Empowering Career Planning for Generation Z Medical Students through Artificial Intelligence: A Strategy Framework Based on Career Self-Management

Abstract

With the expansion of artificial intelligence (AI) across education and employment services, its application in the career planning of medical students has gained growing attention.This study constructs an analytical framework based on the Career Self-Management (CSM) model and integrates data from surveys and focus groups with Generation Z medical students.Five major challenges in AI-driven career guidance are identified, spanning goal ambiguity, low trust in algorithms, functional misalignment, lack of feedback mechanisms, and ethical concerns.Accordingly, the study proposes a four-stage, five-strategy framework grounded in the CSM process-cognitive scaffolding, pathway suggestion, behavioral execution, and dynamic feedback.These strategies emphasize transparency, personalization, and developmental continuity.The findings contribute both theoretically and practically to the digital transformation of medical education, offering a path toward more sustainable and student-centered career development supported by AI.

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