the Impact of Artificial Intelligence Capability on Corporate Financial Performance through the Mediating Role of Financial Decision-Making Quality
TL;DR
The proposed mechanism that AI capability creates financial value when technological resources are translated into timely, evidence-based, and economically sound financial decisions supports the proposed mechanism that AI capability creates financial value when technological resources are translated into timely, evidence-based, and economically sound financial decisions.
Abstract
This study examines the impact of Artificial Intelligence Capability (AIC) on Corporate Financial Performance (CFP) through the mediating role of Financial Decision-Making Quality (FDMQ). A simulation-based quantitative explanatory design was applied to 200 computer-generated Likert-scale observations calibrated to represent finance and accounting decision contexts in AI-enabled organizations. The analysis uses instrument validity and reliability testing, multiple linear regression, and mediation analysis following PROCESS Model 4 logic with 5,000 bootstrap resamples in IBM SPSS Statistics. The results show that AIC positively affects FDMQ (β = 0.617, p < 0.001) and retains a significant direct effect on CFP after the mediator is included (β = 0.316, p < 0.001). FDMQ also has a positive effect on CFP (β = 0.473, p < 0.001), while the outcome model explains 50.8% of the variance in CFP. The indirect effect is significant (B = 0.319; 95% bootstrap CI [0.231, 0.412]), indicating partial mediation. The findings support the proposed mechanism that AI capability creates financial value when technological resources are translated into timely, evidence-based, and economically sound financial decisions.
