Investigating the microfoundation of dynamic managerial and organizational capabilities for business model innovation: a mediated-moderated model of artificial intelligence

In rapidly evolving digital environments, organizations must develop dynamic capabilities to drive business model innovation (BMI). This study examines how dynamic managerial capabilities (DMCs), including internal advice-seeking, external advice-seeking, and collaborative sensemaking, translate into BMI through two AI-driven organizational capabilities: artificial intelligence integration capability (AIIC) and AI-augmented coordination flexibility capability. Guided by the dynamic capabilities view (DCV), we construct and empirically test a multilevel model using survey data from 517 managers purposively sampled from Chinese firms undergoing digital transformation. Results from partial least squares structural equation modeling indicate that internal advice-seeking has the strongest direct effect on BMI. Conversely, external advice-seeking most strongly influences AIIC. AI integration enhances coordination flexibility, which in turn drives BMI. The findings support a serial mediation model in which DMCs influence BMI through AI integration and coordination flexibility. Moreover, a data-driven decision-making orientation significantly strengthens the relationship between coordination flexibility and BMI, underscoring the importance of organizational mindset. This study advances the DCV by introducing and validating two AI-driven capabilities that link sensing, seizing, and transforming in strategic renewal. Managers who actively seek external insights, foster collaborative sensemaking, and lead data-driven teams are best positioned to leverage AI for sustainable BMI.