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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

Trends and Insights Across Industry

In the previous chapter, we looked at how the rising tide of artificial intelligence (AI) is affecting companies across the spectrum, as well as the ways AI is affecting companies within their own operations. In this chapter, we will look at the various ways we’re seeing AI trending across industries, through the lens of prominent and respected research organizations, in an effort to inspire product managers and entrepreneurs out there to begin to formulate their strategies by elevating their products into AI products. We will look at the key growth areas for AI integration based on the conglomeration of research and trend analysis from Forrester, Gartner, and McKinsey. In addition, we will go over the various considerations they must keep in mind when attempting to approach AI, including AI readiness and enablement.

Analyzing trends and understanding the growth areas for AI and machine learning (ML) adoption can open us up to powerful...

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