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Ai project

An AI project is a planned effort to develop, apply, deploy, or evaluate a system or capability that incorporates artificial intelligence.

How 2 Manning books explain it

The Art of AI Product Development

A project that develops a product or solution incorporating artificial intelligence.

How it is used
Frames AI development as an opportunity-led product effort connecting user needs, business goals, technology, and governance.
How deep it goes
Explains decision criteria, collaboration, experimentation, and governance, but stops short of model implementation details.
Examples
Uses predictive inventory optimization, demand variability, waste reduction, client adoption, upsell revenue, and executive pitching as concrete examples.
What you can do after
Evaluate AI opportunities, align cross-functional teams, pitch initiatives, prototype responsibly, and plan iterative launches with safeguards.

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Inside AI

An AI project is an organized effort to design, develop, and deploy an artificial-intelligence solution for a defined objective.

How it is used
Guides teams from business justification through data work, modeling, deployment, and post-deployment improvement.
How deep it goes
Breaks the process into operational stages and decision criteria but leaves algorithm implementation to specialized techniques.
Examples
Uses fraud prevention, customer loss, product associations, and credit-card authorization as concrete project scenarios.
What you can do after
Build an AI project around a modest objective, validate its data and performance, deploy it, and monitor its operation.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.