The first jobs you take after college are disappearing — not because there aren’t enough roles, but because AI is stealing the work that once taught you how to work. Companies are gaining efficiency today, but who will learn to lead tomorrow?
Microsoft’s Future of Work report suggests artificial intelligence is not hitting the workforce evenly. Instead of replacing senior experts, it is erasing the earliest steps of a career — the small tasks that once trained new employees.
This is already measurable; in occupations highly exposed to AI, employment among workers aged 22 to 25 has fallen about 13%, indicating companies are cutting entry-level work before anything else.
The First Rung Of The Ladder Is Going Away
For decades, organizations relied on junior staff to handle routine cognitive work: drafting documents, summarizing meetings, researching background information, organizing data, and preparing updates. The work was repetitive but essential. It taught context, judgment, and how decisions get made.
AI systems now perform those same tasks instantly.
Microsoft’s research finds workers are saving time and increasing output with AI assistance, but the time savings come from automating the exact activities that historically functioned as on-the-job training.Â
Instead of gradually learning by doing, early-career workers increasingly review or prompt AI rather than produce work themselves.
Companies gain efficiency immediately, but they lose the training process gradually.
Productivity Up, Learning Down
Employees are gaining hours back in their day and completing more work, but overreliance on AI can reduce independent thinking and judgment, especially for less experienced workers who have not yet built professional instincts.
Previously, competence developed through repetition: writing dozens of briefs, researching countless topics, fixing mistakes, and receiving corrections. Those cycles created expertise.
Now many of those repetitions never happen.
Junior employees interact with outputs rather than problems, which compresses experience but also weakens skill development. Over time, organizations may end up with workers who can supervise AI tools but lack the underlying understanding those tools were meant to accelerate.
The Hidden Risk To Talent Pipelines
The immediate business case for automation is clear: fewer beginner tasks means fewer beginner roles. But those roles were actually talent pipelines.
Entry-level jobs produced mid-level professionals, future managers, and institutional knowledge holders. By removing the lowest-stakes work, companies may also be removing the stage where employees learn judgment safely.
Microsoft warns this could create a delayed capability gap. Companies may retain senior expertise today while quietly reducing the number of people capable of replacing it later.
In other words, automation can improve short-term efficiency while weakening long-term workforce sustainability.
AI Also Changes Workplace Relationships
There is also another unintended consequence: collaboration patterns are transitioning. When AI replaces discussion, drafting, or shared problem-solving, workers interact less with each other.
Organizations risk weakening mentorship, informal learning, and mutual support — elements historically strongest at the junior level where employees ask the most questions and build networks fastest.
Remove beginner work, and you remove many beginner conversations.
A Structural Change, Not A Temporary One
This is not a typical automation cycle where certain jobs disappear and others emerge quickly in their place. Instead, AI is compressing career progression by removing the apprenticeship stage.Â
Senior roles still exist, but fewer workers are moving through the steps required to reach them.
The early 13% employment decline among young workers may be the first signal of a longer transition: a workforce where companies increasingly hire experience rather than develop it.
The challenge ahead is rebuilding how expertise forms when the practice work no longer needs to be practiced.
