Building Dynamic AI Capabilities for Sustainable Employee Performance: The Roles of Trust, Knowledge Management, and Competitive Advantage

The accelerated adoption of Artificial Intelligence (AI) is reshaping organizational landscapes, yet many firms struggle to translate AI investments into meaningful employee performance gains due to insufficient integration between AI systems and organizational capabilities. This study proposes a comprehensive model examining how AI system implementation and trust in AI influence sustainable employee performance through dynamic capabilities, company competitiveness, and knowledge management capacity. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with data from Indonesian firms, the research validates an integrated framework connecting technological, psychological, and organizational factors. Findings reveal that both AI implementation and trust significantly enhance organizational capabilities, with AI implementation showing stronger effects. Company competitiveness and dynamic capabilities serve as critical mediators between AI factors and employee performance, while knowledge management capacity shows no direct performance impact. The model explains 78.3% of variance in employee performance, demonstrating substantial predictive power. Results emphasize that sustainable performance requires simultaneous development of strategic capabilities supported by trust mechanisms, not merely technological deployment. This study contributes by integrating previously isolated constructs and provides practical guidance for managers aligning AI initiatives with capability development and competitive positioning for organizational resilience.