The AI Product Manager's Handbook: Develop a product that takes advantage of machine learning to solve AI problems

Master the skills required to become an AI product manager and drive the successful development and deployment of AI products to deliver value to your organization.

Purchase of the print or Kindle book includes a free PDF eBook.

Key Features

• Build products that leverage AI for the common good and commercial success
• Take macro data and use it to show your customers you’re a source of truth
• Best practices and common pitfalls that impact companies while developing AI product

Book Description

Product managers working with artificial intelligence will be able to put their knowledge to work with this practical guide to applied AI. This book covers everything you need to know to drive product development and growth in the AI industry. From understanding AI and machine learning to developing and launching AI products, it provides the strategies, techniques, and tools you need to succeed.

The first part of the book focuses on establishing a foundation of the concepts most relevant to maintaining AI pipelines. The next part focuses on building an AI-native product, and the final part guides you in integrating AI into existing products.

You’ll learn about the types of AI, how to integrate AI into a product or business, and the infrastructure to support the exhaustive and ambitious endeavor of creating AI products or integrating AI into existing products. You’ll gain practical knowledge of managing AI product development processes, evaluating and optimizing AI models, and navigating complex ethical and legal considerations associated with AI products. With the help of real-world examples and case studies, you’ll stay ahead of the curve in the rapidly evolving field of AI and ML.

By the end of this book, you’ll have understood how to navigate the world of AI from a product perspective.

What you will learn

• Build AI products for the future using minimal resources
• Identify opportunities where AI can be leveraged to meet business needs
• Collaborate with cross-functional teams to develop and deploy AI products
• Analyze the benefits and costs of developing products using ML and DL
• Explore the role of ethics and responsibility in dealing with sensitive data
• Understand performance and efficacy across verticals

Who this book is for

This book is for product managers and other professionals interested in incorporating AI into their products. Foundational knowledge of AI is expected. If you understand the importance of AI as the rising fourth industrial revolution, this book will help you surf the tidal wave of digital transformation and change across industries.

Table of Contents

1. Understanding the Infrastructure and Tools for Building AI Products
2. Model Development and Maintenance for AI Products
3. Machine Learning and Deep Learning Deep Dive
4. Commercializing AI Products
5. AI Transformation and Its Impact on Product Management
6. Understanding the AI-Native Product
7. Productizing the ML Service
8. Customization for Verticals, Customers, and Peer Groups
9. Macro and Micro AI for Your Product
10. Benchmarking Performance, Growth Hacking, and Cost
11. The Rising Tide of AI
12. Trends and Insights across Industry
13. Evolving Products into AI Products

Irene Bratsis is a director of digital product and data at the International WELL Building Institute (IWBI). She has a bachelor's in economics, and after completing various MOOCs in data science and big data analytics, she completed a data science program with Thinkful. Before joining IWBI, Irene worked as an operations analyst at Tesla, a data scientist at Gesture, a data product manager at Beekin, and head of product at Tenacity. Irene volunteers as NYC chapter co-lead for Women in Data, has coordinated various AI accelerators, moderated countless events with a speaker series with Women in AI called WaiTalk, and runs a monthly book club focused on data and AI books.