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The AI Product Manager's Handbook

You're reading from  The AI Product Manager's Handbook

Product type Book
Published in Feb 2023
Publisher Packt
ISBN-13 9781804612934
Pages 250 pages
Edition 1st Edition
Languages
Author (1):
Irene Bratsis Irene Bratsis
Profile icon Irene Bratsis

Table of Contents (19) Chapters

Preface 1. Part 1 – Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Chapter 1: Understanding the Infrastructure and Tools for Building AI Products 3. Chapter 2: Model Development and Maintenance for AI Products 4. Chapter 3: Machine Learning and Deep Learning Deep Dive 5. Chapter 4: Commercializing AI Products 6. Chapter 5: AI Transformation and Its Impact on Product Management 7. Part 2 – Building an AI-Native Product
8. Chapter 6: Understanding the AI-Native Product 9. Chapter 7: Productizing the ML Service 10. Chapter 8: Customization for Verticals, Customers, and Peer Groups 11. Chapter 9: Macro and Micro AI for Your Product 12. Chapter 10: Benchmarking Performance, Growth Hacking, and Cost 13. Part 3 – Integrating AI into Existing Non-AI Products
14. Chapter 11: The Rising Tide of AI 15. Chapter 12: Trends and Insights across Industry 16. Chapter 13: Evolving Products into AI Products 17. Index 18. Other Books You May Enjoy

Highest growth areas – Forrester, Gartner, and McKinsey research

In this section, we will be taking a look at some of the growth areas of AI from some of the most prominent research and consulting groups. Understanding what the signals are saying gives us the motivation and foresight to be able to anticipate some of the greatest opportunities that lie ahead. This is particularly helpful in the context of revolutionizing a business or product toward AI because many product managers and technologists may be at odds about which specific areas of a product or service they might want to begin bolstering with AI capabilities.

Some of the top growth areas we will look at based on the conglomeration of research and trend analysis from Forrester, Gartner, and McKinsey in the following subsections are embedded AI, ethical AI, creative AI, and autonomous AI development. Embedded AI will look at AI that’s applied and integrated into the operations of organizations and foundations...

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