10/19/2026
We're watching an interesting shift in the job market.
Companies are spending enormous amounts of money on AI, but somebody still has to show up with actual tools and build the infrastructure to make it work.
And apparently, some of those people are getting paid VERY well.
According to this post, two young electricians just left their jobs for positions paying $3,000 a week at a data center.
That's $156,000 a year if they're earning that amount for all 52 weeks.
Now, before everybody rushes out to become an electrician, that's certainly not the typical salary. Jobs paying that much often involve specialized skills, overtime, demanding schedules, or temporary project work.
But I think there's something fascinating happening here.
We're spending so much time talking about AI replacing accountants, programmers, customer service representatives, and practically every other white-collar profession.
Meanwhile, who's going to build the data centers? Install the electrical systems? Keep the cooling equipment running? Maintain the infrastructure that makes all this technology possible?
And these facilities consume an absolutely ridiculous amount of electricity.
I've spent nearly 20 years in financial planning, and I've always believed people should look at the actual economics of a career before spending a fortune on education.
College can be a fantastic investment. So can learning a skilled trade.
But I think we're going to see some pretty interesting opportunities over the next several years for people who have the technical skills to build and maintain the physical infrastructure behind AI.
And here's the part I find hilarious.
We could end up in a situation where somebody spends four years studying artificial intelligence, only to graduate and discover that the electrician installing the power systems for the AI data center is making considerably more money.
I'm certainly not suggesting every electrician is going to make $150,000 a year.
But I wouldn't underestimate the earning potential of someone who knows how to do the work that keeps all this technology running.
All those billions being invested in AI have to go somewhere, and a pretty significant amount of that money is going toward things that still require actual human beings showing up and doing the work.
