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Managing AI Projects
book

Managing AI Projects

by Malini Jain Runtasewee, Adrián González Sánchez
May 2026
Intermediate to advanced
308 pages
8h 6m
English
O'Reilly Media, Inc.
Content preview from Managing AI Projects

Chapter 1. Introduction to AI Project Management

A few years ago, AI project management wasn’t really a thing. There are several flavors of projects involving AI, machine learning, and related technologies, but managing AI projects didn’t seem to be an area of study for project managers. Somehow, no one thought it would require new techniques or knowledge...until companies started to adopt AI and experience project failure. You probably heard the stories: unjustified return on investment (ROI), only 20% of projects succeeding (based on statistics from Gartner and others), eternal cycles of AI proof-of-conceptionitis (or being afraid to actually move to production and stop the experimentation phase). Implementing AI is not easy. It requires specialization at all levels, from technical roles to executive stakeholders, including all tactical roles at the project, product, program, and portfolio levels.

But still, you may be asking: Why focus on the project manager (PM)? Why is this role so important for the art of managing AI projects? This chapter will explain how PMs contribute to every aspect of AI projects. The following list previews how the role interacts with other project stakeholders:

Executive sponsors

Unlike other tactical managers, project-level professionals focus on the prioritization, planning, implementation, and completion of AI projects. That means that PMs are the point people for sharing relevant news with any executive who wants to understand the progress of ...

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Publisher Resources

ISBN: 9798341641006Errata Page