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Concluding AI Prototyping Projects
How to go from prototype to production with AI
AI prototyping projects are short-lived and will typically have one of a few different conclusions:
- A finding that the project is viable and can be converted to a real system with additional engineering effort.
- Determining that the project is not currently viable with the data available to the organization and the currently available technology.
- A demonstration of partial progress, obstacles overcome, obstacles identified, and a request for additional time and resources to determine project viability.
Note that none of the expected outputs of an AI prototyping project is a deployable AI product — your goal is to determine viability of a project with the organization’s data and technical team.
AI prototyping projects will typically end in a formal report and/or presentation with recommendations to senior leadership on what the next steps of the project should be. These steps will usually result in a direction to suspend or continue the project — potentially converting the prototype to a real AI application that is deployed to real users.
In this fifth and final article in the AI Prototyping Projects series let’s talk through the details of these steps as AI prototyping projects invariably conclude.
