ARTIFICIAL INTELLIGENCE IN PERSONALIZED LEARNING FOR CAREER GUIDANCE: A SYSTEMATIC LITERATURE REVIEW

Abstract

This study presents a systematic literature review (SLR) examining how Artificial Intelligence (AI) has been applied to support personalized learning systems in career guidance for secondary and higher education students. Using the PRISMA 2020 framework, four major databases Scopus, Web of Science, ERIC, and IEEE Xplore, were systematically searched for articles published between 2018 and 2025. A total of 18 empirical studies met the inclusion criteria and were analyzed thematically. The results reveal that AI technologies such as machine learning, chatbots, recommender systems, and adaptive learning platforms have been effectively used to enhance career clarity, self-efficacy, and decision-making among students. The findings extend the Social Cognitive Career Theory (SCCT) by integrating adaptive AI as a contextual factor influencing learners’ career choices and confidence. This review highlights both opportunities and challenges of AI integration in career counseling, emphasizing ethical considerations, data privacy, and counselor readiness. It concludes that AI serves as a transformative force in developing human-centered, data-informed, and adaptive career guidance systems for the digital era