Artificial intelligence and corporate financing decisions: evidence from capital structure adjustment

Balancing debt levels with capital needs is a key challenge in corporate financing decisions. The speed of capital structure adjustment (SOA) determines how efficiently firms return to their target leverage after deviations, thereby affecting risk control, the cost of capital, and strategic resilience. As artificial intelligence (AI) increasingly permeates corporate operations and governance, whether and how AI enhances SOA has become an important question. This study investigates the impact of AI on SOA using panel data on Chinese A-share listed firms from 2010 to 2023. We employ partial adjustment models and fixed effects estimation, supplemented by alternative AI proxies and leverage measures, system GMM, one- and two-year lag regressions, propensity score matching (PSM), and two-stage least squares (2SLS) methods to ensure robustness. The results show that AI significantly accelerates SOA, primarily by enhancing the information environment and mitigating operational risk. Heterogeneity analyses reveal that the effect is strongest at moderate board independence and among low-growth firms. These findings deepen our understanding of how emerging technologies influence corporate financing decisions and provide practical implications for managers and policymakers seeking to optimize capital structure in the era of AI.