The AI Playbook: Mastering the Rare Art of Machine Learning Deployment

在這波AI狂潮裡，為何有人能一飛沖天，有人卻一敗塗地？關鍵就在應用！

機器學習可以說是現今世上最重要的通用技術(General Purpose Technology)，新一波經濟成長將有賴於AI技術的持續發展與應用。但最厲害的工具，往往也是最難使用的！資深企業顧問、前哥倫比亞大學教授Eric Siegel將在本書中向讀者揭示企業布署機器學習專案實所需的關鍵六步驟，讓企業有機會真正實踐AI技術商轉。

In his bestselling first book, Eric Siegel explained how machine learning works. Now, in The AI Playbook, he shows how to capitalize on it.

“Eric Siegel delivers a robust primer on machine learning, the key mechanism in AI. A forward-looking, practical book and a must-read for anyone in the information economy.”
—Scott Galloway, NYU Stern Professor of Marketing; bestselling author of The Four




“An antidote to today’s relentless AI hype—why some AI initiatives thrive while others fail and what it takes for companies and people to succeed.”
—Charles Duhigg, author of bestsellers The Power of Habit and Smarter Faster Better

The greatest tool is the hardest to use. Machine learning is the world’s most important general-purpose technology—but it’s notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What’s missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects from conception to deployment. He illustrates the practice with stories of success and of failure, including revealing case studies from UPS, FICO, and prominent dot-coms. This disciplined approach serves both sides: It empowers business professionals, and it establishes a sorely needed strategic framework for data professionals.


Beyond detailing the practice, this book also upskills business professionals—painlessly. It delivers a vital yet friendly dose of semi-technical background knowledge that all stakeholders need to lead or participate in machine learning projects, end to end. This puts business and data professionals on the same page so that they can collaborate deeply, jointly establishing precisely what machine learning is called upon to predict, how well it predicts, and how its predictions are acted upon to improve operations. These essentials make or break each initiative—getting them right paves the way for machine learning’s value-driven deployment.

What kind of AI does this book cover? The buzzword AI can mean many things, but this book is about machine learning, which is a central basis for—and what many mean by—AI. To be specific, this book covers the most vital use cases of machine learning, those designed to improve a wide range of business operations.