MIT research scientist Andrew McAfee warned that companies automating entry-level Gen Z roles may harm long-term workforce development by cutting off the “apprenticeship ladder” that trains future talent. In comments tied to the school’s Initiative on the Digital Economy, he argued on-the-job learning is how workers build difficult knowledge capabilities—and that rapid automation risks shrinking the future pipeline. McAfee also tied the point to AI readiness, noting that Gen Z shows far higher adoption of standalone AI tools than prior generations, citing a Deloitte study reporting roughly 76% usage among Gen Z. He argued that delaying or reducing entry-level hiring forfeits early AI fluency that could matter as firms scale AI-enabled operations. The warning landed amid signs of a tightening entry-level market: Handshake reports entry-level postings are down year-over-year and below pre-pandemic levels, while the unemployment rate for college graduates aged 22 to 27 remains elevated compared with recent eras. For universities, career-services leaders, and employers embedded in degree-to-job pathways, the message is a signal to re-examine how AI and automation strategies intersect with internship, co-op, and first-job training models.