Cross-sectional text analysis reveals selective technical and soft-skill gaps in vocational AI training, highlighting work-integrated learning as a key driver of industry alignment.
China’s rapid artificial intelligence (AI) expansion has intensified demand for graduates who combine applied technical skills with professional competencies. This study examines the alignment between vocational AI curricula and employer skill demand using 498,331 job advertisements from 2020 to 2024 and 46 institutional training plans. We develop a bilingual taxonomy of 198 hard- and soft-skill keywords and calculate a demand-weighted coverage index, supported by bootstrap, permutation and robustness checks. Results indicate a selective technology lag: programming and AI practicum courses align relatively well, while cloud computing and big-data competencies remain less visible in curricula. Soft-skill coverage is also uneven, with many professional attributes implicit rather than systematically embedded. Work-integrated learning shows the strongest overall alignment, suggesting that practicums, internships and capstone projects are key mechanisms for curriculum renewal.
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Xiao et al. (2026) studied this question.
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