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

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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Publication Details

Journal
International Journal of Academic Research in Business and Social Sciences
Published
2025-07-20
DOI
https://doi.org/10.6007/ijarbss/v15-i7/25943
Primary Topic
Health and Well-being Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Bity Salwana Alias, Yiyi Quan
International Journal of Academic Research in Business and Social Sciences
Health and Well-being Studies
article

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

Bity Salwana Alias, Yiyi Quan
article en

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.

International Journal of Academic Research in Business and Social SciencesVol. 15(7)
National University of Malaysia (MY)
Openalex Percentile: Top 75%
Health and Well-being Studies
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Empowering Career Planning for Generation Z Medical Students through Artificial Intelligence: A Strategy Framework Based on Career Self-Management — Bity Salwana Alias, Yiyi Quan · International Journal of Academic Research in Business and Social Sciences (2025) | TGRS Research Map | TGRS