In order for a project to be successful, there needs to be some positive return on the investment (ROI) involved to get this project off the ground and into production. This ROI can be measured by cost savings, but also by people savings, resource savings, and/or time allocation savings.
A common reason we see AI projects fail is that the ROI is not justified.
In order for an AI project to actually go forward, you need three things in alignment:
- Business feasibility
- Data feasibility
- Technology / execution feasibility
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer we discuss this in greater detail.