There's a more important question than "will AI take our jobs?" Most companies measure AI adoption by headcount reductions and cost savings. But Simon Johnson, 2024 Nobel laureate in Economics (MIT), calls this "just too easy" — automating people away requires almost no management imagination. And that easiness, he argues, is precisely why companies leave the real value of AI on the table. The concept of "pro-worker AI" from MIT economists Acemoglu, Autor, and Johnson — developed with the Brookings Institution — reframes the question entirely: Does this AI make human expertise more valuable, or less necessary? Brookings classifies technologies into five types, and only "new task-creating" technologies are unambiguously good for workers. When AI generates demand for kinds of work that didn't exist before, it represents something categorically different from substitution. Real examples clarify the distinction. Schneider Electric built an AI tool helping electricians troubleshoot machinery — cutting maintenance report time in half while enabling workers to focus on more complex diagnosis. The U.S. Patent Office deployed AI search tools that help examiners find conceptually related documents more precisely, making specialized judgment more valuable. As AI tools spread everywhere, competitive advantage shifts away from which tools you have toward how well you redesign work around them. Title: Pro-Worker AI, Explained URL: The real question for organizations isn't "how many people can AI replace?" — it's "what new things can our people do because of AI?" #AIAndWork# #OrganizationalDesign#