Continuous learning in the ai-integrated workplace: an examination of key determinants

Abstract

AI is reshaping workplace learning, but evidence on how it enables employees’ continuous learning (CL) via cognitive and motivational routes remains scarce in Vietnam. Drawing on Social Cognitive Theory and Self-Determination Theory, we test a model where AI integration in L&D affects CL through AI self-efficacy (ASE) and learning motivation (LM). Survey data from 299 Vietnamese employees across five sectors were analyzed with PLS-SEM and Necessary Condition Analysis (SmartPLS 4.1). AI integration, ASE, and LM each show significant positive effects on CL, with ASE the strongest path. NCA indicates all three are necessary, and AI integration becomes the key bottleneck at higher CL levels. The study links cognitive and motivational mechanisms and urges co-investment in AI infrastructure, AI literacy, and motivating learning design, alongside human-centric upskilling policies. Keywords: AI Integration, AI Self-efficacy, Learning Motivation, Continuous Learning