New research and workplace reporting are reframing AI’s impact on entry-level hiring as both a productivity and a talent pipeline problem. A Federal Reserve Bank of Atlanta paper revisits Kenneth Arrow’s 1962 “learning on the job” theory, warning that automation may reduce the entry-level “curriculum” firms rely on to build human capital for later career productivity. Other findings reinforce this operational risk: HR leaders increasingly expect higher productivity demands for junior roles and some firms are hiring fewer entry-level workers while shifting tasks to mid-level staff using AI. The D2L and Morning Consult report also notes that only a small share of companies plan to cut entry-level hiring, but a majority say AI is changing what juniors do. In higher education, these shifts raise direct planning questions for curriculum design, experiential learning, and internships that function as on-the-job training substitutes when workplaces change their staffing structures. The combined implication is that career readiness strategies must address not only job skills but also the diminished learning opportunities created by automation of early workplace tasks.