Mei Peng LowTai Ming Wut0000-0002-9312-9270WEI FONG, POKPOKWEI FONG2025-10-152025-10-152025-07-0610.1080/03601277.2025.2528673https://dspace-cris.utar.edu.my/handle/123456789/11503Malaysia is undergoing a rapid demographic transition and is projected to become an aging nation by 2057. This shift poses significant social and economic challenges, especially in the labor market, where a declining working-age population is particularly concerning. Amid rapid technological advancements, this study explores the roles of artificial intelligence (AI) competency and lifelong learning in enhancing older workers' career resilience. Employing social cognitive theory and social learning theory, the study tested a conceptual framework using partial least squares structural equation modeling (PLS-SEM) and Necessary Condition Analysis (NCA) to identify necessary factors for employability and job security. The findings indicate that lifelong learning significantly enhances career resilience, while AI competency yields mixed results. The results suggest that older workers should continuously acquire relevant skills and knowledge to enhance career resilience later in their careers. Employers are advised to promote lifelong learning and address ageism to counteract the concerns of a shrinking working population.enDISCRIMINANT VALIDITYEMPLOYABILITYjournal-article