The rapid diffusion of artificial intelligence (AI) technologies across industries raises fundamental questions about their implications for corporate governance and external monitoring mechanisms. This study investigates whether and how corporate AI investment influences audit risk using a comprehensive dataset of Chinese listed companies spanning 2011–2023. Measuring AI investment through the aggregation of AI-related software and hardware assets relative to total assets, and capturing audit risk via the absolute deviation of audit fees from expected levels, we employ two-way fixed effects panel regression models to examine this relationship. Our baseline results demonstrate that AI investment significantly reduces audit risk, with a one-unit increase in AI investment associated with a 0.672-unit decrease in audit risk deviation. This finding remains robust across multiple specifications, including instrumental variable estimation using lagged AI investment, propensity score matching, Heckman two-stage correction, system GMM estimation, alternative variable measurements, and industry-year fixed effects models. Mechanism analysis reveals that internal control quality serves as a significant transmission channel through which AI investment mitigates audit risk. Furthermore, auditor industry specialization strengthens the risk-reducing effect of AI investment, suggesting complementarity between technological advancement and professional expertise. Heterogeneity analyses indicate that the audit risk reduction effect is more pronounced in state-owned enterprises, non-heavily-polluting industries, and regions participating in digital infrastructure pilot programs. These findings contribute to the growing literature on the governance implications of digital transformation and offer practical insights for corporate technology investment decisions, audit practice development, and regulatory policy formulation in the context of AI-driven economic transformation.
Yan Li (Wed,) studied this question.