mitigate emerging AI-driven network risks and vulnerabilities.

● Understand and reduce data debt to enhance AI performance.

● Step-by-step roadmap to implement and scale AI-ready networks.

Who this book is for

This book is designed for network architects, AI strategists, cybersecurity professionals, data engineers, and IT leaders navigating the union of artificial intelligence and infrastructure. It also serves CIOs, system integrators, and digital transformation executives seeking to modernize enterprise networks for intelligent, autonomous operations.

Table of Contents

Section I: AI's Foundational Impact

1. Understanding Your Network

2. AI's Impact on Modern Organizational Structure

3. AI-driven Transformation in Networks

4. AI and Decision-making, Collaboration, and Innovation

Section II: The Impact of AI on Organizational Security

5. AI in Cybersecurity

6. Implementing AI-driven Security

7. Managing Artificial Intelligence Risks

8. Understanding Data Debt

9. Reducing Data Debt with AI

10. Case Studies in Data Debt Reduction

Section III: Improving Your Organization's Network Structure

11. Evaluating Your Current Network for AI Readiness

12. Designing AI-optimized Networks

13. Step-by-step Implementation Plan for AI Networks

14. Sustaining and Scaling AI Initiatives

15. Conclusion

APPENDIX A: AI Integration Checklist

APPENDIX B: Network Build and Enablement

APPENDIX C: History of AI HDMI

APPENDIX D: References