Wharton AI expert says young job seekers need to focus on something other than skills (www.businessinsider.com)

Wharton professor Ethan Mollick argues that young job seekers should prioritize mastering concrete tasks rather than narrowly learning AI-related skills that can quickly become obsolete. He says AI’s real workplace value is in "task distribution"—automating parts of a job while leaving humans to the elements machines struggle with. That means applicants who can clearly instruct models, critically evaluate outputs, and be “expert enough” to judge quality will stay ahead. Mollick also recommends broad subject knowledge, including the humanities, and stronger soft skills (communication, leadership, organization) as entry-level roles are reshaped or threatened by automation. For the AI/ML community this reframes priorities: design and training should emphasize complementary human–AI workflows, task-level interfaces, and tools that make model outputs easy to inspect and judge. Curricula and hiring should tilt toward domain expertise, critical evaluation, and prompt engineering rather than transient technical minutiae. Practically, teams need better methods for distributing subtasks between humans and models, metrics for output fidelity, and workplace restructuring to preserve meaningful, non-automatable work—a point Mollick stresses as urgent given AI’s rapid adoption and impact on early-career employment.