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AI Product Manager's Handbook

You're reading from   AI Product Manager's Handbook Build, integrate, scale, and optimize products to grow as an AI product manager

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835882849
Length 484 pages
Edition 2nd Edition
Languages
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Author (1):
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Irene Bratsis Irene Bratsis
Author Profile Icon Irene Bratsis
Irene Bratsis
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Table of Contents (26) Chapters Close

Preface 1. Part 1: Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Understanding the Infrastructure and Tools for Building AI Products FREE CHAPTER 3. Model Development and Maintenance for AI Products 4. Deep Learning Deep Dive 5. Commercializing AI Products 6. AI Transformation and Its Impact on Product Management 7. Part 2: Building an AI-Native Product
8. Understanding the AI-Native Product 9. Productizing the ML Service 10. Customization for Verticals, Customers, and Peer Groups 11. Product Design for the AI-Native Product 12. Benchmarking Performance, Growth Hacking, and Cost 13. Managing the AI-Native Product 14. Part 3: Integrating AI into Existing Traditional Software Products
15. The Rising Tide of AI 16. Trends and Insights Across Industry 17. Evolving Products into AI Products 18. The Role of AI Product Design 19. Managing the Evolving AI Product 20. Part 4: Managing the AI PM Career
21. Starting a Career as an AI PM 22. What Does It Mean to Be a Good AI PM? 23. Maturing and Growing as an AI PM 24. Other Books You May Enjoy
25. Index

Anticipating potential risks

Part of the specialization that takes place in the current form of an AI PM is knowledge of what can go wrong. Your AI features may be taking certain liberties with your customers’ data, and it’s your job as a PM to anticipate the potential risks your product might create for your users. As a PM, you’re looking to address the most important business problems your users have with your product, but you’re also looking to minimize potential adverse effects.

I know, we got you all jazzed up about being a fearless AI product manager only to then bring up the things you should be afraid of because we want to make a distinction. I’d rather you be afraid of the potentially harmful side of AI than be afraid of the complexity of AI systems. Understanding the structure and complexity is the easy part. Making sure this complexity is handled properly is the hard part. For example, rather than worrying about where to start with...

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