Richard Smith, Johns Hopkins University’s Human Capital Development Lab Professor of Practice, and Arafat Kabir, writer about AI, in their The Wall Street Journal op-ed think that AI is spelling the death knell of entry-level jobs.
When AI automates routine tasks, organizations often find they need experienced employees who can combine AI capabilities with years of business knowledge. What those organizations don’t need is entry-level employees learning the basics. Data shows rising unemployment since 2022 among 22- to 25-year-olds in AI-affected sectors—even while employment for older workers remains stable.
Not so much. The transition from hand-spinning thread from cotton balls—an entry-level job for making cloth—changed with spinning jennies, powered looms, and the like. Entry-level work didn’t disappear, it transitioned to requiring different, and better, skills and the knowledge required to understand the more complex work. Hand spinners and weavers had to upgrade their skill sets and knowledge or go unemployed. New basic employees learned those new skills and gained that new knowledge. Employers who invested in the requisite training prospered, those that didn’t, didn’t.
Similarly, the transition from hand-fabricating and assembling automobiles to the assembly line changed the nature of entry-level work. Henry Ford blew away his competitors when he invested in training his new employees, which along with a small pay raise increased worker retention with its associated reduced labor costs from worker turnover and needing constantly to get new ones trained. OJT of hand crafters no longer could cut it, but the entry-level work, while changed in nature, remained in fact.
So it is with AI when it’s properly put to use. The scut work and grunt work of interns as gophers along with the routine most basic work that will be done by AI applications also does not replace entry-level work; it merely changes the nature of that basic work and, as before, requires a bit more knowledge of how to do it. The existing work force—those older workers—will retire sometime between sooner and later. Their loss will require companies to train their replacements in this new entry-level work, and those that do will move ahead, while those that do not will fall behind.
Smith and Kabir acknowledge as much without, apparently, recognizing so.
[R]ecogniz[e] that AI represents a fundamental shift rather than merely another tool. One example could be focusing on “AI native” tracks in which, instead of starting new employees with routine tasks that AI can handle, they begin with AI oversight and optimization roles. They learn to train, monitor, and improve AI systems while simultaneously building domain expertise—combining technical fluency with business acumen.
Yet, that’s precisely what a tool does. The steam-power was a fundamental shift for industry and industry-related work. It powered mining drills, heavy transportation, forges, and on and on. That fundamental shift, though, was just a means of getting new tools for more efficient work with an associated change in what constituted entry-level work. That basic work ranged from running those new tools to maintaining them to manufacturing them.
As technology evolves, so too does the nature of “entry-level.”
