Assess students' ability to analyze how automation and AI influence productivity, employment composition, and wage inequality across industries, testing knowledge of theoretical channels (capital–labor substitution, task reallocation, complementarity, skill-biased technical change), empirical measures (productivity metrics, employment shares, wage percentiles/Gini), identification strategies for causal inference (diff-in-diff, IV), short- vs long-run effects, cross-industry heterogeneity, interpretation of data/case studies, and formulation of evidence-based policy responses.