Dzone iconDzoneAug 28, 2026

Why AI Projects Stall Between Proof of Concept and Production

The scope is narrow, the users are friendly, the data sample is controlled, and the success criteria are usually simple enough to prove that something can work. The demo looks promising, stakeholders get excited, and the team starts talking about production.

Why AI Projects Stall Between Proof of Concept and Production

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The scope is narrow, the users are friendly, the data sample is controlled, and the success criteria are usually simple enough to prove that something can work.

The demo looks promising, stakeholders get excited, and the team starts talking about production.

A proof of concept is often the easiest part of an AI project.

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The useful part

The scope is narrow, the users are friendly, the data sample is controlled, and the success criteria are usually simple enough to prove that something can work. The demo looks promising, stakeholders get excited, and the team starts talking about production. A proof of concept is often the easiest part of an AI project.

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A proof of concept is often the easiest part of an AI project.

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