AI’s Hidden Talent Risk: Skill Loss, Not Job Loss
When AI absorbs foundational junior work, organizations may gain efficiency while weakening the repetition that builds intuition, pattern recognition, and judgment.
What if the real AI problem is not job loss, but skill loss?
The first years of a career used to be full of repetition: research, drafting, basic analysis, cleaning data, building decks, and writing simple code.
Much of that work was tedious. It was also training.
Now AI can absorb more of it. Bloomberg recently pointed to research showing a widening split between senior and junior employment at companies adopting AI.
If junior employees receive fewer opportunities to perform foundational work, they may also receive fewer opportunities to build intuition, pattern recognition, and judgment.
The future junior employee may need to start closer to the middle: reviewing outputs, challenging assumptions, and making decisions earlier than previous generations had to.
That sounds more efficient. It also sounds harder.
If we remove the reps, how do we still build the judgment?