Career Anxiety in the Age of AI
Examining AI Disruption as a Risk Factor and Optimism as a Protective Factor among University Students - A Literature Review
Keywords:
Career Anxiety, Artificial Intelligence, Optimism, Final-Year University Students, Protective FactorAbstract
The rapid integration of artificial intelligence (AI) into the labor market has created new sources of career-related uncertainty among university students approaching graduation. At the same time, optimism may function as a psychological resource that supports adaptive responses to career challenges. This literature review examined career anxiety among university students through two complementary perspectives: AI disruption as a potential risk factor and optimism as a potential protective factor. A structured literature search was conducted using the Scopus database, resulting in 425 records. Following screening and eligibility assessment, 20 articles were included, comprising 16 primary empirical studies and 4 systematic literature reviews. The findings indicate that AI-related constructs, including AI anxiety, AI attitudes, AI acceptance, and perceived AI job threat, were generally associated with career anxiety and related outcomes such as career stress, job-seeking anxiety, and difficulties in career decision-making. In contrast, optimism and psychological capital were consistently associated with more favorable career-related outcomes and lower career-related distress. However, the reviewed studies rarely examined AI-related risks and optimism within the same empirical framework. Thus, whether optimism buffers AI-related career anxiety remains insufficiently established and warrants further investigation.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Amelia Husna Adindia Br. Matondang, Anna Armeini Rangkuti, Iriani Indri Hapsari

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish in this journal agree to the following terms:
Copyright in any article is held by the author.
The author grants the journal, publication rights with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
Authors may enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., posting it to an institutional repository or publishing it in a book), with an acknowledgment of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in an institutional repository or on their website) prior to and during the submission process, as this can lead to productive exchanges, as well as earlier and greater citation of published work.