MIT AI researcher Andrew McAfee warned that companies automating entry-level roles can backfire by breaking the “apprenticeship ladder” that builds job-ready expertise. McAfee argued that on-the-job training is how people learn complex work, and that automating too much too quickly reduces both today’s hiring and tomorrow’s workforce development. The reporting ties the warning to broader signals in youth labor markets: declining entry-level postings, elevated unemployment among college graduates, and heightened graduate anxiety about AI replacing entry-level work. The development is relevant to higher education workforce planning, career-services strategy, and employer partnerships that depend on predictable entry-level pathways. For universities, the practical risk is mismatch—graduates may face fewer entry-level learning opportunities even as employers demand AI fluency. Campuses may need to strengthen experiential learning, internships, and curriculum-aligned upskilling to preserve the pipeline that entry-level roles provide.