Aligning Cognition with Action in Digital Transformation: A Pathway to Enhancing a Firm’s AI Capability

To substantively advance digital transformation and cultivate AI capability (AIC) for enhanced competitive benefits derived from AI, this study—grounded in signaling theory—uses polynomial regression and response surface analysis on panel data from Chinese A-share listed firms (2013–2023) to investigate the relationship between digital transformation cognition (DTC) and digital transformation action (DTA) configurations and a firm’s AIC. The results demonstrate that DTC–DTA congruence yields a stronger positive effect on AIC relative to incongruent configuration. Moreover, high DTC–high DTA congruence drives significantly greater AIC enhancement than low DTC–low DTA congruence. In incongruent scenarios, high DTC–low DTA configuration exerts a more pronounced impact on AIC than low DTC–high DTA configuration, highlighting the pivotal leading role of strategic cognition. Mechanisms analysis reveals that information asymmetry serves as a mediating pathway, partially masking the impact of DTC–DTA congruence on AIC. Furthermore, under conditions of high equity balance or low policy pressure, the effect of such congruence is significantly amplified. These insights advance the understanding of cognition–action configurations in digital transformation while providing practical implications for firms to develop AI capability to address digital-era challenges.