You can also access this resource and many others in Issue 363 of my Talent Edge Weekly newsletter.
Over the past few years, I have tracked organizational layoffs and job cuts through my layoff tracker, largely to monitor shifts in the labor and job market. One observation I have made over the past several months is an increase in the number of layoff announcements citing AI as a reason for workforce reductions. I have also shared in several posts how I believe many of these decisions are being made prematurely, before organizations fully understand how AI is actually changing the work. One example is the elimination or reduction of entry-level roles. A new HBR article puts numbers behind this broader concern, drawing on several data points. For example, it cites a survey of 600 HR leaders whose organizations made AI-driven layoffs, finding that only 8.4% said the restructuring delivered as promised, while one in three reported losing critical skills they had not anticipated losing. The authors argue the more effective approach starts with the work itself, not headcount targets: breaking roles into tasks and redesigning processes around the right mix of human and AI capabilities. They share several ideas for implementing this. As a bonus, I want to reshare one of my one-pagers that tackles another issue related to layoffs: overhiring, which can partly be caused by defaulting to a decision to backfill a recently vacant role without truly understanding whether it is needed. My one-page cheat sheet includes targeted questions to help leaders make that decision, reducing the costly cycle of overhiring, job cuts, and rehiring.
