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A few weeks ago, I shared the Stanford Institute for Human-Centered AI’s 2026 AI Index Report, one of the most comprehensive annual reports on the state of AI. While there was much to unpack in the 400+ page report, one finding I highlighted was that early-career workers in AI-exposed roles, such as software development and customer support, have experienced meaningful employment declines, while mid-career and senior workers in those same roles have held steady or grown. This matters because entry-level roles help people build the tacit knowledge, judgment, and leadership capabilities that senior roles eventually require. Organizations that automate away entry-level positions without rethinking early-career talent strategies may find their leadership pipelines weakening in the years ahead. In a new article, Amy C. Edmondson and Tomas Chamorro-Premuzic argue that the smarter path is to redesign entry-level jobs rather than eliminate them. They offer four tactics, including building critical thinking alongside AI use. One example they cite is banking, where junior analysts participate in “red teaming” exercises that require them to challenge AI outputs for incorrect assumptions, missing data, and logical flaws, and then defend their critique to senior colleagues. Amy and Tomas also cite research in Science showing that novices who accept AI outputs uncritically can perform worse than those who reason through problems themselves, reinforcing why building the capability to question AI outputs early matters. Do you have a strategy for redesigning your organization’s entry-level roles before the pipeline gap shows up in your leadership bench?
