Generative artificial intelligence (GenAI) has emerged as a revolutionary technology in education, yet little is known about how GenAI can be specifically utilized to support teacher guidance and holistic student development, particularly in the context of vocational education. Evidence on how GenAI technology can enhance holistic student development in vocational schools, reduce administrative burdens, and support teacher guidance systems is explored in this systematic review. A synthesis of 45 peer-reviewed articles from the Scopus, Web of Science, and ERIC databases, published between 2020 and 2025 in accordance with PRISMA-ScR guidelines, was conducted. Five main thematic areas were identified through thematic analysis: (1) GenAI's function as a pedagogical assistant for individualized teacher support; (2) administrative automation that reduces teacher workload by thirty to forty percent; (3) natural language processing for qualitative analysis of student data; (4) comprehensive student development through career and character guidance; and (5) implementation challenges, including ethical issues, digital literacy gaps, and institutional readiness. These findings highlight GenAI's significant potential in addressing the teacher workload crisis, with approximately 40% of teachers' time spent on administrative tasks, while improving the quality of student guidance. However, its implementation still depends on resolving equity issues, developing robust institutional policies, and adopting human-centered pedagogical approaches. This review provides valuable insights for education practitioners, policymakers, and researchers seeking to implement sustainable AI-based guidance systems in vocational education. Recommendations include structured professional development programs, ethical frameworks for GenAI usage, and context-specific adaptation models for vocational schools, particularly in developing educational contexts.
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