A string of developments around generative AI and workplace automation are feeding scrutiny of how AI tools will reshape entry-level pathways—an issue universities increasingly address in career services, curriculum, and academic integrity policy. At Notre Dame, a freshman’s AI tool connected to Canvas triggered investigations and account actions after students signed up rapidly; he characterized the software as productivity rather than cheating. The episode follows other campus incidents involving student-built AI systems that forced administrators to recalibrate enforcement approaches. Meanwhile, broader labor-market commentary warns that automating entry-level work too quickly can disrupt training ladders—raising the risk that today’s hiring decisions affect tomorrow’s workforce capability. For higher education leaders, the operational challenge is whether institutional policies treat AI as a learning aid, an assessment risk, or an employment pathway tool—and whether governance structures can keep up with fast-moving student and industry deployment.