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Purpose Despite the widespread adoption of artificial intelligence (AI) in knowledge-based work, uncertainty remains about when AI-augmented work improves organizational agility. This study aims to address this gap by explaining when and how AI-augmented work translates into perceived organizational agility, focusing on the roles of knowledge integration and meaningfulness. Design/methodology/approach This study involved 554 employees of companies in Indonesia that have adopted AI technology or AI-based digital systems to support knowledge-based work. Data were analyzed using the PROCESS macro approach. Findings AI-augmented work has a positive effect on perceived organizational agility, both directly and indirectly through knowledge integration. The results reveal an asymmetric pattern, where meaningfulness strengthens the indirect effect via knowledge integration but weakens the direct effect. These findings suggest that AI operates through two complementary mechanisms: as a compensatory resource when meaningfulness is low and as a developmental enabler when meaningfulness is high. Research limitations/implications AI-augmented work contributes to organizational agility by integrating knowledge under certain meaningfulness conditions. Future research could further examine how different knowledge practices and AI arrangements affect organizational contexts. Practical implications Organizations must align AI implementation with knowledge management practices and human resource policies to maximize the adaptive benefits of AI. Originality/value This research contributes to the knowledge management literature by integrating dynamic capability view and job demands–resources theories to explain how AI contingencies shape organizational agility.
Kornelius et al. (Tue,) studied this question.