Abstract: Artificial intelligence is fundamentally reshaping organizational skill portfolios in ways that extend beyond simple job displacement. Drawing on analysis of 67 million job postings in China (2019–2024), recent empirical work reveals a pattern of "de-coring"—a simultaneous flattening of skill importance hierarchies, broadening of portfolio dispersion, and divergence between skill share movements and within-category depth requirements. This restructuring concentrates most heavily in small, lower-threshold firms with minimal reskilling infrastructure. The findings challenge education systems oriented toward single-track vocational specialization and suggest policy interventions emphasizing portable competency frameworks, modular credentialing, and employer–government cost-sharing mechanisms. This article synthesizes emerging evidence on AI's compositional effects on labor demand, contextualizes the phenomenon within sustainable workforce development frameworks, and outlines organizational and policy responses aligned with the 2030 Agenda's commitment to inclusive, quality education and decent work.
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