AI Project Failure
Let’s find out why AI projects fail and how to prevent that from happening.
Why do AI projects fail?
Organizations that are new to AI should understand that deploying it isn’t always straightforward. They may only see an ROI (return on investment) after several AI projects have been deployed and when the AI team is more mature and proficient at creating a successful product.
It is very common for many organizations to believe that they have the data necessary to succeed. Still, the data is not readily available when they dig a little deeper. Maybe because the data is in multiple systems, extracting that data is extremely difficult. Or, perhaps they haven’t captured all of the necessary data points.
A quick AI hypothetical
Imagine working on an AI project in which the team attempts to perform predictive maintenance on a specific device. The manufacturer estimates the device’s lifespan to be between 12 and 14 years.
Unfortunately, ...