The AI Playbook, with a new preface by the author: Mastering the Rare Art of Machine Learning Deployment...

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Eric Siegel

The AI Playbook, with a new preface by the author

Name: The AI Playbook, with a new preface by the author
Price: 49.04 AUD
Availability: PreOrder
ISBN: 9780262057240

Mastering the Rare Art of Machine Learning Deployment

Eric Siegel

$54.95 $49.04

Paperback

Forthcoming
Pre-Order now

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English

MIT Press
27 October 2026

Economics

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, aka predictive AI 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.

A note from the author-

The buzzword AI can mean many things, but this book is about the most vital use cases of machine learning, those designed to improve large-scale business operations-aka predictive AI or predictive analytics.

By: Eric Siegel
Imprint: MIT Press
Country of Publication: United States
Dimensions: Height: 229mm, Width: 152mm,
Weight: 369g
ISBN: 9780262057240
ISBN 10: 0262057247
Pages: 256
Publication Date: 27 October 2026
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Forthcoming

Eric Siegel is a leading consultant and former Columbia University and UVA Darden professor. He is the founder of the long-running Machine Learning Week conference series, a frequent keynote speaker, and author of the bestselling Predictive Analytics- The Power to Predict Who Will Click, Buy, Lie, or Die.

Reviews for The AI Playbook, with a new preface by the author: Mastering the Rare Art of Machine Learning Deployment

A Next Big Idea Club Must Read A Tech Tribune best tech book of the week “An antidote to overheated rhetoric of all-powerful AI... helpfully lays out the key steps to deploying the technology we’re now all obsessed with.” —Fast Company “Separates AI fact from AI fantasy.” —The Forecast “In his new book The AI Playbook, Eric Siegel, a leading consultant and former Columbia University professor, helps bridge the gap between ML as a science and a business practice. Siegel delves into the reasons ML projects fail and provides a framework for implementing machine learning in business.” —TechTalks