Accelerated depreciation policies allow firms to front-load depreciation allowances, generating a substantial intertemporal tax shield that reduces the cost of capital. Leveraging China’s 2014 accelerated depreciation policy for fixed assets as a quasi-natural experiment, this study employs a Difference-in-Differences (DID) method to examine its impact on corporate artificial intelligence (AI) adoption. Our results indicate that the tax incentive serves as a ‘stepping stone’, significantly promoting the uptake of AI technologies in pilot firms. This positive outcome primarily operates through two taxpayer-side mechanisms: alleviating financing constraints and upgrading human capital structures. Shifting the focus from taxpayers to tax administration, moderation analysis distinguishes between administrative services and administrative enforcement by revealing that policy effectiveness is strengthened by streamlined services rather than stringent enforcement. Heterogeneity analysis further demonstrates that the AI-promoting effect is more pronounced for large-scale or recession-stage firms, as well as those in low-uncertainty environments. Finally, we bridge the gap between tax incentives and market stability by showing that the tax incentive suppresses stock price crash risk, revealing its crucial role in fortifying firm resilience and mitigating financial risks. This study provides empirical evidence on how targeted tax incentives catalyse corporate AI adoption, offering policy implications for facilitating high-quality economic development.
Zhu et al. (Tue,) studied this question.