May 2026
Intermediate to advanced
308 pages
8h 6m
English
Content preview from Managing AI Projects
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Chapter 5. PM Considerations During the Technical AI Lifecycle
The previous chapter detailed an applied methodology and concrete stages from an AI project management perspective: the project before it becomes a project, the key turning points, and the proper way to finalize and deliver the implementation.
Now, we will revisit some technical concepts to complement what you learned in Chapter 2, where you were introduced to specific AI models and technologies. Here, you will learn more about AI tasks and project management responsibilities along the entire technical lifecycle.
The Notion of an AI Lifecycle
An AI lifecycle is a framework for mapping the stages of an AI project, from an idea’s conception to the application’s end of service. There are many versions of AI lifecycles out there. Some focus on the input/output between stages, and others deep-dive into the workstreams that are relevant to each project stage. Some are created for technical purposes, and others see the entire implementation from a compliance perspective. Ultimately, if you compare different versions, you will start to see some key patterns emerge. As a project management professional, you have likely encountered project lifecycles already, so this concept is not completely new. The key goal here is for you to understand all the stages and typical tasks and to connect them to the tactical AI management, strategy, and technical levels from Chapter 1.
The notion of an AI lifecycle is not fully standardized ...
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