Application of AI Models in Dynamic Talent Adaptation between Industry and Education: A Case Study of Data from Digital Genealogy Cloud Platform
DOI:
https://doi.org/10.65455/srezr230Keywords:
AI model, Industry-Education Talent, Dynamic Adaptation, Digital Genealogy Cloud Platform, Vocational Education, Macao Greater Bay AreaAbstract
This study examines the application of AI models in dynamic talent adaptation between industry and education, using data from the Digital Genealogy Cloud Platform as a research sample. It analyzes current challenges in industry-education talent alignment and elaborates on the pivotal role of AI models. Through in-depth mining and analysis of platform data, the research demonstrates how AI models leverage big data, artificial intelligence, and knowledge graphs to achieve precise digital integration across industrial chains, talent pipelines, and educational systems. The findings reveal that AI models not only assist vocational colleges in optimizing program structures and innovating talent cultivation models, but also facilitate deep collaboration between schools and enterprises. This enhances the alignment between talent development and industrial demands, providing robust support for the digital transformation and high-quality development of vocational education. Additionally, it offers new perspectives and practical solutions to address fundamental issues in industry-education integration.References
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