The impact mechanism of scenario-driven and AI-enabled approaches on the competency of cross-border air logistics talent

China-ASEAN economic cooperation and AI advancement are reshaping cross-border air logistics, driving demand for interdisciplinary talent. This study examines how 'scenario-driven' and 'AI-enabled' approaches enhance talent competency. Based on situated learning and technology enablement theories, a dual-path mediation model was tested using mixed methods: grounded theory analysis identified key scenarios and AI technologies, followed by a survey of 268 students analysed via structural equation modelling. Results show that both approaches directly improve competency and indirectly enhance it through practical ability and innovative thinking, with AI-Enabled approaches having a stronger total effect. The study supports a progressive, integrated teaching model and offers theoretical and practical insights for constructing a deeply integrated 'scenario-AI-capability' talent cultivation model in digital-era logistics education.