Abstract: As artificial intelligence capabilities advance at unprecedented speed, understanding its labor market implications requires moving beyond simplistic measures of technical exposure. This article synthesizes recent empirical evidence from major AI platforms to propose a multidimensional framework for assessing workforce impact. Drawing on usage data from over 150 million jobs and emerging research on AI adoption patterns, we argue that technical capability, human necessity, demand elasticity, and observed usage must be considered together to identify where labor market pressure may emerge first. Early evidence suggests minimal aggregate employment disruption to date, though specific occupation groups—particularly younger workers in highly exposed roles—show preliminary signs of hiring slowdowns. We outline differentiated policy responses aligned with four distinct transition pathways: jobs at higher automation risk, jobs requiring reorganization, jobs likely to expand with AI, and jobs facing less immediate change. This framework aims to help policymakers, business leaders, and workers navigate the AI transition with better information about where and how workforce effects are most likely to materialize.
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