Can We Trust AI in a Product’s Lifecycle Path?

It’s no longer rumors or rumblings of its use—artificial intelligence (AI) is overwhelming every aspect of our digital lives, work or otherwise. Most newer consumer products tout AI. And a majority of companies already use it in all aspects of operation, or they’re at least testing it out. It’s impacting our engineering life.

Let me give you an example from an NVIDIA GPU Summit experience I had.

I can’t say who this company is, but one small software design group’s owner demands that all of their developers use AI to augment their work. This company’s star senior software developer refused to use it, saying they could write better code. Since this person was their “ace,” they let that mandate slide.

The owner said over time that AI was boosting the overall accuracy and output of their junior devs to just a few rungs below that of the “star ace.” Overall, the output wasn’t as good as the star ace, but the volume was sizable. The owner then demanded the star ace to use AI, to no avail. The owner fired the star ace on the spot.

I can’t say that AI use might be the make or break for anyone’s career. But I can say that AI will be introduced somewhere in your design process or product operation at some point by someone. It’s inevitable.

In the upcoming AI Takeover Week, starting on July 14, we explore what’s out there, how companies are embracing it, and its potential ramifications. We look at AI in the process of design, manufacturing, and operation of products. And we attempt to answer the question of whether can be trusted along the product lifecycle path.

You may have a strong opinion on the matter, one way or another. I encourage you to share your thoughts on each of the pieces in the series. I want to know your thoughts!