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The AI Optimization Playbook
The AI Optimization Playbook

The AI Optimization Playbook: Drive business success with proven AI strategies, best practices, and responsible innovation

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Profile Icon Dr. Chun Schiros Profile Icon Supreet Kaur Profile Icon Rajdeep Arora Profile Icon Dr. Usha Jagannathan
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€24.29 €26.99
eBook Nov 2025 382 pages 1st Edition
eBook
€24.29 €26.99
Paperback
€33.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Dr. Chun Schiros Profile Icon Supreet Kaur Profile Icon Rajdeep Arora Profile Icon Dr. Usha Jagannathan
Arrow right icon
€24.29 €26.99
eBook Nov 2025 382 pages 1st Edition
eBook
€24.29 €26.99
Paperback
€33.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
€24.29 €26.99
Paperback
€33.99
Subscription
Free Trial
Renews at $19.99p/m

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The AI Optimization Playbook

Laying the Groundwork for AI Success

In Part 1 of this book, we will establish the strategic foundation necessary for any successful AI initiative. We will begin by examining why most AI projects fail, showing that these are overwhelmingly strategy, execution, and integration failures, not technology failures. We will analyze common pitfalls such as misaligned goals (chasing technical “surrogate metrics” instead of business value), siloed development, weak data foundations, and a misunderstanding of AI’s iterative, non-deterministic nature. Having established what goes wrong, this part translates these lessons into a practical framework for building a mature AI strategy. This includes using evaluation processes such as the ICE framework to prioritize a project roadmap, building robust governance and compliance using established models such as the NIST AI RMF, and designing a modern data strategy that treats data as a product. Finally, we will cover the need for a scalable AI platform, a principled algorithm selection strategy, and a hybrid “hub-and-spoke” organizational structure to manage change.

This part contains the following chapters:

  • Chapter 1, Understanding the Perils of AI Products
  • Chapter 2, Building the Enterprise AI Strategy
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Key benefits

  • Build AI strategies that align with business goals and maximize ROI
  • Implement enterprise-ready frameworks for MLOps, LLMOps, and Responsible AI
  • Learn from real-world case studies spanning industries and AI maturity levels

Description

AI is only as valuable as the business outcomes it enables, and this hands-on guide shows you how to make that happen. Whether you’re a technology leader launching your first AI use case or scaling production systems, you need a clear path from innovation to impact. That means aligning your AI initiatives with enterprise strategy, operational readiness, and responsible practices, and The AI Optimization Playbook gives you the clarity, structure, and insight you need to succeed. Through actionable guidance and real-world examples, you’ll learn how to build high-impact AI strategies, evaluate projects based on ROI, secure executive sponsorship, and transition prototypes into production-grade systems. You’ll also explore MLOps and LLMOps practices that ensure scalability, reliability, and governance across the AI lifecycle. But deployment is just the beginning. This book goes further to address the crucial need for Responsible AI through frameworks, compliance strategies, and transparency techniques. Written by AI experts and industry leaders, this playbook combines technical fluency with strategic perspective to bridge the business–technology divide so you can confidently lead AI transformation across the enterprise. *Email sign-up and proof of purchase required

Who is this book for?

This book is for AI/ML leaders and business leaders, CTOs, CIOs, CDAOs, and CAIOs, responsible for driving innovation, operational efficiency, and risk mitigation through artificial intelligence. You should have familiarity with enterprise technology and the fundamentals of AI solution development.

What you will learn

  • Design business-aligned AI strategies
  • Select and prioritize AI projects with the highest potential ROI
  • Develop reliable prototypes and scale them using MLOps pipelines
  • Integrate explainability, fairness, and compliance into AI systems
  • Apply LLMOps practices to deploy and maintain generative AI models
  • Build AI agents that support autonomous decision-making at scale
  • Navigate evolving AI regulations with actionable compliance frameworks
  • Build a future-ready, ethically grounded AI organization

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 28, 2025
Length: 382 pages
Edition : 1st
Language : English
ISBN-13 : 9781806115105
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Amazon
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Product Details

Publication date : Nov 28, 2025
Length: 382 pages
Edition : 1st
Language : English
ISBN-13 : 9781806115105
Vendor :
Amazon
Category :
Languages :
Tools :

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Table of Contents

24 Chapters
Part 1: Laying the Groundwork for AI Success Chevron down icon Chevron up icon
Understanding the Perils of AI Products Chevron down icon Chevron up icon
Building the Enterprise AI Strategy Chevron down icon Chevron up icon
Part 2:Aligning Projects with Business Impact Chevron down icon Chevron up icon
Selecting High-Impact AI Projects Chevron down icon Chevron up icon
Beyond the Build: Gaining Leadership Support for AI Initiatives Chevron down icon Chevron up icon
Building an AI Proof of Concept and Measuring Your Solution Chevron down icon Chevron up icon
Part 3: Deploying and Proving ML Value Chevron down icon Chevron up icon
Beyond Accuracy: A Guide to Defining Metrics for Adoption Chevron down icon Chevron up icon
From Model to Market: Operationalizing ML Systems Chevron down icon Chevron up icon
From Metrics to Measurement: Experimentation and Causal Inference Chevron down icon Chevron up icon
Part 4: Emerging Topics: Generative AI and AI Agents Chevron down icon Chevron up icon
Generative AI in the Enterprise: Unlocking New Opportunities Chevron down icon Chevron up icon
Understanding GenAI Operations Chevron down icon Chevron up icon
AI Agents Explained Chevron down icon Chevron up icon
Part 5: Responsible AI and Governance Chevron down icon Chevron up icon
Introduction to Responsible AI Chevron down icon Chevron up icon
Implementing RAI Frameworks, Metrics, and Best Practices Chevron down icon Chevron up icon
Building Trustworthy LLMs and Generative AI Chevron down icon Chevron up icon
Regulatory and Legal Frameworks for Responsible AI Chevron down icon Chevron up icon
The Future of AI Optimization: Trends, Vision, and Responsible Implementation Chevron down icon Chevron up icon
Unlock Your Exclusive Benefits Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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