According to Anthropic, if you’re senior enough, the answer is not yet.
For those early in their career, the signs are harder to ignore. Hiring for workers aged 22–25 in AI-exposed roles is down 16% since late 2022, and the Federal Reserve Bank of New York puts recent graduate underemployment at 42.5%. The evidence is early. Anthropic calls their own data ‘tentative.’ But the emerging pattern is consistent: when someone is promoted or leaves, the role simply wasn’t backfilled.
JPMorganChase’s CFO told analysts last year that managers had been instructed to avoid hiring as AI deploys. The bank has “a very strong bias against having the reflexive response to any given need to be to hire more people.” You can’t rehire into a role that was never posted.
Junior employees weren’t just doing work. They were introducing novel perspectives to legacy systems, asking questions that senior leaders forgot they needed to ask. Most importantly, they were the next generation of managers, directors, and leaders.
When that layer thins out, the work doesn’t disappear. A University of California, Berkeley study published in Harvard Business Review tracked 200 employees at a tech company for eight months. When workers adopted AI tools, seniors didn’t report liberation. They reported task expansion, workload creep, and context-switching overload. Work redistributed upward, in fragments, at the cost of the focus the senior needed to do what only she could do.
Not everyone is buying the efficiency thesis. Amazon Web Services (AWS) CEO Matt Garman called the broader idea of replacing junior employees with AI “one of the dumbest things I’ve ever heard.” His reasoning: junior employees are the least expensive people you have, and the most likely to actually use the AI tools. The ones building fluency the seniors are still resisting.
When your best senior people leave, who’s ready to replace them?