It seems that newly minted college graduates are having trouble getting those entry level, low-paying jobs that used to be virtual guarantees in most avocations. Employers are discovering that AI can do many of those entry level jobs just fine, so they’re only interested in hiring folks with a few (say 5-ish) years of actual experience into those jobs that need that experience.

The question becomes what to do after those 5-ish years when those relatively experienced employees move on. Having hired few to no inexperienced folks fresh out of college, there now is no pool of somewhat experienced folks from which to hire.

My thought: use AI to train those who are inexperienced, both new graduates and by now 5-ish years post-college and still inexperienced, to do the entry-level and the somewhat experience-needing work. Continue that cycle as AI advances into the work heretothen requiring more experience, using AI to train employees into those yet more experience-needing positions.

Humans are always going to be better than robots at doing work that requires actual thinking, including jobs that don’t require much thinking directly but do require interaction with other humans in teamwork and/or collaboration (which are not the same thing), with supervisors, even with robots. It also takes humans to train that thinking, and robots can be useful tools in that training.

Carlyle, an investment firm, already is doing this sort of thing, but it needs to get more widespread.

The investment firm Carlyle now pitches to prospective hires that they won’t be doing grunt work. Junior hires go through AI training and a program called “AI University” in which employees share best practices and participate in pilot programs, said Lúcia Soares, the firm’s Chief Information Officer.
In the past, she said, junior hires evaluating a deal would find articles on Google, request documents from companies, review that information manually, highlight details, and copy and paste information from one document to another. Now, AI tools can do almost all of that.
“That analyst still has to go in and make sure the analysis is accurate, question it, challenge it,” she said. “The nature of the brain work that needs to go into it is very much the same. It’s just the speed at which these analysts can move.”