Successful AI product creation : a 9-step framework / Shub Agarwal.

Format:

Book

Author/Creator:

Agarwal, Shub, author.

Language:

English

Subjects (All):

Artificial intelligence.

Product management.

Physical Description:

1 online resource (xxii, 282 pages) : illustrations

Place of Publication:

Hoboken, New Jersey : John Wiley & Sons, Inc., [2025]

Summary:

The Essential Guide to AI and Generative AI Product Creation from a Veteran AI Leader and Educator In Successful AI Product Creation: A 9-Step Framework, AI product leader, professor of product management and AI, and industry expert, Prof. Shub Agarwal delivers the ultimate playbook--a comprehensive, step-by-step guide to Building, Scaling, and Integrating AI and Generative AI into real-world products. Drawing from over two decades of experience, this comprehensive guide bridges the gap between AI technology and business impact, ensuring you can navigate the AI revolution with confidence. Featuring Forewords by: Ted Shelton, Chief Operating Officer at Inflection AI (co-founded by Reid Hoffman) Dr. Jia Li, Co-Founder and Chief AI Officer at LiveX AI; Founding Head of R&D at Google Cloud AI; AI Professor at Stanford What You'll Learn: Complete 9-Step AI Product Creation Framework: Master the entire AI product lifecycle from discovery and experimentation to scaling, governance, and AI model lifecycle management. 20+ Real-World Case Studies: Learn from successful AI implementations across healthcare, finance, e-commerce, retail, manufacturing, and big tech companies like Google, Meta, Amazon, and Apple. Traditional AI vs. Generative AI: Understand when to use each approach, how to leverage models like GPT and transformers, and key differences in adoption strategies. AI Model Performance and Ethics: Address challenges like bias, fairness, model drift, and regulatory compliance. Practical Tools and Templates: Access decision-making frameworks, checklists, and internal diagrams that guide seamless execution. Who Should Read This Book? AI Product Managers and Tech Leaders: A strategic and tactical guide for AI integration. Entrepreneurs and Founders: Leverage AI for competitive advantage and scalability. Business Executives and Decision-Makers: Understand AI's potential for growth and optimization. Students and Aspiring AI PMs: Develop industry-ready skills through real-world case studies.

Contents:

Cover

Title Page

Copyright Page

Contents

Preface

Foreword by Jia Li

Bridging the Gap: From Demos to Impactful Products

A Unique Perspective

Why This Book Matters

Foreword by Ted Shelton

Introduction: Creating Successful AI Products-A Nine-Step Framework

The Evolution of AI Product Management

A Personal Journey Through AI

The Nine-Step Framework

Who This Book Is For

Our Journey Ahead

Part I Strategic Foundation

Chapter 1 Mapping Problems to Business Goals for AI Products

Understanding the Role of AI in Business Problem-Solving

The Importance of Aligning AI Solutions with Business Goals

Problem Analysis Framework

Developing a Framework for AI Implementation Decisions

Practical Examples of AI Solutions in Action

The Revolutionization of Generative AI

Endnote

Chapter 2 Curiosity to Learn AI Use Cases and Emerging Technical ML Concepts

The Foundation of Machine Learning

A Walk Through the AI Landscape

Deep Learning and Generative AI-The Frontiers of Innovation

The Model Training Process, Demystified

Advanced AI

Real-World AI: Bridging Theory and Practice

Chapter 3 Experimentation Mindset and Room in the Roadmap to Innovate

The Experimentation Mindset

Key Aspects of an Experimentation Mindset

Experimentation in AI Projects

Integrating Experimentation into the AI Product Roadmap

Real-World Case Studies

Traditional AI vs. Generative AI

Part II Implementation &amp

Integration

Chapter 4 Integrating the MDLC with the SDLC

Understanding the MDLC

Stages of SDLC

Synchronizing the MDLC and SDLC for Seamless Integration

Ensuring Effective Communication and Collaboration Between Teams

Best Practices for Integrated Development and Deployment

Overcoming Common Challenges in Integrating the MDLC and SDLC

Case Studies of Successful MDLC and SDLC Integration

Chapter 5 Scaling Research to Production

Importance of Developing a Research Mindset

Strategies for Developing a Research Mindset

Transitioning from Research to Production

Understanding the Research

Developing Prototypes and Iterative Testing

Generative AI and Traditional AI within Scaling Research to Production

Case Studies of Scaling AI Research to Production

Optimizing Supply Chain Management with Predictive Analytics

Chapter 6 Acceptance Criteria in the World of AI

Understanding Acceptance Criteria in AI

Defining Functional Requirements and Performance Standards

Managing Data Quality, Scalability, and Compliance

Developing a Ramp-Up Plan for AI Deployments

Case Studies of Acceptance Criteria in the World of AI

Part III Sustainable Excellence &amp

Innovation

Chapter 7 Patience and Plan to Surpass Human-Level Performance

The Importance of Patience in AI Development

Strategic Planning for AI Implementation

Understanding the Innovator's Dilemma in AI

Key Strategies for Achieving and Surpassing Human-Level Performance

Innovating with Generative and Traditional AI

Case Studies: Overcoming Initial Underperformance in AI

Chapter 8 Model Explainability, Interpretability, Ethics, and Bias

Understanding Explainability in AI Models

The Significance of Model Interpretability

Ethical Considerations in AI Models

Addressing Bias in AI Models

Balancing Performance, Explainability, and Fairness

Case Studies: Model Explainability, Interpretability, Ethics, and Bias

Traditional AI vs. Generative AI in Model Explainability, Interpretability, Ethics, and Bias

Chapter 9 Model Operations: Model Drift Management

Understanding Model Drift

Key Components of Model Operations

Strategies for Monitoring and Managing Model Drift

The Role of Continuous Data Collection and Retraining

Automation in Model Drift Management

Incorporating Model Operations into the Product Roadmap

Traditional AI vs. Generative AI in Model Drift Management

Case Studies: Model Operations

Chapter 10 AI Is the New UX: Transforming Human Interaction

The Evolution of Intelligence-First Product Management

The Role of an AI-UX Product Manager

AI as the Invisible Interface

Multimodal Interactions

Business Insights: Chat with Data

Balancing Generative AI and Traditional AI in Model Operations

Case Studies: Real-Life Applications of AI as the New UX

Conclusion: The Dawn of Intelligence-First Product Creation-A New Chapter in Human Innovation

Chapter 11 Understanding Generative AI for Product Management

Introduction to Generative AI

Practical Applications of Generative AI

Glossary

Index

EULA.

Notes:

Includes index.

Description based on publisher supplied metadata and other sources.

ISBN:

9781394337859

139433785X

9781394337866

1394337868

OCLC:

1513423092