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

Product typeBook

Published inFeb 2023

Reading LevelIntermediate

PublisherPackt

ISBN-139781804612934

Edition1st Edition

Languages

Python

Concepts

Artificial Intelligence

Author (1)

Irene Bratsis

Part 2 – Building an AI-Native Product

Understanding what it takes to manage an AI program is a prerequisite when it comes to AI product management. Now that we’ve covered the basics of that in Part 1, we can move on to contextualize the outputs of that AI program in your AI- native product in this second part.

This part consists of five chapters addressing the various relevant areas when going to market with a new product built with AI from the very beginning. We will cover the basics when it comes to creating an AI-native product, productizing the AI/ML service that powers it, positioning that product for various groups, AI/ML options you can take when building, and how that all relates to performance benchmarking, costs, and growth. We’ll understand both tactical and strategic considerations when launching an AI/ML- native product by the end of this part.

This part comprises the following chapters:

Chapter 6, Understanding the AI-Native Product...

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Author (1)

Irene Bratsis

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.
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