You're reading from The AI Optimization Playbook Drive business success with proven AI strategies, best practices, and responsible innovation

Product type Paperback

Published in Nov 2025

Publisher Packt

ISBN-13 9781806115112

Length 382 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Artificial Intelligence

Authors (4):

Dr. Chun Schiros

Dr. Usha Jagannathan

Supreet Kaur

Rajdeep Arora

View More author details

Table of Contents (25) Chapters

Preface

1. Part 1: Laying the Groundwork for AI Success

2. Understanding the Perils of AI Products FREE CHAPTER

3. Building the Enterprise AI Strategy

4. Part 2:Aligning Projects with Business Impact

5. Selecting High-Impact AI Projects

6. Beyond the Build: Gaining Leadership Support for AI Initiatives

7. Building an AI Proof of Concept and Measuring Your Solution

8. Part 3: Deploying and Proving ML Value

9. Beyond Accuracy: A Guide to Defining Metrics for Adoption

10. From Model to Market: Operationalizing ML Systems

11. From Metrics to Measurement: Experimentation and Causal Inference

12. Part 4: Emerging Topics: Generative AI and AI Agents

13. Generative AI in the Enterprise: Unlocking New Opportunities

14. Understanding GenAI Operations

15. AI Agents Explained

16. Part 5: Responsible AI and Governance

17. Introduction to Responsible AI

18. Implementing RAI Frameworks, Metrics, and Best Practices

19. Building Trustworthy LLMs and Generative AI

20. Regulatory and Legal Frameworks for Responsible AI

21. The Future of AI Optimization: Trends, Vision, and Responsible Implementation

22. Unlock Your Exclusive Benefits

23. Index

24. Other Books You May Enjoy

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Implementing RAI Frameworks, Metrics, and Best Practices

The preceding chapter laid out the essential groundwork for understanding the principles and significance of Responsible AI (RAI). However, translating these guiding ideals into tangible practice requires a structured and deliberate approach. This chapter serves as a practical roadmap for operationalizing RAI, moving beyond theoretical discussions to provide actionable strategies and tools that organizations can implement throughout the AI life cycle. Effectively embedding ethical considerations is not a passive aspiration but an active process that demands the establishment of clear frameworks, the application of relevant metrics, and the adoption of proven best practices.

This chapter will guide you through the essential components of an ethical AI implementation strategy. We will begin by exploring various frameworks for ethical AI governance, such as the establishment of a dedicated RAI governance committee and the utilization...